diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml index d8c043821..036592135 100644 --- a/.github/ISSUE_TEMPLATE/config.yml +++ b/.github/ISSUE_TEMPLATE/config.yml @@ -3,3 +3,6 @@ contact_links: - name: PyPSA Mailing List url: https://groups.google.com/forum/#!forum/pypsa about: Please ask and answer general usage questions here. +- name: Stackoverflow + url: https://stackoverflow.com/questions/tagged/pypsa + about: Please ask and answer code-related questions here. diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index e9fedd36a..c2be39092 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -19,7 +19,6 @@ on: - cron: "0 5 * * TUE" env: - CONDA_CACHE_NUMBER: 1 # Change this value to manually reset the environment cache DATA_CACHE_NUMBER: 2 jobs: @@ -27,22 +26,12 @@ jobs: strategy: fail-fast: false + max-parallel: 3 matrix: - include: - # Matrix required to handle caching with Mambaforge - - os: ubuntu-latest - label: ubuntu-latest - prefix: /usr/share/miniconda3/envs/pypsa-eur - - - os: macos-latest - label: macos-latest - prefix: /Users/runner/miniconda3/envs/pypsa-eur - - - os: windows-latest - label: windows-latest - prefix: C:\Miniconda3\envs\pypsa-eur - - name: ${{ matrix.label }} + os: + - ubuntu-latest + - macos-latest + - windows-latest runs-on: ${{ matrix.os }} @@ -60,24 +49,25 @@ jobs: - name: Add solver to environment run: | echo -e "- glpk\n- ipopt<3.13.3" >> envs/environment.yaml - if: ${{ matrix.label }} == 'windows-latest' + if: ${{ matrix.os }} == 'windows-latest' - name: Add solver to environment run: | echo -e "- glpk\n- ipopt" >> envs/environment.yaml - if: ${{ matrix.label }} != 'windows-latest' + if: ${{ matrix.os }} != 'windows-latest' - - name: Setup Mambaforge - uses: conda-incubator/setup-miniconda@v2 + - name: Setup micromamba + uses: mamba-org/setup-micromamba@v1 with: - miniforge-variant: Mambaforge - miniforge-version: latest - activate-environment: pypsa-eur - use-mamba: true + micromamba-version: latest + environment-file: envs/environment.yaml + log-level: debug + init-shell: bash + cache-environment: true + cache-downloads: true - name: Set cache dates run: | - echo "DATE=$(date +'%Y%m%d')" >> $GITHUB_ENV echo "WEEK=$(date +'%Y%U')" >> $GITHUB_ENV - name: Cache data and cutouts folders @@ -88,24 +78,11 @@ jobs: cutouts key: data-cutouts-${{ env.WEEK }}-${{ env.DATA_CACHE_NUMBER }} - - name: Create environment cache - uses: actions/cache@v3 - id: cache - with: - path: ${{ matrix.prefix }} - key: ${{ matrix.label }}-conda-${{ env.DATE }}-${{ env.CONDA_CACHE_NUMBER }} - - - name: Update environment due to outdated or unavailable cache - run: mamba env update -n pypsa-eur -f envs/environment.yaml - if: steps.cache.outputs.cache-hit != 'true' - - name: Test snakemake workflow run: | - conda activate pypsa-eur - conda list - snakemake -call solve_elec_networks --configfile test/config.electricity.yaml --rerun-triggers=mtime - snakemake -call all --configfile test/config.overnight.yaml --rerun-triggers=mtime - snakemake -call all --configfile test/config.myopic.yaml --rerun-triggers=mtime + snakemake -call solve_elec_networks --configfile config/test/config.electricity.yaml --rerun-triggers=mtime + snakemake -call all --configfile config/test/config.overnight.yaml --rerun-triggers=mtime + snakemake -call all --configfile config/test/config.myopic.yaml --rerun-triggers=mtime - name: Upload artifacts uses: actions/upload-artifact@v3 diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index aa2953222..006673b94 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -30,7 +30,7 @@ repos: # Find common spelling mistakes in comments and docstrings - repo: https://github.com/codespell-project/codespell - rev: v2.2.4 + rev: v2.2.5 hooks: - id: codespell args: ['--ignore-regex="(\b[A-Z]+\b)"', '--ignore-words-list=fom,appartment,bage,ore,setis,tabacco,berfore'] # Ignore capital case words, e.g. country codes @@ -39,7 +39,7 @@ repos: # Make docstrings PEP 257 compliant - repo: https://github.com/PyCQA/docformatter - rev: v1.5.1 + rev: v1.7.5 hooks: - id: docformatter args: ["--in-place", "--make-summary-multi-line", "--pre-summary-newline"] @@ -51,7 +51,7 @@ repos: # Formatting with "black" coding style - repo: https://github.com/psf/black - rev: 23.1.0 + rev: 23.7.0 hooks: # Format Python files - id: black @@ -67,14 +67,14 @@ repos: # Do YAML formatting (before the linter checks it for misses) - repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks - rev: v2.7.0 + rev: v2.10.0 hooks: - id: pretty-format-yaml args: [--autofix, --indent, "2", --preserve-quotes] # Format Snakemake rule / workflow files - repo: https://github.com/snakemake/snakefmt - rev: v0.8.2 + rev: v0.8.4 hooks: - id: snakefmt @@ -87,6 +87,6 @@ repos: # Check for FSFE REUSE compliance (licensing) - repo: https://github.com/fsfe/reuse-tool - rev: v1.1.2 + rev: v2.1.0 hooks: - id: reuse diff --git a/.readthedocs.yml b/.readthedocs.yml index 3d7a86b2a..900dba1eb 100644 --- a/.readthedocs.yml +++ b/.readthedocs.yml @@ -4,8 +4,14 @@ version: 2 +build: + os: ubuntu-22.04 + tools: + python: "3.11" + apt_packages: + - graphviz + python: - version: 3.8 install: - requirements: doc/requirements.txt - system_packages: true + system_packages: false diff --git a/.syncignore-receive b/.syncignore-receive index a216e0d85..d2e9b76d5 100644 --- a/.syncignore-receive +++ b/.syncignore-receive @@ -18,3 +18,4 @@ cutouts data benchmarks *.nc +configs diff --git a/CITATION.cff b/CITATION.cff index 712a02f35..c80b73ef0 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -6,7 +6,7 @@ cff-version: 1.1.0 message: "If you use this package, please cite it in the following way." title: "PyPSA-Eur: An open sector-coupled optimisation model of the European energy system" repository: https://github.com/pypsa/pypsa-eur -version: 0.8.0 +version: 0.8.1 license: MIT authors: - family-names: Brown diff --git a/README.md b/README.md index 2973fa330..9691abc48 100644 --- a/README.md +++ b/README.md @@ -9,8 +9,9 @@ SPDX-License-Identifier: CC-BY-4.0 ![Size](https://img.shields.io/github/repo-size/pypsa/pypsa-eur) [![Zenodo PyPSA-Eur](https://zenodo.org/badge/DOI/10.5281/zenodo.3520874.svg)](https://doi.org/10.5281/zenodo.3520874) [![Zenodo PyPSA-Eur-Sec](https://zenodo.org/badge/DOI/10.5281/zenodo.3938042.svg)](https://doi.org/10.5281/zenodo.3938042) -[![Snakemake](https://img.shields.io/badge/snakemake-≥5.0.0-brightgreen.svg?style=flat)](https://snakemake.readthedocs.io) +[![Snakemake](https://img.shields.io/badge/snakemake-≥7.7.0-brightgreen.svg?style=flat)](https://snakemake.readthedocs.io) [![REUSE status](https://api.reuse.software/badge/github.com/pypsa/pypsa-eur)](https://api.reuse.software/info/github.com/pypsa/pypsa-eur) +[![Stack Exchange questions](https://img.shields.io/stackexchange/stackoverflow/t/pypsa)](https://stackoverflow.com/questions/tagged/pypsa) # PyPSA-Eur: A Sector-Coupled Open Optimisation Model of the European Energy System @@ -34,17 +35,18 @@ The model is designed to be imported into the open toolbox [PyPSA](https://github.com/PyPSA/PyPSA). **WARNING**: PyPSA-Eur is under active development and has several -[limitations](https://pypsa-eur.readthedocs.io/en/latest/limitations.html) -which you should understand before using the model. The github repository +[limitations](https://pypsa-eur.readthedocs.io/en/latest/limitations.html) which +you should understand before using the model. The github repository [issues](https://github.com/PyPSA/pypsa-eur/issues) collect known topics we are working on (please feel free to help or make suggestions). The [documentation](https://pypsa-eur.readthedocs.io/) remains somewhat patchy. You -can find showcases of the model's capabilities in the preprint [Benefits of a -Hydrogen Network in Europe](https://arxiv.org/abs/2207.05816), a [paper in Joule -with a description of the industry sector](https://arxiv.org/abs/2109.09563), or -in [a 2021 presentation at EMP-E](https://nworbmot.org/energy/brown-empe.pdf). -We cannot support this model if you choose to use it. We do not recommend to use -the full resolution network model for simulations. At high granularity the +can find showcases of the model's capabilities in the Joule paper [The potential +role of a hydrogen network in +Europe](https://doi.org/10.1016/j.joule.2023.06.016), another [paper in Joule +with a description of the industry +sector](https://doi.org/10.1016/j.joule.2022.04.016), or in [a 2021 presentation +at EMP-E](https://nworbmot.org/energy/brown-empe.pdf). We do not recommend to +use the full resolution network model for simulations. At high granularity the assignment of loads and generators to the nearest network node may not be a correct assumption, depending on the topology of the underlying distribution grid, and local grid bottlenecks may cause unrealistic load-shedding or @@ -90,6 +92,14 @@ to 50-200 nodes. Already-built versions of the model can be found in the accompanying [Zenodo repository](https://doi.org/10.5281/zenodo.3601881). + +# Contributing and Support +We strongly welcome anyone interested in contributing to this project. If you have any ideas, suggestions or encounter problems, feel invited to file issues or make pull requests on GitHub. +- In case of code-related **questions**, please post on [stack overflow](https://stackoverflow.com/questions/tagged/pypsa). +- For non-programming related and more general questions please refer to the [mailing list](https://groups.google.com/group/pypsa). +- To **discuss** with other PyPSA users, organise projects, share news, and get in touch with the community you can use the [discord server](https://discord.com/invite/AnuJBk23FU). +- For **bugs and feature requests**, please use the [PyPSA-Eur Github Issues page](https://github.com/PyPSA/pypsa-eur/issues). + # Licence The code in PyPSA-Eur is released as free software under the diff --git a/Snakefile b/Snakefile index 621e4e9da..27ed4dfb9 100644 --- a/Snakefile +++ b/Snakefile @@ -14,11 +14,11 @@ from snakemake.utils import min_version min_version("7.7") -if not exists("config.yaml"): - copyfile("config.default.yaml", "config.yaml") +if not exists("config/config.yaml"): + copyfile("config/config.default.yaml", "config/config.yaml") -configfile: "config.yaml" +configfile: "config/config.yaml" COSTS = f"data/costs_{config['costs']['year']}.csv" diff --git a/config.default.yaml b/config/config.default.yaml old mode 100755 new mode 100644 similarity index 53% rename from config.default.yaml rename to config/config.default.yaml index 1a8a8a9f8..aa9523177 --- a/config.default.yaml +++ b/config/config.default.yaml @@ -2,71 +2,59 @@ # # SPDX-License-Identifier: CC0-1.0 -version: 0.8.0 +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#top-level-configuration +version: 0.8.1 tutorial: false logging: level: INFO format: '%(levelname)s:%(name)s:%(message)s' +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#run run: - name: "" # use this to keep track of runs with different settings - disable_progressbar: false # set to true to disable the progressbar - shared_resources: false # set to true to share the default resources across runs - shared_cutouts: true # set to true to share the default cutout(s) across runs + name: "" + disable_progressbar: false + shared_resources: false + shared_cutouts: true -foresight: overnight # options are overnight, myopic, perfect (perfect is not yet implemented) -# if you use myopic or perfect foresight, set the investment years in "planning_horizons" below +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#foresight +foresight: overnight +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#scenario +# Wildcard docs in https://pypsa-eur.readthedocs.io/en/latest/wildcards.html scenario: simpl: - '' - ll: # allowed transmission line volume expansion, can be any float >= 1.0 with a prefix v|c (today) or "copt" - - v1.0 + ll: - v1.5 - clusters: # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred + clusters: - 37 - 128 - 256 - 512 - 1024 - opts: # only relevant for PyPSA-Eur + opts: - '' - sector_opts: # this is where the main scenario settings are + sector_opts: - Co2L0-3H-T-H-B-I-A-solar+p3-dist1 - # to really understand the options here, look in scripts/prepare_sector_network.py - # Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%); - # Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions - # xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours - # single letters are sectors: T for land transport, H for building heating, - # B for biomass supply, I for industry, shipping and aviation, - # A for agriculture, forestry and fishing - # solar+c0.5 reduces the capital cost of solar to 50\% of reference value - # solar+p3 multiplies the available installable potential by factor 3 - # seq400 sets the potential of CO2 sequestration to 400 Mt CO2 per year - # dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv - # for myopic/perfect foresight cb states the carbon budget in GtCO2 (cumulative - # emissions throughout the transition path in the timeframe determined by the - # planning_horizons), be:beta decay; ex:exponential decay - # cb40ex0 distributes a carbon budget of 40 GtCO2 following an exponential - # decay with initial growth rate 0 - planning_horizons: # investment years for myopic and perfect; for overnight, year of cost assumptions can be different and is defined under 'costs' - - 2050 - # for example, set to + planning_horizons: # - 2020 # - 2030 # - 2040 - # - 2050 - # for myopic foresight + - 2050 +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#countries countries: ['AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK'] +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#snapshots snapshots: start: "2013-01-01" end: "2014-01-01" - inclusive: 'left' # include start, not end + inclusive: 'left' +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#enable enable: + retrieve: auto prepare_links_p_nom: false retrieve_databundle: true retrieve_sector_databundle: true @@ -77,9 +65,7 @@ enable: retrieve_natura_raster: true custom_busmap: false -# CO2 budget as a fraction of 1990 emissions -# this is over-ridden if CO2Lx is set in sector_opts -# this is also over-ridden if cb is set in sector_opts +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#co2-budget co2_budget: 2020: 0.701 2025: 0.524 @@ -89,18 +75,19 @@ co2_budget: 2045: 0.032 2050: 0.000 +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#electricity electricity: voltages: [220., 300., 380.] - gaslimit: false # global gas usage limit of X MWh_th - co2limit: 7.75e+7 # 0.05 * 3.1e9*0.5 + gaslimit: false + co2limit: 7.75e+7 co2base: 1.487e+9 agg_p_nom_limits: data/agg_p_nom_minmax.csv - operational_reserve: # like https://genxproject.github.io/GenX/dev/core/#Reserves + operational_reserve: activate: false - epsilon_load: 0.02 # share of total load - epsilon_vres: 0.02 # share of total renewable supply - contingency: 4000 # fixed capacity in MW + epsilon_load: 0.02 + epsilon_vres: 0.02 + contingency: 4000 max_hours: battery: 6 @@ -112,9 +99,7 @@ electricity: Store: [battery, H2] Link: [] # H2 pipeline - # use pandas query strings here, e.g. Country not in ['Germany'] powerplants_filter: (DateOut >= 2022 or DateOut != DateOut) - # use pandas query strings here, e.g. Country in ['Germany'] custom_powerplants: false conventional_carriers: [nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass] @@ -122,25 +107,19 @@ electricity: estimate_renewable_capacities: enable: true - # Add capacities from OPSD data from_opsd: true - # Renewable capacities are based on existing capacities reported by IRENA year: 2020 - # Artificially limit maximum capacities to factor * (IRENA capacities), - # i.e. 110% of 's capacities => expansion_limit: 1.1 - # false: Use estimated renewable potentials determine by the workflow expansion_limit: false technology_mapping: - # Wind is the Fueltype in powerplantmatching, onwind, offwind-{ac,dc} the carrier in PyPSA-Eur Offshore: [offwind-ac, offwind-dc] Onshore: [onwind] PV: [solar] - +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#atlite atlite: default_cutout: europe-2013-era5 nprocesses: 4 - show_progress: false # false saves time + show_progress: false cutouts: # use 'base' to determine geographical bounds and time span from config # base: @@ -163,20 +142,16 @@ atlite: sarah_dir: features: [influx, temperature] - +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#renewable renewable: onwind: cutout: europe-2013-era5 resource: method: wind turbine: Vestas_V112_3MW - capacity_per_sqkm: 3 # ScholzPhd Tab 4.3.1: 10MW/km^2 and assuming 30% fraction of the already restricted - # area is available for installation of wind generators due to competing land use and likely public - # acceptance issues. + capacity_per_sqkm: 3 # correction_factor: 0.93 corine: - # Scholz, Y. (2012). Renewable energy based electricity supply at low costs - # development of the REMix model and application for Europe. ( p.42 / p.28) grid_codes: [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32] distance: 1000 distance_grid_codes: [1, 2, 3, 4, 5, 6] @@ -189,13 +164,8 @@ renewable: resource: method: wind turbine: NREL_ReferenceTurbine_5MW_offshore - capacity_per_sqkm: 2 # ScholzPhd Tab 4.3.1: 10MW/km^2 and assuming 20% fraction of the already restricted - # area is available for installation of wind generators due to competing land use and likely public - # acceptance issues. + capacity_per_sqkm: 2 correction_factor: 0.8855 - # proxy for wake losses - # from 10.1016/j.energy.2018.08.153 - # until done more rigorously in #153 corine: [44, 255] natura: true ship_threshold: 400 @@ -209,13 +179,8 @@ renewable: resource: method: wind turbine: NREL_ReferenceTurbine_5MW_offshore - capacity_per_sqkm: 2 # ScholzPhd Tab 4.3.1: 10MW/km^2 and assuming 20% fraction of the already restricted - # area is available for installation of wind generators due to competing land use and likely public - # acceptance issues. + capacity_per_sqkm: 2 correction_factor: 0.8855 - # proxy for wake losses - # from 10.1016/j.energy.2018.08.153 - # until done more rigorously in #153 corine: [44, 255] natura: true ship_threshold: 400 @@ -232,14 +197,7 @@ renewable: orientation: slope: 35. azimuth: 180. - capacity_per_sqkm: 1.7 # ScholzPhd Tab 4.3.1: 170 MW/km^2 and assuming 1% of the area can be used for solar PV panels - # Correction factor determined by comparing uncorrected area-weighted full-load hours to those - # published in Supplementary Data to - # Pietzcker, Robert Carl, et al. "Using the sun to decarbonize the power - # sector -- The economic potential of photovoltaics and concentrating solar - # power." Applied Energy 135 (2014): 704-720. - # This correction factor of 0.854337 may be in order if using reanalysis data. - # for discussion refer to https://github.com/PyPSA/pypsa-eur/pull/304 + capacity_per_sqkm: 1.7 # correction_factor: 0.854337 corine: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 26, 31, 32] natura: true @@ -253,10 +211,12 @@ renewable: hydro_max_hours: "energy_capacity_totals_by_country" # one of energy_capacity_totals_by_country, estimate_by_large_installations or a float clip_min_inflow: 1.0 +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#conventional conventional: nuclear: p_max_pu: "data/nuclear_p_max_pu.csv" # float of file name +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#lines lines: types: 220.: "Al/St 240/40 2-bundle 220.0" @@ -264,27 +224,40 @@ lines: 380.: "Al/St 240/40 4-bundle 380.0" s_max_pu: 0.7 s_nom_max: .inf + max_extension: .inf length_factor: 1.25 under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity + dynamic_line_rating: + activate: false + cutout: europe-2013-era5 + correction_factor: 0.95 + max_voltage_difference: false + max_line_rating: false +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#links links: p_max_pu: 1.0 p_nom_max: .inf + max_extension: .inf include_tyndp: true under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#transformers transformers: x: 0.1 s_nom: 2000. type: '' +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#load load: - power_statistics: true # only for files from <2019; set false in order to get ENTSOE transparency data - interpolate_limit: 3 # data gaps up until this size are interpolated linearly - time_shift_for_large_gaps: 1w # data gaps up until this size are copied by copying from + power_statistics: true + interpolate_limit: 3 + time_shift_for_large_gaps: 1w manual_adjustments: true # false scaling_factor: 1.0 +# docs +# TODO: PyPSA-Eur merge issue in prepare_sector_network.py # regulate what components with which carriers are kept from PyPSA-Eur; # some technologies are removed because they are implemented differently # (e.g. battery or H2 storage) or have different year-dependent costs @@ -305,12 +278,14 @@ pypsa_eur: - hydro Store: [] +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#energy energy: energy_totals_year: 2011 base_emissions_year: 1990 eurostat_report_year: 2016 - emissions: CO2 # "CO2" or "All greenhouse gases - (CO2 equivalent)" + emissions: CO2 +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#biomass biomass: year: 2030 scenario: ENS_Med @@ -336,14 +311,14 @@ biomass: - Manure solid, liquid - Sludge - +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#solar-thermal solar_thermal: clearsky_model: simple # should be "simple" or "enhanced"? orientation: slope: 45. azimuth: 180. -# only relevant for foresight = myopic or perfect +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#existing-capacities existing_capacities: grouping_years_power: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, 2025, 2030] grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019] # these should not extend 2020 @@ -354,37 +329,34 @@ existing_capacities: - oil - uranium - +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#sector sector: district_heating: - potential: 0.6 # maximum fraction of urban demand which can be supplied by district heating - # increase of today's district heating demand to potential maximum district heating share - # progress = 0 means today's district heating share, progress = 1 means maximum fraction of urban demand is supplied by district heating + potential: 0.6 progress: 2020: 0.0 2030: 0.3 2040: 0.6 2050: 1.0 district_heating_loss: 0.15 - cluster_heat_buses: false # cluster residential and service heat buses to one to save memory - bev_dsm_restriction_value: 0.75 #Set to 0 for no restriction on BEV DSM - bev_dsm_restriction_time: 7 #Time at which SOC of BEV has to be dsm_restriction_value + cluster_heat_buses: false + bev_dsm_restriction_value: 0.75 + bev_dsm_restriction_time: 7 transport_heating_deadband_upper: 20. transport_heating_deadband_lower: 15. - ICE_lower_degree_factor: 0.375 #in per cent increase in fuel consumption per degree above deadband + ICE_lower_degree_factor: 0.375 ICE_upper_degree_factor: 1.6 EV_lower_degree_factor: 0.98 EV_upper_degree_factor: 0.63 - bev_dsm: true #turns on EV battery - bev_availability: 0.5 #How many cars do smart charging - bev_energy: 0.05 #average battery size in MWh - bev_charge_efficiency: 0.9 #BEV (dis-)charging efficiency - bev_plug_to_wheel_efficiency: 0.2 #kWh/km from EPA https://www.fueleconomy.gov/feg/ for Tesla Model S - bev_charge_rate: 0.011 #3-phase charger with 11 kW + bev_dsm: true + bev_availability: 0.5 + bev_energy: 0.05 + bev_charge_efficiency: 0.9 + bev_plug_to_wheel_efficiency: 0.2 + bev_charge_rate: 0.011 bev_avail_max: 0.95 bev_avail_mean: 0.8 - v2g: true #allows feed-in to grid from EV battery - #what is not EV or FCEV is oil-fuelled ICE + v2g: true land_transport_fuel_cell_share: 2020: 0 2030: 0.05 @@ -404,12 +376,12 @@ sector: transport_internal_combustion_efficiency: 0.3 agriculture_machinery_electric_share: 0 agriculture_machinery_oil_share: 1 - agriculture_machinery_fuel_efficiency: 0.7 # fuel oil per use - agriculture_machinery_electric_efficiency: 0.3 # electricity per use - MWh_MeOH_per_MWh_H2: 0.8787 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64. - MWh_MeOH_per_tCO2: 4.0321 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64. - MWh_MeOH_per_MWh_e: 3.6907 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64. - shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands + agriculture_machinery_fuel_efficiency: 0.7 + agriculture_machinery_electric_efficiency: 0.3 + MWh_MeOH_per_MWh_H2: 0.8787 + MWh_MeOH_per_tCO2: 4.0321 + MWh_MeOH_per_MWh_e: 3.6907 + shipping_hydrogen_liquefaction: false shipping_hydrogen_share: 2020: 0 2030: 0 @@ -425,18 +397,14 @@ sector: 2030: 0.7 2040: 0.3 2050: 0 - shipping_methanol_efficiency: 0.46 # 10-15% higher https://www.iea-amf.org/app/webroot/files/file/Annex%20Reports/AMF_Annex_56.pdf, https://users.ugent.be/~lsileghe/documents/extended_abstract.pdf - shipping_oil_efficiency: 0.40 #For conversion of fuel oil to propulsion in 2011 - aviation_demand_factor: 1. # relative aviation demand compared to today - HVC_demand_factor: 1. # relative HVC demand compared to today - time_dep_hp_cop: true #time dependent heat pump coefficient of performance - heat_pump_sink_T: 55. # Celsius, based on DTU / large area radiators; used in build_cop_profiles.py - # conservatively high to cover hot water and space heating in poorly-insulated buildings - reduce_space_heat_exogenously: true # reduces space heat demand by a given factor (applied before losses in DH) - # this can represent e.g. building renovation, building demolition, or if - # the factor is negative: increasing floor area, increased thermal comfort, population growth - reduce_space_heat_exogenously_factor: # per unit reduction in space heat demand - # the default factors are determined by the LTS scenario from http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221 + shipping_methanol_efficiency: 0.46 + shipping_oil_efficiency: 0.40 + aviation_demand_factor: 1. + HVC_demand_factor: 1. + time_dep_hp_cop: true + heat_pump_sink_T: 55. + reduce_space_heat_exogenously: true + reduce_space_heat_exogenously_factor: 2020: 0.10 # this results in a space heat demand reduction of 10% 2025: 0.09 # first heat demand increases compared to 2020 because of larger floor area per capita 2030: 0.09 @@ -444,15 +412,15 @@ sector: 2040: 0.16 2045: 0.21 2050: 0.29 - retrofitting: # co-optimises building renovation to reduce space heat demand - retro_endogen: false # co-optimise space heat savings - cost_factor: 1.0 # weight costs for building renovation - interest_rate: 0.04 # for investment in building components - annualise_cost: true # annualise the investment costs - tax_weighting: false # weight costs depending on taxes in countries - construction_index: true # weight costs depending on labour/material costs per country + retrofitting: + retro_endogen: false + cost_factor: 1.0 + interest_rate: 0.04 + annualise_cost: true + tax_weighting: false + construction_index: true tes: true - tes_tau: # 180 day time constant for centralised, 3 day for decentralised + tes_tau: decentral: 3 central: 180 boilers: true @@ -464,57 +432,57 @@ sector: solar_cf_correction: 0.788457 # = >>> 1/1.2683 marginal_cost_storage: 0. #1e-4 methanation: true - helmeth: true + helmeth: false coal_cc: false dac: true co2_vent: false allam_cycle: false + hydrogen_fuel_cell: true + hydrogen_turbine: false SMR: true regional_co2_sequestration_potential: - enable: false # enable regionally resolved geological co2 storage potential + enable: false attribute: 'conservative estimate Mt' - include_onshore: false # include onshore sequestration potentials - min_size: 3 # Gt, sites with lower potential will be excluded - max_size: 25 # Gt, max sequestration potential for any one site, TODO research suitable value - years_of_storage: 25 # years until potential exhausted at optimised annual rate - co2_sequestration_potential: 200 #MtCO2/a sequestration potential for Europe - co2_sequestration_cost: 10 #EUR/tCO2 for sequestration of CO2 + include_onshore: false + min_size: 3 + max_size: 25 + years_of_storage: 25 + co2_sequestration_potential: 200 + co2_sequestration_cost: 10 co2_spatial: false co2network: false - cc_fraction: 0.9 # default fraction of CO2 captured with post-combustion capture + cc_fraction: 0.9 hydrogen_underground_storage: true hydrogen_underground_storage_locations: # - onshore # more than 50 km from sea - nearshore # within 50 km of sea # - offshore - ammonia: false # can be false (no NH3 carrier), true (copperplated NH3), "regional" (regionalised NH3 without network) - min_part_load_fischer_tropsch: 0.9 # p_min_pu - min_part_load_methanolisation: 0.5 # p_min_pu + ammonia: false + min_part_load_fischer_tropsch: 0.9 + min_part_load_methanolisation: 0.5 use_fischer_tropsch_waste_heat: true use_fuel_cell_waste_heat: true use_electrolysis_waste_heat: false electricity_distribution_grid: true - electricity_distribution_grid_cost_factor: 1.0 #multiplies cost in data/costs.csv - electricity_grid_connection: true # only applies to onshore wind and utility PV + electricity_distribution_grid_cost_factor: 1.0 + electricity_grid_connection: true H2_network: true gas_network: false - H2_retrofit: false # if set to True existing gas pipes can be retrofitted to H2 pipes - # according to hydrogen backbone strategy (April, 2020) p.15 - # https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf - # 60% of original natural gas capacity could be used in cost-optimal case as H2 capacity - H2_retrofit_capacity_per_CH4: 0.6 # ratio for H2 capacity per original CH4 capacity of retrofitted pipelines - gas_network_connectivity_upgrade: 1 # https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation + H2_retrofit: false + H2_retrofit_capacity_per_CH4: 0.6 + gas_network_connectivity_upgrade: 1 gas_distribution_grid: true - gas_distribution_grid_cost_factor: 1.0 #multiplies cost in data/costs.csv - biomass_spatial: false # regionally resolve biomass (e.g. potentials) - biomass_transport: false # allow transport of solid biomass between nodes - conventional_generation: # generator : carrier + gas_distribution_grid_cost_factor: 1.0 + biomass_spatial: false + biomass_transport: false + conventional_generation: OCGT: gas biomass_to_liquid: false biosng: false +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#industry industry: - St_primary_fraction: # fraction of steel produced via primary route versus secondary route (scrap+EAF); today fraction is 0.6 + St_primary_fraction: 2020: 0.6 2025: 0.55 2030: 0.5 @@ -522,7 +490,7 @@ industry: 2040: 0.4 2045: 0.35 2050: 0.3 - DRI_fraction: # fraction of the primary route converted to DRI + EAF + DRI_fraction: 2020: 0 2025: 0 2030: 0.05 @@ -530,9 +498,9 @@ industry: 2040: 0.4 2045: 0.7 2050: 1 - H2_DRI: 1.7 #H2 consumption in Direct Reduced Iron (DRI), MWh_H2,LHV/ton_Steel from 51kgH2/tSt in Vogl et al (2018) doi:10.1016/j.jclepro.2018.08.279 - elec_DRI: 0.322 #electricity consumption in Direct Reduced Iron (DRI) shaft, MWh/tSt HYBRIT brochure https://ssabwebsitecdn.azureedge.net/-/media/hybrit/files/hybrit_brochure.pdf - Al_primary_fraction: # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4 + H2_DRI: 1.7 + elec_DRI: 0.322 + Al_primary_fraction: 2020: 0.4 2025: 0.375 2030: 0.35 @@ -540,35 +508,33 @@ industry: 2040: 0.3 2045: 0.25 2050: 0.2 - MWh_NH3_per_tNH3: 5.166 # LHV - MWh_CH4_per_tNH3_SMR: 10.8 # 2012's demand from https://ec.europa.eu/docsroom/documents/4165/attachments/1/translations/en/renditions/pdf - MWh_elec_per_tNH3_SMR: 0.7 # same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3 - MWh_H2_per_tNH3_electrolysis: 6.5 # from https://doi.org/10.1016/j.joule.2018.04.017, around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy) - MWh_elec_per_tNH3_electrolysis: 1.17 # from https://doi.org/10.1016/j.joule.2018.04.017 Table 13 (air separation and HB) + MWh_NH3_per_tNH3: 5.166 + MWh_CH4_per_tNH3_SMR: 10.8 + MWh_elec_per_tNH3_SMR: 0.7 + MWh_H2_per_tNH3_electrolysis: 6.5 + MWh_elec_per_tNH3_electrolysis: 1.17 MWh_NH3_per_MWh_H2_cracker: 1.46 # https://github.com/euronion/trace/blob/44a5ff8401762edbef80eff9cfe5a47c8d3c8be4/data/efficiencies.csv - NH3_process_emissions: 24.5 # in MtCO2/a from SMR for H2 production for NH3 from UNFCCC for 2015 for EU28 - petrochemical_process_emissions: 25.5 # in MtCO2/a for petrochemical and other from UNFCCC for 2015 for EU28 - HVC_primary_fraction: 1. # fraction of today's HVC produced via primary route - HVC_mechanical_recycling_fraction: 0. # fraction of today's HVC produced via mechanical recycling - HVC_chemical_recycling_fraction: 0. # fraction of today's HVC produced via chemical recycling - HVC_production_today: 52. # MtHVC/a from DECHEMA (2017), Figure 16, page 107; includes ethylene, propylene and BTX - MWh_elec_per_tHVC_mechanical_recycling: 0.547 # from SI of https://doi.org/10.1016/j.resconrec.2020.105010, Table S5, for HDPE, PP, PS, PET. LDPE would be 0.756. - MWh_elec_per_tHVC_chemical_recycling: 6.9 # Material Economics (2019), page 125; based on pyrolysis and electric steam cracking - chlorine_production_today: 9.58 # MtCl/a from DECHEMA (2017), Table 7, page 43 - MWh_elec_per_tCl: 3.6 # DECHEMA (2017), Table 6, page 43 - MWh_H2_per_tCl: -0.9372 # DECHEMA (2017), page 43; negative since hydrogen produced in chloralkali process - methanol_production_today: 1.5 # MtMeOH/a from DECHEMA (2017), page 62 - MWh_elec_per_tMeOH: 0.167 # DECHEMA (2017), Table 14, page 65 - MWh_CH4_per_tMeOH: 10.25 # DECHEMA (2017), Table 14, page 65 + NH3_process_emissions: 24.5 + petrochemical_process_emissions: 25.5 + HVC_primary_fraction: 1. + HVC_mechanical_recycling_fraction: 0. + HVC_chemical_recycling_fraction: 0. + HVC_production_today: 52. + MWh_elec_per_tHVC_mechanical_recycling: 0.547 + MWh_elec_per_tHVC_chemical_recycling: 6.9 + chlorine_production_today: 9.58 + MWh_elec_per_tCl: 3.6 + MWh_H2_per_tCl: -0.9372 + methanol_production_today: 1.5 + MWh_elec_per_tMeOH: 0.167 + MWh_CH4_per_tMeOH: 10.25 hotmaps_locate_missing: false reference_year: 2015 - # references: - # DECHEMA (2017): https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf - # Material Economics (2019): https://materialeconomics.com/latest-updates/industrial-transformation-2050 +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#costs costs: year: 2030 - version: v0.5.0 + version: v0.6.0 rooftop_share: 0.14 # based on the potentials, assuming (0.1 kW/m2 and 10 m2/person) fill_values: FOM: 0 @@ -592,14 +558,15 @@ costs: fuel cell: 0. battery: 0. battery inverter: 0. - emission_prices: # in currency per tonne emission, only used with the option Ep + emission_prices: co2: 0. +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#clustering clustering: simplify_network: - to_substations: false # network is simplified to nodes with positive or negative power injection (i.e. substations or offwind connections) + to_substations: false algorithm: kmeans # choose from: [hac, kmeans] - feature: solar+onwind-time # only for hac. choose from: [solar+onwind-time, solar+onwind-cap, solar-time, solar-cap, solar+offwind-cap] etc. + feature: solar+onwind-time exclude_carriers: [] remove_stubs: true remove_stubs_across_borders: true @@ -609,7 +576,7 @@ clustering: exclude_carriers: [] aggregation_strategies: generators: - p_nom_max: sum # use "min" for more conservative assumptions + p_nom_max: sum p_nom_min: sum p_min_pu: mean marginal_cost: mean @@ -618,12 +585,13 @@ clustering: ramp_limit_down: max efficiency: mean +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#solving solving: #tmpdir: "path/to/tmp" options: - formulation: kirchhoff clip_p_max_pu: 1.e-2 load_shedding: false + transmission_losses: 0 noisy_costs: true skip_iterations: true track_iterations: false @@ -684,14 +652,14 @@ solving: threads: 4 lpmethod: 4 # barrier solutiontype: 2 # non basic solution, ie no crossover - barrier_convergetol: 1.e-5 - feasopt_tolerance: 1.e-6 + barrier.convergetol: 1.e-5 + feasopt.tolerance: 1.e-6 cbc-default: {} # Used in CI glpk-default: {} # Used in CI mem: 30000 #memory in MB; 20 GB enough for 50+B+I+H2; 100 GB for 181+B+I+H2 - +# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#plotting plotting: map: boundaries: [-11, 30, 34, 71] @@ -706,48 +674,6 @@ plotting: energy_max: 20000 energy_min: -20000 energy_threshold: 50. - vre_techs: - - onwind - - offwind-ac - - offwind-dc - - solar - - ror - renewable_storage_techs: - - PHS - - hydro - conv_techs: - - OCGT - - CCGT - - Nuclear - - Coal - storage_techs: - - hydro+PHS - - battery - - H2 - load_carriers: - - AC load - AC_carriers: - - AC line - - AC transformer - link_carriers: - - DC line - - Converter AC-DC - heat_links: - - heat pump - - resistive heater - - CHP heat - - CHP electric - - gas boiler - - central heat pump - - central resistive heater - - central CHP heat - - central CHP electric - - central gas boiler - heat_generators: - - gas boiler - - central gas boiler - - solar thermal collector - - central solar thermal collector nice_names: OCGT: "Open-Cycle Gas" @@ -788,6 +714,11 @@ plotting: solar: "#f9d002" solar PV: "#f9d002" solar thermal: '#ffbf2b' + residential rural solar thermal: '#f1c069' + services rural solar thermal: '#eabf61' + residential urban decentral solar thermal: '#e5bc5a' + services urban decentral solar thermal: '#dfb953' + urban central solar thermal: '#d7b24c' solar rooftop: '#ffea80' # gas OCGT: '#e0986c' @@ -796,9 +727,15 @@ plotting: gas boiler: '#db6a25' gas boilers: '#db6a25' gas boiler marginal: '#db6a25' + residential rural gas boiler: '#d4722e' + residential urban decentral gas boiler: '#cb7a36' + services rural gas boiler: '#c4813f' + services urban decentral gas boiler: '#ba8947' + urban central gas boiler: '#b0904f' gas: '#e05b09' fossil gas: '#e05b09' natural gas: '#e05b09' + biogas to gas: '#e36311' CCGT: '#a85522' CCGT marginal: '#a85522' allam: '#B98F76' @@ -811,6 +748,11 @@ plotting: # oil oil: '#c9c9c9' oil boiler: '#adadad' + residential rural oil boiler: '#a9a9a9' + services rural oil boiler: '#a5a5a5' + residential urban decentral oil boiler: '#a1a1a1' + urban central oil boiler: '#9d9d9d' + services urban decentral oil boiler: '#999999' agriculture machinery oil: '#949494' shipping oil: "#808080" land transport oil: '#afafaf' @@ -836,13 +778,20 @@ plotting: solid biomass for industry CC: '#47411c' solid biomass for industry co2 from atmosphere: '#736412' solid biomass for industry co2 to stored: '#47411c' + urban central solid biomass CHP: '#9d9042' + urban central solid biomass CHP CC: '#6c5d28' biomass boiler: '#8A9A5B' + residential rural biomass boiler: '#a1a066' + residential urban decentral biomass boiler: '#b0b87b' + services rural biomass boiler: '#c6cf98' + services urban decentral biomass boiler: '#dde5b5' biomass to liquid: '#32CD32' BioSNG: '#123456' # power transmission lines: '#6c9459' transmission lines: '#6c9459' electricity distribution grid: '#97ad8c' + low voltage: '#97ad8c' # electricity demand Electric load: '#110d63' electric demand: '#110d63' @@ -853,24 +802,48 @@ plotting: # battery + EVs battery: '#ace37f' battery storage: '#ace37f' + battery charger: '#88a75b' + battery discharger: '#5d4e29' home battery: '#80c944' home battery storage: '#80c944' + home battery charger: '#5e8032' + home battery discharger: '#3c5221' BEV charger: '#baf238' V2G: '#e5ffa8' land transport EV: '#baf238' Li ion: '#baf238' # hot water storage water tanks: '#e69487' + residential rural water tanks: '#f7b7a3' + services rural water tanks: '#f3afa3' + residential urban decentral water tanks: '#f2b2a3' + services urban decentral water tanks: '#f1b4a4' + urban central water tanks: '#e9977d' hot water storage: '#e69487' - hot water charging: '#e69487' - hot water discharging: '#e69487' + hot water charging: '#e8998b' + urban central water tanks charger: '#b57a67' + residential rural water tanks charger: '#b4887c' + residential urban decentral water tanks charger: '#b39995' + services rural water tanks charger: '#b3abb0' + services urban decentral water tanks charger: '#b3becc' + hot water discharging: '#e99c8e' + urban central water tanks discharger: '#b9816e' + residential rural water tanks discharger: '#ba9685' + residential urban decentral water tanks discharger: '#baac9e' + services rural water tanks discharger: '#bbc2b8' + services urban decentral water tanks discharger: '#bdd8d3' # heat demand Heat load: '#cc1f1f' heat: '#cc1f1f' heat demand: '#cc1f1f' rural heat: '#ff5c5c' + residential rural heat: '#ff7c7c' + services rural heat: '#ff9c9c' central heat: '#cc1f1f' + urban central heat: '#d15959' decentral heat: '#750606' + residential urban decentral heat: '#a33c3c' + services urban decentral heat: '#cc1f1f' low-temperature heat for industry: '#8f2727' process heat: '#ff0000' agriculture heat: '#d9a5a5' @@ -878,14 +851,26 @@ plotting: heat pumps: '#2fb537' heat pump: '#2fb537' air heat pump: '#36eb41' + residential urban decentral air heat pump: '#48f74f' + services urban decentral air heat pump: '#5af95d' + urban central air heat pump: '#6cfb6b' ground heat pump: '#2fb537' + residential rural ground heat pump: '#48f74f' + services rural ground heat pump: '#5af95d' Ambient: '#98eb9d' CHP: '#8a5751' + urban central gas CHP: '#8d5e56' CHP CC: '#634643' + urban central gas CHP CC: '#6e4e4c' CHP heat: '#8a5751' CHP electric: '#8a5751' district heating: '#e8beac' resistive heater: '#d8f9b8' + residential rural resistive heater: '#bef5b5' + residential urban decentral resistive heater: '#b2f1a9' + services rural resistive heater: '#a5ed9d' + services urban decentral resistive heater: '#98e991' + urban central resistive heater: '#8cdf85' retrofitting: '#8487e8' building retrofitting: '#8487e8' # hydrogen @@ -897,12 +882,16 @@ plotting: SMR CC: '#4f1745' H2 liquefaction: '#d647bd' hydrogen storage: '#bf13a0' + H2 Store: '#bf13a0' H2 storage: '#bf13a0' land transport fuel cell: '#6b3161' H2 pipeline: '#f081dc' H2 pipeline retrofitted: '#ba99b5' H2 Fuel Cell: '#c251ae' + H2 fuel cell: '#c251ae' + H2 turbine: '#991f83' H2 Electrolysis: '#ff29d9' + H2 electrolysis: '#ff29d9' # ammonia NH3: '#46caf0' ammonia: '#46caf0' @@ -951,9 +940,11 @@ plotting: waste: '#e3d37d' other: '#000000' geothermal: '#ba91b1' + AC: "#70af1d" AC-AC: "#70af1d" AC line: "#70af1d" links: "#8a1caf" HVDC links: "#8a1caf" + DC: "#8a1caf" DC-DC: "#8a1caf" DC link: "#8a1caf" diff --git a/test/config.electricity.yaml b/config/test/config.electricity.yaml old mode 100755 new mode 100644 similarity index 92% rename from test/config.electricity.yaml rename to config/test/config.electricity.yaml index 6798e38cc..b750bf629 --- a/test/config.electricity.yaml +++ b/config/test/config.electricity.yaml @@ -60,6 +60,12 @@ renewable: clustering: exclude_carriers: ["OCGT", "offwind-ac", "coal"] +lines: + dynamic_line_rating: + activate: true + cutout: be-03-2013-era5 + max_line_rating: 1.3 + solving: solver: diff --git a/test/config.myopic.yaml b/config/test/config.myopic.yaml similarity index 90% rename from test/config.myopic.yaml rename to config/test/config.myopic.yaml index efa031366..0bb85ec6c 100644 --- a/test/config.myopic.yaml +++ b/config/test/config.myopic.yaml @@ -31,6 +31,14 @@ snapshots: end: "2013-03-08" electricity: + co2limit: 100.e+6 + + extendable_carriers: + Generator: [OCGT] + StorageUnit: [battery] + Store: [H2] + Link: [H2 pipeline] + renewable_carriers: [solar, onwind, offwind-ac, offwind-dc] atlite: diff --git a/test/config.overnight.yaml b/config/test/config.overnight.yaml similarity index 89% rename from test/config.overnight.yaml rename to config/test/config.overnight.yaml index fb468ded9..a2a0f5a46 100644 --- a/test/config.overnight.yaml +++ b/config/test/config.overnight.yaml @@ -28,6 +28,14 @@ snapshots: end: "2013-03-08" electricity: + co2limit: 100.e+6 + + extendable_carriers: + Generator: [OCGT] + StorageUnit: [battery] + Store: [H2] + Link: [H2 pipeline] + renewable_carriers: [solar, onwind, offwind-ac, offwind-dc] atlite: diff --git a/data/costs.csv b/data/costs.csv deleted file mode 100644 index 8953eb8a8..000000000 --- a/data/costs.csv +++ /dev/null @@ -1,195 +0,0 @@ -technology,year,parameter,value,unit,source -solar-rooftop,2030,discount rate,0.04,per unit,standard for decentral -onwind,2030,lifetime,30,years,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -offwind,2030,lifetime,30,years,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -solar,2030,lifetime,25,years,IEA2010 -solar-rooftop,2030,lifetime,25,years,IEA2010 -solar-utility,2030,lifetime,25,years,IEA2010 -PHS,2030,lifetime,80,years,IEA2010 -hydro,2030,lifetime,80,years,IEA2010 -ror,2030,lifetime,80,years,IEA2010 -OCGT,2030,lifetime,30,years,IEA2010 -nuclear,2030,lifetime,45,years,ECF2010 in DIW DataDoc http://hdl.handle.net/10419/80348 -CCGT,2030,lifetime,30,years,IEA2010 -coal,2030,lifetime,40,years,IEA2010 -lignite,2030,lifetime,40,years,IEA2010 -geothermal,2030,lifetime,40,years,IEA2010 -biomass,2030,lifetime,30,years,ECF2010 in DIW DataDoc http://hdl.handle.net/10419/80348 -oil,2030,lifetime,30,years,ECF2010 in DIW DataDoc http://hdl.handle.net/10419/80348 -onwind,2030,investment,1040,EUR/kWel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -offwind,2030,investment,1640,EUR/kWel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -offwind-ac-station,2030,investment,250,EUR/kWel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -offwind-ac-connection-submarine,2030,investment,2685,EUR/MW/km,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -offwind-ac-connection-underground,2030,investment,1342,EUR/MW/km,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -offwind-dc-station,2030,investment,400,EUR/kWel,Haertel 2017; assuming one onshore and one offshore node + 13% learning reduction -offwind-dc-connection-submarine,2030,investment,2000,EUR/MW/km,DTU report based on Fig 34 of https://ec.europa.eu/energy/sites/ener/files/documents/2014_nsog_report.pdf -offwind-dc-connection-underground,2030,investment,1000,EUR/MW/km,Haertel 2017; average + 13% learning reduction -solar,2030,investment,600,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -biomass,2030,investment,2209,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -geothermal,2030,investment,3392,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -coal,2030,investment,1300,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC) -lignite,2030,investment,1500,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -solar-rooftop,2030,investment,725,EUR/kWel,ETIP PV -solar-utility,2030,investment,425,EUR/kWel,ETIP PV -PHS,2030,investment,2000,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -hydro,2030,investment,2000,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -ror,2030,investment,3000,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -OCGT,2030,investment,400,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -nuclear,2030,investment,6000,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -CCGT,2030,investment,800,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -oil,2030,investment,400,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 -onwind,2030,FOM,2.450549,%/year,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -offwind,2030,FOM,2.304878,%/year,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -solar,2030,FOM,4.166667,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 -solar-rooftop,2030,FOM,2,%/year,ETIP PV -solar-utility,2030,FOM,3,%/year,ETIP PV -biomass,2030,FOM,4.526935,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 -geothermal,2030,FOM,2.358491,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 -coal,2030,FOM,1.923076,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC) -lignite,2030,FOM,2.0,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC) -oil,2030,FOM,1.5,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 -PHS,2030,FOM,1,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 -hydro,2030,FOM,1,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 -ror,2030,FOM,2,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 -CCGT,2030,FOM,2.5,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 -OCGT,2030,FOM,3.75,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 -onwind,2030,VOM,2.3,EUR/MWhel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -offwind,2030,VOM,2.7,EUR/MWhel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data -solar,2030,VOM,0.01,EUR/MWhel,RES costs made up to fix curtailment order -coal,2030,VOM,6,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC) -lignite,2030,VOM,7,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348 -CCGT,2030,VOM,4,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348 -OCGT,2030,VOM,3,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348 -nuclear,2030,VOM,8,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348 -gas,2030,fuel,21.6,EUR/MWhth,IEA2011b -uranium,2030,fuel,3,EUR/MWhth,DIW DataDoc http://hdl.handle.net/10419/80348 -oil,2030,VOM,3,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348 -nuclear,2030,fuel,3,EUR/MWhth,IEA2011b -biomass,2030,fuel,7,EUR/MWhth,IEA2011b -coal,2030,fuel,8.4,EUR/MWhth,IEA2011b -lignite,2030,fuel,2.9,EUR/MWhth,IEA2011b -oil,2030,fuel,50,EUR/MWhth,IEA WEM2017 97USD/boe = http://www.iea.org/media/weowebsite/2017/WEM_Documentation_WEO2017.pdf -PHS,2030,efficiency,0.75,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 -hydro,2030,efficiency,0.9,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 -ror,2030,efficiency,0.9,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 -OCGT,2030,efficiency,0.39,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 -CCGT,2030,efficiency,0.5,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 -biomass,2030,efficiency,0.468,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 -geothermal,2030,efficiency,0.239,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 -nuclear,2030,efficiency,0.337,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 -gas,2030,CO2 intensity,0.187,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php -coal,2030,efficiency,0.464,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC) -lignite,2030,efficiency,0.447,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 -oil,2030,efficiency,0.393,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 CT -coal,2030,CO2 intensity,0.354,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php -lignite,2030,CO2 intensity,0.334,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php -oil,2030,CO2 intensity,0.248,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php -geothermal,2030,CO2 intensity,0.026,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php -electrolysis,2030,investment,350,EUR/kWel,Palzer Thesis -electrolysis,2030,FOM,4,%/year,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013 -electrolysis,2030,lifetime,18,years,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013 -electrolysis,2030,efficiency,0.8,per unit,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013 -fuel cell,2030,investment,339,EUR/kWel,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013 -fuel cell,2030,FOM,3,%/year,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013 -fuel cell,2030,lifetime,20,years,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013 -fuel cell,2030,efficiency,0.58,per unit,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013 conservative 2020 -hydrogen storage,2030,investment,11.2,USD/kWh,budischak2013 -hydrogen storage,2030,lifetime,20,years,budischak2013 -hydrogen underground storage,2030,investment,0.5,EUR/kWh,maximum from https://www.nrel.gov/docs/fy10osti/46719.pdf -hydrogen underground storage,2030,lifetime,40,years,http://www.acatech.de/fileadmin/user_upload/Baumstruktur_nach_Website/Acatech/root/de/Publikationen/Materialien/ESYS_Technologiesteckbrief_Energiespeicher.pdf -H2 pipeline,2030,investment,267,EUR/MW/km,Welder et al https://doi.org/10.1016/j.ijhydene.2018.12.156 -H2 pipeline,2030,lifetime,40,years,Krieg2012 http://juser.fz-juelich.de/record/136392/files/Energie%26Umwelt_144.pdf -H2 pipeline,2030,FOM,5,%/year,Krieg2012 http://juser.fz-juelich.de/record/136392/files/Energie%26Umwelt_144.pdf -H2 pipeline,2030,efficiency,0.98,per unit,Krieg2012 http://juser.fz-juelich.de/record/136392/files/Energie%26Umwelt_144.pdf -methanation,2030,investment,1000,EUR/kWH2,Schaber thesis -methanation,2030,lifetime,25,years,Schaber thesis -methanation,2030,FOM,3,%/year,Schaber thesis -methanation,2030,efficiency,0.6,per unit,Palzer; Breyer for DAC -helmeth,2030,investment,1000,EUR/kW,no source -helmeth,2030,lifetime,25,years,no source -helmeth,2030,FOM,3,%/year,no source -helmeth,2030,efficiency,0.8,per unit,HELMETH press release -DAC,2030,investment,250,EUR/(tCO2/a),Fasihi/Climeworks -DAC,2030,lifetime,30,years,Fasihi -DAC,2030,FOM,4,%/year,Fasihi -battery inverter,2030,investment,411,USD/kWel,budischak2013 -battery inverter,2030,lifetime,20,years,budischak2013 -battery inverter,2030,efficiency,0.9,per unit charge/discharge,budischak2013; Lund and Kempton (2008) http://dx.doi.org/10.1016/j.enpol.2008.06.007 -battery inverter,2030,FOM,3,%/year,budischak2013 -battery storage,2030,investment,192,USD/kWh,budischak2013 -battery storage,2030,lifetime,15,years,budischak2013 -decentral air-sourced heat pump,2030,investment,1050,EUR/kWth,HP; Palzer thesis -decentral air-sourced heat pump,2030,lifetime,20,years,HP; Palzer thesis -decentral air-sourced heat pump,2030,FOM,3.5,%/year,Palzer thesis -decentral air-sourced heat pump,2030,efficiency,3,per unit,default for costs -decentral air-sourced heat pump,2030,discount rate,0.04,per unit,Palzer thesis -decentral ground-sourced heat pump,2030,investment,1400,EUR/kWth,Palzer thesis -decentral ground-sourced heat pump,2030,lifetime,20,years,Palzer thesis -decentral ground-sourced heat pump,2030,FOM,3.5,%/year,Palzer thesis -decentral ground-sourced heat pump,2030,efficiency,4,per unit,default for costs -decentral ground-sourced heat pump,2030,discount rate,0.04,per unit,Palzer thesis -central air-sourced heat pump,2030,investment,700,EUR/kWth,Palzer thesis -central air-sourced heat pump,2030,lifetime,20,years,Palzer thesis -central air-sourced heat pump,2030,FOM,3.5,%/year,Palzer thesis -central air-sourced heat pump,2030,efficiency,3,per unit,default for costs -retrofitting I,2030,discount rate,0.04,per unit,Palzer thesis -retrofitting I,2030,lifetime,50,years,Palzer thesis -retrofitting I,2030,FOM,1,%/year,Palzer thesis -retrofitting I,2030,investment,50,EUR/m2/fraction reduction,Palzer thesis -retrofitting II,2030,discount rate,0.04,per unit,Palzer thesis -retrofitting II,2030,lifetime,50,years,Palzer thesis -retrofitting II,2030,FOM,1,%/year,Palzer thesis -retrofitting II,2030,investment,250,EUR/m2/fraction reduction,Palzer thesis -water tank charger,2030,efficiency,0.9,per unit,HP -water tank discharger,2030,efficiency,0.9,per unit,HP -decentral water tank storage,2030,investment,860,EUR/m3,IWES Interaktion -decentral water tank storage,2030,FOM,1,%/year,HP -decentral water tank storage,2030,lifetime,20,years,HP -decentral water tank storage,2030,discount rate,0.04,per unit,Palzer thesis -central water tank storage,2030,investment,30,EUR/m3,IWES Interaktion -central water tank storage,2030,FOM,1,%/year,HP -central water tank storage,2030,lifetime,40,years,HP -decentral resistive heater,2030,investment,100,EUR/kWhth,Schaber thesis -decentral resistive heater,2030,lifetime,20,years,Schaber thesis -decentral resistive heater,2030,FOM,2,%/year,Schaber thesis -decentral resistive heater,2030,efficiency,0.9,per unit,Schaber thesis -decentral resistive heater,2030,discount rate,0.04,per unit,Palzer thesis -central resistive heater,2030,investment,100,EUR/kWhth,Schaber thesis -central resistive heater,2030,lifetime,20,years,Schaber thesis -central resistive heater,2030,FOM,2,%/year,Schaber thesis -central resistive heater,2030,efficiency,0.9,per unit,Schaber thesis -decentral gas boiler,2030,investment,175,EUR/kWhth,Palzer thesis -decentral gas boiler,2030,lifetime,20,years,Palzer thesis -decentral gas boiler,2030,FOM,2,%/year,Palzer thesis -decentral gas boiler,2030,efficiency,0.9,per unit,Palzer thesis -decentral gas boiler,2030,discount rate,0.04,per unit,Palzer thesis -central gas boiler,2030,investment,63,EUR/kWhth,Palzer thesis -central gas boiler,2030,lifetime,22,years,Palzer thesis -central gas boiler,2030,FOM,1,%/year,Palzer thesis -central gas boiler,2030,efficiency,0.9,per unit,Palzer thesis -decentral CHP,2030,lifetime,25,years,HP -decentral CHP,2030,investment,1400,EUR/kWel,HP -decentral CHP,2030,FOM,3,%/year,HP -decentral CHP,2030,discount rate,0.04,per unit,Palzer thesis -central CHP,2030,lifetime,25,years,HP -central CHP,2030,investment,650,EUR/kWel,HP -central CHP,2030,FOM,3,%/year,HP -decentral solar thermal,2030,discount rate,0.04,per unit,Palzer thesis -decentral solar thermal,2030,FOM,1.3,%/year,HP -decentral solar thermal,2030,investment,270000,EUR/1000m2,HP -decentral solar thermal,2030,lifetime,20,years,HP -central solar thermal,2030,FOM,1.4,%/year,HP -central solar thermal,2030,investment,140000,EUR/1000m2,HP -central solar thermal,2030,lifetime,20,years,HP -HVAC overhead,2030,investment,400,EUR/MW/km,Hagspiel -HVAC overhead,2030,lifetime,40,years,Hagspiel -HVAC overhead,2030,FOM,2,%/year,Hagspiel -HVDC overhead,2030,investment,400,EUR/MW/km,Hagspiel -HVDC overhead,2030,lifetime,40,years,Hagspiel -HVDC overhead,2030,FOM,2,%/year,Hagspiel -HVDC submarine,2030,investment,2000,EUR/MW/km,DTU report based on Fig 34 of https://ec.europa.eu/energy/sites/ener/files/documents/2014_nsog_report.pdf -HVDC submarine,2030,lifetime,40,years,Hagspiel -HVDC submarine,2030,FOM,2,%/year,Hagspiel -HVDC inverter pair,2030,investment,150000,EUR/MW,Hagspiel -HVDC inverter pair,2030,lifetime,40,years,Hagspiel -HVDC inverter pair,2030,FOM,2,%/year,Hagspiel diff --git a/data/override_component_attrs/buses.csv b/data/override_component_attrs/buses.csv deleted file mode 100644 index 7581e3286..000000000 --- a/data/override_component_attrs/buses.csv +++ /dev/null @@ -1,3 +0,0 @@ -attribute,type,unit,default,description,status -location,string,n/a,n/a,Reference to original electricity bus,Input (optional) -unit,string,n/a,MWh,Unit of the bus (descriptive only), Input (optional) diff --git a/data/override_component_attrs/generators.csv b/data/override_component_attrs/generators.csv deleted file mode 100644 index 4f2143960..000000000 --- a/data/override_component_attrs/generators.csv +++ /dev/null @@ -1,4 +0,0 @@ -attribute,type,unit,default,description,status -carrier,string,n/a,n/a,carrier,Input (optional) -lifetime,float,years,inf,lifetime,Input (optional) -build_year,int,year ,0,build year,Input (optional) diff --git a/data/override_component_attrs/links.csv b/data/override_component_attrs/links.csv deleted file mode 100644 index 0fc2747ac..000000000 --- a/data/override_component_attrs/links.csv +++ /dev/null @@ -1,13 +0,0 @@ -attribute,type,unit,default,description,status -bus2,string,n/a,n/a,2nd bus,Input (optional) -bus3,string,n/a,n/a,3rd bus,Input (optional) -bus4,string,n/a,n/a,4th bus,Input (optional) -efficiency2,static or series,per unit,1,2nd bus efficiency,Input (optional) -efficiency3,static or series,per unit,1,3rd bus efficiency,Input (optional) -efficiency4,static or series,per unit,1,4th bus efficiency,Input (optional) -p2,series,MW,0,2nd bus output,Output -p3,series,MW,0,3rd bus output,Output -p4,series,MW,0,4th bus output,Output -carrier,string,n/a,n/a,carrier,Input (optional) -lifetime,float,years,inf,lifetime,Input (optional) -build_year,int,year ,0,build year,Input (optional) diff --git a/data/override_component_attrs/loads.csv b/data/override_component_attrs/loads.csv deleted file mode 100644 index 10bb5b4f9..000000000 --- a/data/override_component_attrs/loads.csv +++ /dev/null @@ -1,2 +0,0 @@ -attribute,type,unit,default,description,status -carrier,string,n/a,n/a,carrier,Input (optional) diff --git a/data/override_component_attrs/stores.csv b/data/override_component_attrs/stores.csv deleted file mode 100644 index 4f2143960..000000000 --- a/data/override_component_attrs/stores.csv +++ /dev/null @@ -1,4 +0,0 @@ -attribute,type,unit,default,description,status -carrier,string,n/a,n/a,carrier,Input (optional) -lifetime,float,years,inf,lifetime,Input (optional) -build_year,int,year ,0,build year,Input (optional) diff --git a/doc/conf.py b/doc/conf.py index 4b3978afd..1ddae4667 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -36,6 +36,7 @@ extensions = [ #'sphinx.ext.autodoc', #'sphinx.ext.autosummary', + "myst_parser", "sphinx.ext.autosectionlabel", "sphinx.ext.intersphinx", "sphinx.ext.todo", @@ -81,7 +82,7 @@ # The short X.Y version. version = "0.8" # The full version, including alpha/beta/rc tags. -release = "0.8.0" +release = "0.8.1" # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. diff --git a/doc/configtables/biomass.csv b/doc/configtables/biomass.csv new file mode 100644 index 000000000..f5b4841f2 --- /dev/null +++ b/doc/configtables/biomass.csv @@ -0,0 +1,7 @@ +,Unit,Values,Description +year ,--,"{2010, 2020, 2030, 2040, 2050}",Year for which to retrieve biomass potential according to the assumptions of the `JRC ENSPRESO `_ . +scenario ,--,"{""ENS_Low"", ""ENS_Med"", ""ENS_High""}",Scenario for which to retrieve biomass potential. The scenario definition can be seen in `ENSPRESO_BIOMASS `_ +classes ,,, +-- solid biomass,--,Array of biomass comodity,The comodity that are included as solid biomass +-- not included,--,Array of biomass comodity,The comodity that are not included as a biomass potential +-- biogas,--,Array of biomass comodity,The comodity that are included as biogas diff --git a/doc/configtables/co2_budget.csv b/doc/configtables/co2_budget.csv new file mode 100644 index 000000000..21b42f056 --- /dev/null +++ b/doc/configtables/co2_budget.csv @@ -0,0 +1,2 @@ +,Unit,Values,Description +co2_budget,--,Dictionary with planning horizons as keys.,CO2 budget as a fraction of 1990 emissions. Overwritten if ``CO2Lx`` or ``cb`` are set in ``{sector_opts}`` wildcard"doc/configtables/othertoplevel.csv diff --git a/doc/configtables/countries.csv b/doc/configtables/countries.csv new file mode 100644 index 000000000..6a386416c --- /dev/null +++ b/doc/configtables/countries.csv @@ -0,0 +1,2 @@ + ,Unit,Values,Description +countries,--,"Subset of {'AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK'}","European countries defined by their `Two-letter country codes (ISO 3166-1) `_ which should be included in the energy system model." diff --git a/doc/configtables/electricity.csv b/doc/configtables/electricity.csv index 9cf23ebf7..4c04fee66 100644 --- a/doc/configtables/electricity.csv +++ b/doc/configtables/electricity.csv @@ -1,29 +1,36 @@ -,Unit,Values,Description -voltages,kV,"Any subset of {220., 300., 380.}",Voltage levels to consider -gaslimit,MWhth,"float or false",Global gas usage limit -co2limit,:math:`t_{CO_2-eq}/a`,float,Cap on total annual system carbon dioxide emissions -co2base,:math:`t_{CO_2-eq}/a`,float,Reference value of total annual system carbon dioxide emissions if relative emission reduction target is specified in ``{opts}`` wildcard. -agg_p_nom_limits,file,path,Reference to ``.csv`` file specifying per carrier generator nominal capacity constraints for individual countries if ``'CCL'`` is in ``{opts}`` wildcard. Defaults to ``data/agg_p_nom_minmax.csv``. -operational_reserve,,,"Settings for reserve requirements following like `GenX `_" --- activate,bool,"true or false","Whether to take operational reserve requirements into account during optimisation" --- epsilon_load,--,float,share of total load --- epsilon_vres,--,float,share of total renewable supply --- contingency,MW,float,fixed reserve capacity -max_hours,,, --- battery,h,float,Maximum state of charge capacity of the battery in terms of hours at full output capacity ``p_nom``. Cf. `PyPSA documentation `_. --- H2,h,float,Maximum state of charge capacity of the hydrogen storage in terms of hours at full output capacity ``p_nom``. Cf. `PyPSA documentation `_. -extendable_carriers,,, --- Generator,--,"Any extendable carrier","Defines existing or non-existing conventional and renewable power plants to be extendable during the optimization. Conventional generators can only be built/expanded where already existent today. If a listed conventional carrier is not included in the ``conventional_carriers`` list, the lower limit of the capacity expansion is set to 0." --- StorageUnit,--,"Any subset of {'battery','H2'}",Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity. --- Store,--,"Any subset of {'battery','H2'}",Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity. --- Link,--,Any subset of {'H2 pipeline'},Adds extendable links (H2 pipelines only) at every connection where there are lines or HVDC links without capacity limits and with zero initial capacity. Hydrogen pipelines require hydrogen storage to be modelled as ``Store``. -powerplants_filter,--,"use `pandas.query `_ strings here, e.g. Country not in ['Germany']",Filter query for the default powerplant database. -custom_powerplants,--,"use `pandas.query `_ strings here, e.g. Country in ['Germany']",Filter query for the custom powerplant database. -conventional_carriers,--,"Any subset of {nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass}","List of conventional power plants to include in the model from ``resources/powerplants.csv``. If an included carrier is also listed in `extendable_carriers`, the capacity is taken as a lower bound." -renewable_carriers,--,"Any subset of {solar, onwind, offwind-ac, offwind-dc, hydro}",List of renewable generators to include in the model. -estimate_renewable_capacities,,, --- enable,,bool,"Activate routine to estimate renewable capacities" --- from_opsd,--,bool,"Add capacities from OPSD data" --- year,--,bool,"Renewable capacities are based on existing capacities reported by IRENA for the specified year" --- expansion_limit,--,float or false,"Artificially limit maximum capacities to factor * (IRENA capacities), i.e. 110% of 's capacities => expansion_limit: 1.1 false: Use estimated renewable potentials determine by the workflow" --- technology_mapping,,,"Mapping between powerplantmatching and PyPSA-Eur technology names" +,Unit,Values,Description +voltages,kV,"Any subset of {220., 300., 380.}",Voltage levels to consider +gaslimit,MWhth,float or false,Global gas usage limit +co2limit,:math:`t_{CO_2-eq}/a`,float,Cap on total annual system carbon dioxide emissions +co2base,:math:`t_{CO_2-eq}/a`,float,Reference value of total annual system carbon dioxide emissions if relative emission reduction target is specified in ``{opts}`` wildcard. +agg_p_nom_limits,file,path,Reference to ``.csv`` file specifying per carrier generator nominal capacity constraints for individual countries if ``'CCL'`` is in ``{opts}`` wildcard. Defaults to ``data/agg_p_nom_minmax.csv``. +operational_reserve,,,Settings for reserve requirements following `GenX `_ +,,, +-- activate,bool,true or false,Whether to take operational reserve requirements into account during optimisation +-- epsilon_load,--,float,share of total load +-- epsilon_vres,--,float,share of total renewable supply +-- contingency,MW,float,fixed reserve capacity +max_hours,,, +-- battery,h,float,Maximum state of charge capacity of the battery in terms of hours at full output capacity ``p_nom``. Cf. `PyPSA documentation `_. +-- H2,h,float,Maximum state of charge capacity of the hydrogen storage in terms of hours at full output capacity ``p_nom``. Cf. `PyPSA documentation `_. +extendable_carriers,,, +-- Generator,--,Any extendable carrier,"Defines existing or non-existing conventional and renewable power plants to be extendable during the optimization. Conventional generators can only be built/expanded where already existent today. If a listed conventional carrier is not included in the ``conventional_carriers`` list, the lower limit of the capacity expansion is set to 0." +-- StorageUnit,--,"Any subset of {'battery','H2'}",Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity. +-- Store,--,"Any subset of {'battery','H2'}",Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity. +-- Link,--,Any subset of {'H2 pipeline'},Adds extendable links (H2 pipelines only) at every connection where there are lines or HVDC links without capacity limits and with zero initial capacity. Hydrogen pipelines require hydrogen storage to be modelled as ``Store``. +powerplants_filter,--,"use `pandas.query `_ strings here, e.g. ``Country not in ['Germany']``",Filter query for the default powerplant database. +,,, +custom_powerplants,--,"use `pandas.query `_ strings here, e.g. ``Country in ['Germany']``",Filter query for the custom powerplant database. +,,, +conventional_carriers,--,"Any subset of {nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass}","List of conventional power plants to include in the model from ``resources/powerplants.csv``. If an included carrier is also listed in ``extendable_carriers``, the capacity is taken as a lower bound." +,,, +renewable_carriers,--,"Any subset of {solar, onwind, offwind-ac, offwind-dc, hydro}",List of renewable generators to include in the model. +estimate_renewable_capacities,,, +-- enable,,bool,Activate routine to estimate renewable capacities +-- from_opsd,--,bool,Add renewable capacities from `OPSD database `_. The value is depreciated but still can be used. +-- year,--,bool,Renewable capacities are based on existing capacities reported by IRENA (IRENASTAT) for the specified year +-- expansion_limit,--,float or false,"Artificially limit maximum IRENA capacities to a factor. For example, an ``expansion_limit: 1.1`` means 110% of capacities . If false are chosen, the estimated renewable potentials determine by the workflow are used." +-- technology_mapping,,,Mapping between PyPSA-Eur and powerplantmatching technology names +-- -- Offshore,--,"Any subset of {offwind-ac, offwind-dc}","List of PyPSA-Eur carriers that is considered as (IRENA, OPSD) onshore technology." +-- -- Offshore,--,{onwind},"List of PyPSA-Eur carriers that is considered as (IRENA, OPSD) offshore technology." +-- -- PV,--,{solar},"List of PyPSA-Eur carriers that is considered as (IRENA, OPSD) PV technology." diff --git a/doc/configtables/enable.csv b/doc/configtables/enable.csv index 8a543b46c..e1349fef8 100644 --- a/doc/configtables/enable.csv +++ b/doc/configtables/enable.csv @@ -1,4 +1,5 @@ ,Unit,Values,Description +enable,str or bool,"{auto, true, false}","Switch to include (true) or exclude (false) the retrieve_* rules of snakemake into the workflow; 'auto' sets true|false based on availability of an internet connection to prevent issues with snakemake failing due to lack of internet connection." prepare_links_p_nom,bool,"{true, false}","Switch to retrieve current HVDC projects from `Wikipedia `_" retrieve_databundle,bool,"{true, false}","Switch to retrieve databundle from zenodo via the rule :mod:`retrieve_databundle` or whether to keep a custom databundle located in the corresponding folder." retrieve_sector_databundle,bool,"{true, false}","Switch to retrieve sector databundle from zenodo via the rule :mod:`retrieve_sector_databundle` or whether to keep a custom databundle located in the corresponding folder." diff --git a/doc/configtables/energy.csv b/doc/configtables/energy.csv new file mode 100644 index 000000000..8718d75ed --- /dev/null +++ b/doc/configtables/energy.csv @@ -0,0 +1,7 @@ +,Unit,Values,Description +energy_totals_year ,--,"{1990,1995,2000,2005,2010,2011,…} ",The year for the sector energy use. The year must be avaliable in the Eurostat report +base_emissions_year ,--,"YYYY; e.g. 1990","The base year for the sector emissions. See `European Environment Agency (EEA) `_." + +eurostat_report_year ,--,"{2016,2017,2018}","The publication year of the Eurostat report. 2016 includes Bosnia and Herzegovina, 2017 does not" + +emissions ,--,"{CO2, All greenhouse gases - (CO2 equivalent)}","Specify which sectoral emissions are taken into account. Data derived from EEA. Currently only CO2 is implemented." diff --git a/doc/configtables/existing_capacities.csv b/doc/configtables/existing_capacities.csv new file mode 100644 index 000000000..875191931 --- /dev/null +++ b/doc/configtables/existing_capacities.csv @@ -0,0 +1,6 @@ +,Unit,Values,Description +grouping_years_power ,--,A list of years,Intervals to group existing capacities for power +grouping_years_heat ,--,A list of years below 2020,Intervals to group existing capacities for heat + +threshold_capacity ,MW,float,Capacities generators and links of below threshold are removed during add_existing_capacities +conventional_carriers ,--,"Any subset of {uranium, coal, lignite, oil} ",List of conventional power plants to include in the sectoral network diff --git a/doc/configtables/foresight.csv b/doc/configtables/foresight.csv new file mode 100644 index 000000000..a19ec1393 --- /dev/null +++ b/doc/configtables/foresight.csv @@ -0,0 +1,2 @@ +,Unit,Values,Description +foresight,string,"{overnight, myopic, perfect}","See :ref:`Foresight Options` for detail explanations." diff --git a/doc/configtables/industry.csv b/doc/configtables/industry.csv new file mode 100644 index 000000000..fc1b3f0fa --- /dev/null +++ b/doc/configtables/industry.csv @@ -0,0 +1,31 @@ +,Unit,Values,Description +St_primary_fraction,--,Dictionary with planning horizons as keys.,The fraction of steel produced via primary route versus secondary route (scrap+EAF). Current fraction is 0.6 +DRI_fraction,--,Dictionary with planning horizons as keys.,The fraction of the primary route DRI + EAF +,,, +H2_DRI,--,float,The hydrogen consumption in Direct Reduced Iron (DRI) Mwh_H2 LHV/ton_Steel from 51kgH2/tSt in `Vogl et al (2018) `_ +elec_DRI,MWh/tSt,float,The electricity consumed in Direct Reduced Iron (DRI) shaft. From `HYBRIT brochure `_ +Al_primary_fraction,--,Dictionary with planning horizons as keys.,The fraction of aluminium produced via the primary route versus scrap. Current fraction is 0.4 +MWh_NH3_per_tNH3,LHV,float,The energy amount per ton of ammonia. +MWh_CH4_per_tNH3_SMR,--,float,The energy amount of methane needed to produce a ton of ammonia using steam methane reforming (SMR). Value derived from 2012's demand from `Center for European Policy Studies (2008) `_ +MWh_elec_per_tNH3_SMR,--,float,"The energy amount of electricity needed to produce a ton of ammonia using steam methane reforming (SMR). same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3" +Mwh_H2_per_tNH3 _electrolysis,--,float,"The energy amount of hydrogen needed to produce a ton of ammonia using Haber–Bosch process. From `Wang et al (2018) `_, Base value assumed around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy)" +Mwh_elec_per_tNH3 _electrolysis,--,float,"The energy amount of electricity needed to produce a ton of ammonia using Haber–Bosch process. From `Wang et al (2018) `_, Table 13 (air separation and HB)" +Mwh_NH3_per_MWh _H2_cracker,--,float,The energy amount of amonia needed to produce an energy amount hydrogen using ammonia cracker +NH3_process_emissions,MtCO2/a,float,The emission of ammonia production from steam methane reforming (SMR). From UNFCCC for 2015 for EU28 +petrochemical_process _emissions,MtCO2/a,float,The emission of petrochemical production. From UNFCCC for 2015 for EU28 +HVC_primary_fraction,--,float,The fraction of high value chemicals (HVC) produced via primary route +HVC_mechanical_recycling _fraction,--,float,The fraction of high value chemicals (HVC) produced using mechanical recycling +HVC_chemical_recycling _fraction,--,float,The fraction of high value chemicals (HVC) produced using chemical recycling +,,, +HVC_production_today,MtHVC/a,float,"The amount of high value chemicals (HVC) produced. This includes ethylene, propylene and BTX. From `DECHEMA (2017) `_, Figure 16, page 107" +Mwh_elec_per_tHVC _mechanical_recycling,MWh/tHVC,float,"The energy amount of electricity needed to produce a ton of high value chemical (HVC) using mechanical recycling. From SI of `Meys et al (2020) `_, Table S5, for HDPE, PP, PS, PET. LDPE would be 0.756." +Mwh_elec_per_tHVC _chemical_recycling,MWh/tHVC,float,"The energy amount of electricity needed to produce a ton of high value chemical (HVC) using chemical recycling. The default value is based on pyrolysis and electric steam cracking. From `Material Economics (2019) `_, page 125" +,,, +chlorine_production _today,MtCl/a,float,"The amount of chlorine produced. From `DECHEMA (2017) `_, Table 7, page 43" +MWh_elec_per_tCl,MWh/tCl,float,"The energy amount of electricity needed to produce a ton of chlorine. From `DECHEMA (2017) `_, Table 6 page 43" +MWh_H2_per_tCl,MWhH2/tCl,float,"The energy amount of hydrogen needed to produce a ton of chlorine. The value is negative since hydrogen produced in chloralkali process. From `DECHEMA (2017) `_, page 43" +methanol_production _today,MtMeOH/a,float,"The amount of methanol produced. From `DECHEMA (2017) `_, page 62" +MWh_elec_per_tMeOH,MWh/tMeOH,float,"The energy amount of electricity needed to produce a ton of methanol. From `DECHEMA (2017) `_, Table 14, page 65" +MWh_CH4_per_tMeOH,MWhCH4/tMeOH,float,"The energy amount of methane needed to produce a ton of methanol. From `DECHEMA (2017) `_, Table 14, page 65" +hotmaps_locate_missing,--,"{true,false}",Locate industrial sites without valid locations based on city and countries. +reference_year,year,YYYY,The year used as the baseline for industrial energy demand and production. Data extracted from `JRC-IDEES 2015 `_ diff --git a/doc/configtables/lines.csv b/doc/configtables/lines.csv index ddf02e542..ec9ec0070 100644 --- a/doc/configtables/lines.csv +++ b/doc/configtables/lines.csv @@ -2,5 +2,12 @@ types,--,"Values should specify a `line type in PyPSA `_. Keys should specify the corresponding voltage level (e.g. 220., 300. and 380. kV)","Specifies line types to assume for the different voltage levels of the ENTSO-E grid extraction. Should normally handle voltage levels 220, 300, and 380 kV" s_max_pu,--,"Value in [0.,1.]","Correction factor for line capacities (``s_nom``) to approximate :math:`N-1` security and reserve capacity for reactive power flows" s_nom_max,MW,"float","Global upper limit for the maximum capacity of each extendable line." +max_extension,MW,"float","Upper limit for the extended capacity of each extendable line." length_factor,--,float,"Correction factor to account for the fact that buses are *not* connected by lines through air-line distance." under_construction,--,"One of {'zero': set capacity to zero, 'remove': remove completely, 'keep': keep with full capacity}","Specifies how to handle lines which are currently under construction." +dynamic_line_rating,,, +-- activate,bool,"true or false","Whether to take dynamic line rating into account" +-- cutout,--,"Should be a folder listed in the configuration ``atlite: cutouts:`` (e.g. 'europe-2013-era5') or reference an existing folder in the directory ``cutouts``. Source module must be ERA5.","Specifies the directory where the relevant weather data ist stored." +-- correction_factor,--,"float","Factor to compensate for overestimation of wind speeds in hourly averaged wind data" +-- max_voltage_difference,deg,"float","Maximum voltage angle difference in degrees or 'false' to disable" +-- max_line_rating,--,"float","Maximum line rating relative to nominal capacity without DLR, e.g. 1.3 or 'false' to disable" diff --git a/doc/configtables/links.csv b/doc/configtables/links.csv index c9981dc73..c1ffb427c 100644 --- a/doc/configtables/links.csv +++ b/doc/configtables/links.csv @@ -1,5 +1,6 @@ ,Unit,Values,Description p_max_pu,--,"Value in [0.,1.]","Correction factor for link capacities ``p_nom``." p_nom_max,MW,"float","Global upper limit for the maximum capacity of each extendable DC link." +max_extension,MW,"float","Upper limit for the extended capacity of each extendable DC link." include_tyndp,bool,"{'true', 'false'}","Specifies whether to add HVDC link projects from the `TYNDP 2018 `_ which are at least in permitting." under_construction,--,"One of {'zero': set capacity to zero, 'remove': remove completely, 'keep': keep with full capacity}","Specifies how to handle lines which are currently under construction." diff --git a/doc/configtables/plotting.csv b/doc/configtables/plotting.csv index bea345cae..ed5d9c9fe 100644 --- a/doc/configtables/plotting.csv +++ b/doc/configtables/plotting.csv @@ -1,10 +1,10 @@ -,Unit,Values,Description -map,,, --- boundaries,°,"[x1,x2,y1,y2]","Boundaries of the map plots in degrees latitude (y) and longitude (x)" -costs_max,bn Euro,float,"Upper y-axis limit in cost bar plots." -costs_threshold,bn Euro,float,"Threshold below which technologies will not be shown in cost bar plots." -energy_max,TWh,float,"Upper y-axis limit in energy bar plots." -energy_min,TWh,float,"Lower y-axis limit in energy bar plots." -energy_threshold,TWh,float,"Threshold below which technologies will not be shown in energy bar plots." -tech_colors,--,"carrier -> HEX colour code","Mapping from network ``carrier`` to a colour (`HEX colour code `_)." -nice_names,--,"str -> str","Mapping from network ``carrier`` to a more readable name." +,Unit,Values,Description +map,,, +-- boundaries,°,"[x1,x2,y1,y2]",Boundaries of the map plots in degrees latitude (y) and longitude (x) +costs_max,bn Euro,float,Upper y-axis limit in cost bar plots. +costs_threshold,bn Euro,float,Threshold below which technologies will not be shown in cost bar plots. +energy_max,TWh,float,Upper y-axis limit in energy bar plots. +energy_min,TWh,float,Lower y-axis limit in energy bar plots. +energy_threshold,TWh,float,Threshold below which technologies will not be shown in energy bar plots. +tech_colors,--,carrier -> HEX colour code,Mapping from network ``carrier`` to a colour (`HEX colour code `_). +nice_names,--,str -> str,Mapping from network ``carrier`` to a more readable name. diff --git a/doc/configtables/sector-opts.csv b/doc/configtables/sector-opts.csv index 5a6b68527..ea39c3b0d 100644 --- a/doc/configtables/sector-opts.csv +++ b/doc/configtables/sector-opts.csv @@ -1,5 +1,5 @@ Trigger, Description, Definition, Status -``nH``, i.e. ``2H``-``6H``, Resample the time-resolution by averaging over every ``n`` snapshots, ``prepare_network``: `average_every_nhours() `_ and its `caller `__), In active use +``nH``, i.e. ``2H``-``6H``, "Resample the time-resolution by averaging over every ``n`` snapshots, ``prepare_network``: `average_every_nhours() `_ and its `caller `__)", In active use ``Co2L``, Add an overall absolute carbon-dioxide emissions limit configured in ``electricity: co2limit``. If a float is appended an overall emission limit relative to the emission level given in ``electricity: co2base`` is added (e.g. ``Co2L0.05`` limits emissisions to 5% of what is given in ``electricity: co2base``), ``prepare_network``: `add_co2limit() `_ and its `caller `__, In active use ``carrier+{c|p|m}factor``,"Alter the capital cost (``c``), installable potential (``p``) or marginal costs (``m``) of a carrier by a factor. Example: ``solar+c0.5`` reduces the capital cost of solar to 50\% of original values.", ``prepare_network``, In active use ``T``,Add land transport sector,,In active use diff --git a/doc/configtables/sector.csv b/doc/configtables/sector.csv new file mode 100644 index 000000000..d610c8626 --- /dev/null +++ b/doc/configtables/sector.csv @@ -0,0 +1,122 @@ +,Unit,Values,Description +district_heating,--,,`prepare_sector_network.py `_ +-- potential,--,float,maximum fraction of urban demand which can be supplied by district heating +-- progress,--,Dictionary with planning horizons as keys., Increase of today's district heating demand to potential maximum district heating share. Progress = 0 means today's district heating share. Progress = 1 means maximum fraction of urban demand is supplied by district heating +-- district_heating_loss,--,float,Share increase in district heat demand in urban central due to heat losses +cluster_heat_buses,--,"{true, false}",Cluster residential and service heat buses in `prepare_sector_network.py `_ to one to save memory. +,,, +bev_dsm_restriction _value,--,float,Adds a lower state of charge (SOC) limit for battery electric vehicles (BEV) to manage its own energy demand (DSM). Located in `build_transport_demand.py `_. Set to 0 for no restriction on BEV DSM +bev_dsm_restriction _time,--,float,Time at which SOC of BEV has to be dsm_restriction_value +transport_heating _deadband_upper,°C,float,"The maximum temperature in the vehicle. At higher temperatures, the energy required for cooling in the vehicle increases." +transport_heating _deadband_lower,°C,float,"The minimum temperature in the vehicle. At lower temperatures, the energy required for heating in the vehicle increases." +,,, +ICE_lower_degree_factor,--,float,Share increase in energy demand in internal combustion engine (ICE) for each degree difference between the cold environment and the minimum temperature. +ICE_upper_degree_factor,--,float,Share increase in energy demand in internal combustion engine (ICE) for each degree difference between the hot environment and the maximum temperature. +EV_lower_degree_factor,--,float,Share increase in energy demand in electric vehicles (EV) for each degree difference between the cold environment and the minimum temperature. +EV_upper_degree_factor,--,float,Share increase in energy demand in electric vehicles (EV) for each degree difference between the hot environment and the maximum temperature. +bev_dsm,--,"{true, false}",Add the option for battery electric vehicles (BEV) to participate in demand-side management (DSM) +,,, +bev_availability,--,float,The share for battery electric vehicles (BEV) that are able to do demand side management (DSM) +bev_energy,--,float,The average size of battery electric vehicles (BEV) in MWh +bev_charge_efficiency,--,float,Battery electric vehicles (BEV) charge and discharge efficiency +bev_plug_to_wheel _efficiency,km/kWh,float,The distance battery electric vehicles (BEV) can travel in km per kWh of energy charge in battery. Base value comes from `Tesla Model S `_ +bev_charge_rate,MWh,float,The power consumption for one electric vehicle (EV) in MWh. Value derived from 3-phase charger with 11 kW. +bev_avail_max,--,float,The maximum share plugged-in availability for passenger electric vehicles. +bev_avail_mean,--,float,The average share plugged-in availability for passenger electric vehicles. +v2g,--,"{true, false}",Allows feed-in to grid from EV battery +land_transport_fuel_cell _share,--,Dictionary with planning horizons as keys.,The share of vehicles that uses fuel cells in a given year +land_transport_electric _share,--,Dictionary with planning horizons as keys.,The share of vehicles that uses electric vehicles (EV) in a given year +land_transport_ice _share,--,Dictionary with planning horizons as keys.,The share of vehicles that uses internal combustion engines (ICE) in a given year. What is not EV or FCEV is oil-fuelled ICE. +transport_fuel_cell _efficiency,--,float,The H2 conversion efficiencies of fuel cells in transport +transport_internal _combustion_efficiency,--,float,The oil conversion efficiencies of internal combustion engine (ICE) in transport +agriculture_machinery _electric_share,--,float,The share for agricultural machinery that uses electricity +agriculture_machinery _oil_share,--,float,The share for agricultural machinery that uses oil +agriculture_machinery _fuel_efficiency,--,float,The efficiency of electric-powered machinery in the conversion of electricity to meet agricultural needs. +agriculture_machinery _electric_efficiency,--,float,The efficiency of oil-powered machinery in the conversion of oil to meet agricultural needs. +Mwh_MeOH_per_MWh_H2,LHV,float,"The energy amount of the produced methanol per energy amount of hydrogen. From `DECHEMA (2017) `_, page 64." +MWh_MeOH_per_tCO2,LHV,float,"The energy amount of the produced methanol per ton of CO2. From `DECHEMA (2017) `_, page 64." +MWh_MeOH_per_MWh_e,LHV,float,"The energy amount of the produced methanol per energy amount of electricity. From `DECHEMA (2017) `_, page 64." +shipping_hydrogen _liquefaction,--,"{true, false}",Whether to include liquefaction costs for hydrogen demand in shipping. +,,, +shipping_hydrogen_share,--,Dictionary with planning horizons as keys.,The share of ships powered by hydrogen in a given year +shipping_methanol_share,--,Dictionary with planning horizons as keys.,The share of ships powered by methanol in a given year +shipping_oil_share,--,Dictionary with planning horizons as keys.,The share of ships powered by oil in a given year +shipping_methanol _efficiency,--,float,The efficiency of methanol-powered ships in the conversion of methanol to meet shipping needs (propulsion). The efficiency increase from oil can be 10-15% higher according to the `IEA `_ +,,, +shipping_oil_efficiency,--,float,The efficiency of oil-powered ships in the conversion of oil to meet shipping needs (propulsion). Base value derived from 2011 +aviation_demand_factor,--,float,The proportion of demand for aviation compared to today's consumption +HVC_demand_factor,--,float,The proportion of demand for high-value chemicals compared to today's consumption +,,, +time_dep_hp_cop,--,"{true, false}",Consider the time dependent coefficient of performance (COP) of the heat pump +heat_pump_sink_T,°C,float,The temperature heat sink used in heat pumps based on DTU / large area radiators. The value is conservatively high to cover hot water and space heating in poorly-insulated buildings +reduce_space_heat _exogenously,--,"{true, false}",Influence on space heating demand by a certain factor (applied before losses in district heating). +reduce_space_heat _exogenously_factor,--,Dictionary with planning horizons as keys.,"A positive factor can mean renovation or demolition of a building. If the factor is negative, it can mean an increase in floor area, increased thermal comfort, population growth. The default factors are determined by the `Eurocalc Homes and buildings decarbonization scenario `_" +retrofitting,,, +-- retro_endogen,--,"{true, false}",Add retrofitting as an endogenous system which co-optimise space heat savings. +-- cost_factor,--,float,Weight costs for building renovation +-- interest_rate,--,float,The interest rate for investment in building components +-- annualise_cost,--,"{true, false}",Annualise the investment costs of retrofitting +-- tax_weighting,--,"{true, false}",Weight the costs of retrofitting depending on taxes in countries +-- construction_index,--,"{true, false}",Weight the costs of retrofitting depending on labour/material costs per country +tes,--,"{true, false}",Add option for storing thermal energy in large water pits associated with district heating systems and individual thermal energy storage (TES) +tes_tau,,,The time constant used to calculate the decay of thermal energy in thermal energy storage (TES): 1- :math:`e^{-1/24τ}`. +-- decentral,days,float,The time constant in decentralized thermal energy storage (TES) +-- central,days,float,The time constant in centralized thermal energy storage (TES) +boilers,--,"{true, false}",Add option for transforming electricity into heat using resistive heater +oil_boilers,--,"{true, false}",Add option for transforming oil into heat using boilers +biomass_boiler,--,"{true, false}",Add option for transforming biomass into heat using boilers +chp,--,"{true, false}",Add option for using Combined Heat and Power (CHP) +micro_chp,--,"{true, false}",Add option for using Combined Heat and Power (CHP) for decentral areas. +solar_thermal,--,"{true, false}",Add option for using solar thermal to generate heat. +solar_cf_correction,--,float,The correction factor for the value provided by the solar thermal profile calculations +marginal_cost_storage,currency/MWh ,float,The marginal cost of discharging batteries in distributed grids +methanation,--,"{true, false}",Add option for transforming hydrogen and CO2 into methane using methanation. +helmeth,--,"{true, false}",Add option for transforming power into gas using HELMETH (Integrated High-Temperature ELectrolysis and METHanation for Effective Power to Gas Conversion) +coal_cc,--,"{true, false}",Add option for coal CHPs with carbon capture +dac,--,"{true, false}",Add option for Direct Air Capture (DAC) +co2_vent,--,"{true, false}",Add option for vent out CO2 from storages to the atmosphere. +allam_cycle,--,"{true, false}",Add option to include `Allam cycle gas power plants `_ +hydrogen_fuel_cell,--,"{true, false}",Add option to include hydrogen fuel cell for re-electrification. Assuming OCGT technology costs +hydrogen_turbine,--,"{true, false}",Add option to include hydrogen turbine for re-electrification. Assuming OCGT technology costs +SMR,--,"{true, false}",Add option for transforming natural gas into hydrogen and CO2 using Steam Methane Reforming (SMR) +regional_co2 _sequestration_potential,,, +-- enable,--,"{true, false}",Add option for regionally-resolved geological carbon dioxide sequestration potentials based on `CO2StoP `_. +-- attribute,--,string,Name of the attribute for the sequestration potential +-- include_onshore,--,"{true, false}",Add options for including onshore sequestration potentials +-- min_size,Gt ,float,Any sites with lower potential than this value will be excluded +-- max_size,Gt ,float,The maximum sequestration potential for any one site. +-- years_of_storage,years,float,The years until potential exhausted at optimised annual rate +co2_sequestration_potential,MtCO2/a,float,The potential of sequestering CO2 in Europe per year +co2_sequestration_cost,currency/tCO2,float,The cost of sequestering a ton of CO2 +co2_spatial,--,"{true, false}","Add option to spatially resolve carrier representing stored carbon dioxide. This allows for more detailed modelling of CCUTS, e.g. regarding the capturing of industrial process emissions, usage as feedstock for electrofuels, transport of carbon dioxide, and geological sequestration sites." +,,, +co2network,--,"{true, false}",Add option for planning a new carbon dioxide transmission network +,,, +cc_fraction,--,float,The default fraction of CO2 captured with post-combustion capture +hydrogen_underground _storage,--,"{true, false}",Add options for storing hydrogen underground. Storage potential depends regionally. +hydrogen_underground _storage_locations,,"{onshore, nearshore, offshore}","The location where hydrogen underground storage can be located. Onshore, nearshore, offshore means it must be located more than 50 km away from the sea, within 50 km of the sea, or within the sea itself respectively." +,,, +ammonia,--,"{true, false, regional}","Add ammonia as a carrrier. It can be either true (copperplated NH3), false (no NH3 carrier) or ""regional"" (regionalised NH3 without network)" +min_part_load_fischer _tropsch,per unit of p_nom ,float,The minimum unit dispatch (``p_min_pu``) for the Fischer-Tropsch process +min_part_load _methanolisation,per unit of p_nom ,float,The minimum unit dispatch (``p_min_pu``) for the methanolisation process +,,, +use_fischer_tropsch _waste_heat,--,"{true, false}",Add option for using waste heat of Fischer Tropsch in district heating networks +use_fuel_cell_waste_heat,--,"{true, false}",Add option for using waste heat of fuel cells in district heating networks +use_electrolysis_waste _heat,--,"{true, false}",Add option for using waste heat of electrolysis in district heating networks +electricity_distribution _grid,--,"{true, false}",Add a simplified representation of the exchange capacity between transmission and distribution grid level through a link. +electricity_distribution _grid_cost_factor,,,Multiplies the investment cost of the electricity distribution grid +,,, +electricity_grid _connection,--,"{true, false}",Add the cost of electricity grid connection for onshore wind and solar +H2_network,--,"{true, false}",Add option for new hydrogen pipelines +gas_network,--,"{true, false}","Add existing natural gas infrastructure, incl. LNG terminals, production and entry-points. The existing gas network is added with a lossless transport model. A length-weighted `k-edge augmentation algorithm `_ can be run to add new candidate gas pipelines such that all regions of the model can be connected to the gas network. When activated, all the gas demands are regionally disaggregated as well." +H2_retrofit,--,"{true, false}",Add option for retrofiting existing pipelines to transport hydrogen. +H2_retrofit_capacity _per_CH4,--,float,"The ratio for H2 capacity per original CH4 capacity of retrofitted pipelines. The `European Hydrogen Backbone (April, 2020) p.15 `_ 60% of original natural gas capacity could be used in cost-optimal case as H2 capacity." +gas_network_connectivity _upgrade ,--,float,The number of desired edge connectivity (k) in the length-weighted `k-edge augmentation algorithm `_ used for the gas network +gas_distribution_grid,--,"{true, false}",Add a gas distribution grid +gas_distribution_grid _cost_factor,,,Multiplier for the investment cost of the gas distribution grid +,,, +biomass_spatial,--,"{true, false}",Add option for resolving biomass demand regionally +biomass_transport,--,"{true, false}",Add option for transporting solid biomass between nodes +conventional_generation,,,Add a more detailed description of conventional carriers. Any power generation requires the consumption of fuel from nodes representing that fuel. +biomass_to_liquid,--,"{true, false}",Add option for transforming solid biomass into liquid fuel with the same properties as oil +biosng,--,"{true, false}",Add option for transforming solid biomass into synthesis gas with the same properties as natural gas diff --git a/doc/configtables/solar-thermal.csv b/doc/configtables/solar-thermal.csv new file mode 100644 index 000000000..4575ae0d4 --- /dev/null +++ b/doc/configtables/solar-thermal.csv @@ -0,0 +1,6 @@ +,Unit,Values,Description +clearsky_model ,--,"{‘simple’, ‘enhanced’}",Type of clearsky model for diffuse irradiation +orientation ,--,"{units of degrees, ‘latitude_optimal’}",Panel orientation with slope and azimuth +-- azimuth,float,units of degrees,The angle between the North and the sun with panels on the local horizon + +-- slope,float,units of degrees,The angle between the ground and the panels diff --git a/doc/configtables/solving.csv b/doc/configtables/solving.csv index d30029f4e..c252ff328 100644 --- a/doc/configtables/solving.csv +++ b/doc/configtables/solving.csv @@ -1,7 +1,7 @@ ,Unit,Values,Description options,,, --- formulation,--,"Any of {'angles', 'kirchhoff', 'cycles', 'ptdf'}","Specifies which variant of linearized power flow formulations to use in the optimisation problem. Recommended is 'kirchhoff'. Explained in `this article `_." --- load_shedding,bool,"{'true','false'}","Add generators with a prohibitively high marginal cost to simulate load shedding and avoid problem infeasibilities." +-- load_shedding,bool/float,"{'true','false', float}","Add generators with very high marginal cost to simulate load shedding and avoid problem infeasibilities. If load shedding is a float, it denotes the marginal cost in EUR/kWh." +-- transmission_losses,int,"[0-9]","Add piecewise linear approximation of transmission losses based on n tangents. Defaults to 0, which means losses are ignored." -- noisy_costs,bool,"{'true','false'}","Add random noise to marginal cost of generators by :math:`\mathcal{U}(0.009,0,011)` and capital cost of lines and links by :math:`\mathcal{U}(0.09,0,11)`." -- min_iterations,--,int,"Minimum number of solving iterations in between which resistance and reactence (``x/r``) are updated for branches according to ``s_nom_opt`` of the previous run." -- max_iterations,--,int,"Maximum number of solving iterations in between which resistance and reactence (``x/r``) are updated for branches according to ``s_nom_opt`` of the previous run." diff --git a/doc/configtables/toplevel.csv b/doc/configtables/toplevel.csv index 8a4b443c2..dcf0f29a3 100644 --- a/doc/configtables/toplevel.csv +++ b/doc/configtables/toplevel.csv @@ -4,7 +4,3 @@ tutorial,bool,"{true, false}","Switch to retrieve the tutorial data set instead logging,,, -- level,--,"Any of {'INFO', 'WARNING', 'ERROR'}","Restrict console outputs to all infos, warning or errors only" -- format,--,"","Custom format for log messages. See `LogRecord `_ attributes." -foresight,string,"{overnight, myopic, perfect}","Defaults to overnight scenarios." -countries,--,"Subset of {'AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK'}","European countries defined by their `Two-letter country codes (ISO 3166-1) `_ which should be included in the energy system model." -focus_weights,--,"Keys should be two-digit country codes (e.g. DE) and values should range between 0 and 1","Ratio of total clusters for particular countries. the remaining weight is distributed according to mean load. An example: ``focus_weights: 'DE': 0.6 'FR': 0.2``." -co2_budget,--,"Dictionary with planning horizons as keys.","CO2 budget as a fraction of 1990 emissions. Overwritten if ``CO2Lx`` or ``cb`` are set in ``{sector_opts}`` wildcard" diff --git a/doc/configuration.rst b/doc/configuration.rst index ea8c81aa3..8f15faa70 100644 --- a/doc/configuration.rst +++ b/doc/configuration.rst @@ -9,24 +9,25 @@ Configuration ########################################## -PyPSA-Eur has several configuration options which are documented in this section and are collected in a ``config.yaml`` file located in the root directory. Users should copy the provided default configuration (``config.default.yaml``) and amend their own modifications and assumptions in the user-specific configuration file (``config.yaml``); confer installation instructions at :ref:`defaultconfig`. +PyPSA-Eur has several configuration options which are documented in this section and are collected in a ``config/config.yaml`` file located in the root directory. Users should copy the provided default configuration (``config/config.default.yaml``) and amend their own modifications and assumptions in the user-specific configuration file (``config/config.yaml``); confer installation instructions at :ref:`defaultconfig`. .. _toplevel_cf: Top-level configuration ======================= -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml - :lines: 5-11,18-19,62,80-90 + :start-at: version: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/toplevel.csv -.. _scenario: +.. _run_cf: ``run`` ======= @@ -37,16 +38,37 @@ investment changes as more ambitious greenhouse-gas emission reduction targets a The ``run`` section is used for running and storing scenarios with different configurations which are not covered by :ref:`wildcards`. It determines the path at which resources, networks and results are stored. Therefore the user can run different configurations within the same directory. If a run with a non-empty name should use cutouts shared across runs, set ``shared_cutouts`` to `true`. -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: run: - :end-before: foresight: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/run.csv +.. _foresight_cf: + +``foresight`` +============= + +.. literalinclude:: ../config/config.default.yaml + :language: yaml + :start-at: foresight: + :end-at: foresight: + +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/foresight.csv + +.. note:: + If you use myopic or perfect foresight, the planning horizon in + :ref:`planning_horizons` in scenario has to be set. + +.. _scenario: + ``scenario`` ============ @@ -76,16 +98,31 @@ An exemplary dependency graph (starting from the simplification rules) then look .. image:: img/scenarios.png -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: scenario: - :end-before: countries: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/scenario.csv +.. _countries: + +``countries`` +============= + +.. literalinclude:: ../config/config.default.yaml + :language: yaml + :start-at: countries: + :end-before: # docs + +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/countries.csv + .. _snapshots_cf: ``snapshots`` @@ -93,14 +130,14 @@ An exemplary dependency graph (starting from the simplification rules) then look Specifies the temporal range to build an energy system model for as arguments to `pandas.date_range `_ -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: snapshots: - :end-before: enable: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/snapshots.csv .. _enable_cf: @@ -110,29 +147,48 @@ Specifies the temporal range to build an energy system model for as arguments to Switches for some rules and optional features. -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: enable: - :end-before: co2_budget: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/enable.csv +.. _CO2_budget_cf: + +``co2 budget`` +============== + +.. literalinclude:: ../config/config.default.yaml + :language: yaml + :start-at: co2_budget: + :end-before: # docs + +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/co2_budget.csv + +.. note:: + this parameter is over-ridden if ``CO2Lx`` or ``cb`` is set in + sector_opts. + .. _electricity_cf: ``electricity`` =============== -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: electricity: - :end-before: atlite: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/electricity.csv .. _atlite_cf: @@ -142,14 +198,14 @@ Switches for some rules and optional features. Define and specify the ``atlite.Cutout`` used for calculating renewable potentials and time-series. All options except for ``features`` are directly used as `cutout parameters `_. -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: atlite: - :end-before: renewable: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/atlite.csv .. _renewable_cf: @@ -160,66 +216,98 @@ Define and specify the ``atlite.Cutout`` used for calculating renewable potentia ``onwind`` ---------- -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: renewable: :end-before: offwind-ac: .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/onwind.csv +.. note:: + Notes on ``capacity_per_sqkm``. ScholzPhd Tab 4.3.1: 10MW/km^2 and assuming 30% fraction of the already restricted + area is available for installation of wind generators due to competing land use and likely public + acceptance issues. + +.. note:: + The default choice for corine ``grid_codes`` was based on Scholz, Y. (2012). Renewable energy based electricity supply at low costs + development of the REMix model and application for Europe. ( p.42 / p.28) + ``offwind-ac`` -------------- -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: offwind-ac: :end-before: offwind-dc: .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/offwind-ac.csv +.. note:: + Notes on ``capacity_per_sqkm``. ScholzPhd Tab 4.3.1: 10MW/km^2 and assuming 20% fraction of the already restricted + area is available for installation of wind generators due to competing land use and likely public + acceptance issues. + +.. note:: + Notes on ``correction_factor``. Correction due to proxy for wake losses + from 10.1016/j.energy.2018.08.153 + until done more rigorously in #153 + ``offwind-dc`` --------------- -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: offwind-dc: :end-before: solar: .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/offwind-dc.csv +.. note:: + both ``offwind-ac`` and ``offwind-dc`` have the same assumption on + ``capacity_per_sqkm`` and ``correction_factor``. + ``solar`` --------------- -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: solar: :end-before: hydro: .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/solar.csv +.. note:: + Notes on ``capacity_per_sqkm``. ScholzPhd Tab 4.3.1: 170 MW/km^2 and assuming 1% of the area can be used for solar PV panels. + Correction factor determined by comparing uncorrected area-weighted full-load hours to those + published in Supplementary Data to Pietzcker, Robert Carl, et al. "Using the sun to decarbonize the power + sector -- The economic potential of photovoltaics and concentrating solar + power." Applied Energy 135 (2014): 704-720. + This correction factor of 0.854337 may be in order if using reanalysis data. + for discussion refer to this + ``hydro`` --------------- -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: hydro: - :end-before: conventional: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/hydro.csv .. _lines_cf: @@ -234,27 +322,27 @@ with country specific values. Then, the values are read in and applied to all generators of the given carrier in the given country. Note that the value(s) overwrite the existing values. -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: conventional: - :end-before: lines: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/conventional.csv ``lines`` ============= -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: lines: - :end-before: links: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/lines.csv .. _links_cf: @@ -262,14 +350,14 @@ overwrite the existing values. ``links`` ============= -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: links: - :end-before: transformers: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/links.csv .. _transformers_cf: @@ -277,14 +365,14 @@ overwrite the existing values. ``transformers`` ================ -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: transformers: - :end-before: load: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/transformers.csv .. _load_cf: @@ -292,48 +380,16 @@ overwrite the existing values. ``load`` ============= -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-after: type: - :end-at: scaling_factor: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/load.csv -.. _costs_cf: - -``costs`` -============= - -.. literalinclude:: ../config.default.yaml - :language: yaml - :start-at: costs: - :end-before: clustering: - -.. csv-table:: - :header-rows: 1 - :widths: 25,7,22,30 - :file: configtables/costs.csv - - -.. _clustering_cf: - -``clustering`` -============== - -.. literalinclude:: ../config.default.yaml - :language: yaml - :start-at: clustering: - :end-before: solving: - -.. csv-table:: - :header-rows: 1 - :widths: 25,7,22,30 - :file: configtables/clustering.csv - - .. _energy_cf: ``energy`` @@ -342,14 +398,15 @@ overwrite the existing values. .. note:: Only used for sector-coupling studies. -.. warning:: - More comprehensive documentation for this segment will be released soon. - -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: energy: - :end-before: biomass: + :end-before: # docs +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/energy.csv .. _biomass_cf: @@ -359,13 +416,35 @@ overwrite the existing values. .. note:: Only used for sector-coupling studies. -.. warning:: - More comprehensive documentation for this segment will be released soon. - -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: biomass: - :end-before: solar_thermal: + :end-before: # docs + +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/biomass.csv + +The list of available biomass is given by the category in `ENSPRESO_BIOMASS `_, namely: + +- Agricultural waste +- Manure solid, liquid +- Residues from landscape care +- Bioethanol barley, wheat, grain maize, oats, other cereals and rye +- Sugar from sugar beet +- Miscanthus, switchgrass, RCG +- Willow +- Poplar +- Sunflower, soya seed +- Rape seed +- Fuelwood residues +- FuelwoodRW +- C&P_RW +- Secondary Forestry residues - woodchips +- Sawdust +- Municipal waste +- Sludge .. _solar_thermal_cf: @@ -375,13 +454,15 @@ overwrite the existing values. .. note:: Only used for sector-coupling studies. -.. warning:: - More comprehensive documentation for this segment will be released soon. - -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: solar_thermal: - :end-before: existing_capacities: + :end-before: # docs + +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/solar-thermal.csv .. _existing_capacities_cf: @@ -389,15 +470,17 @@ overwrite the existing values. ======================= .. note:: - Only used for sector-coupling studies. + Only used for sector-coupling studies. The value for grouping years are only used in myopic or perfect foresight scenarios. -.. warning:: - More comprehensive documentation for this segment will be released soon. - -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: existing_capacities: - :end-before: sector: + :end-before: # docs + +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/existing_capacities.csv .. _sector_cf: @@ -407,13 +490,15 @@ overwrite the existing values. .. note:: Only used for sector-coupling studies. -.. warning:: - More comprehensive documentation for this segment will be released soon. - -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: sector: - :end-before: industry: + :end-before: # docs + +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/sector.csv .. _industry_cf: @@ -423,32 +508,71 @@ overwrite the existing values. .. note:: Only used for sector-coupling studies. -.. warning:: - More comprehensive documentation for this segment will be released soon. - -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: industry: - :end-before: costs: + :end-before: # docs -.. _solving_cf: +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/industry.csv -``solving`` +.. _costs_cf: + +``costs`` ============= -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml - :start-at: solving: - :end-before: plotting: + :start-at: costs: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 - :file: configtables/solving.csv + :widths: 22,7,22,33 + :file: configtables/costs.csv + +.. note:: + ``rooftop_share:`` are based on the potentials, assuming + (0.1 kW/m2 and 10 m2/person) + +.. _clustering_cf: + +``clustering`` +============== + +.. literalinclude:: ../config/config.default.yaml + :language: yaml + :start-at: clustering: + :end-before: # docs + +.. csv-table:: + :header-rows: 1 + :widths: 22,7,22,33 + :file: configtables/clustering.csv + +.. note:: + ``feature:`` in ``simplify_network:`` + are only relevant if ``hac`` were chosen in ``algorithm``. + +.. tip:: + use ``min`` in ``p_nom_max:`` for more ` + conservative assumptions. + +.. _solving_cf: + +``solving`` +============= + +.. literalinclude:: ../config/config.default.yaml + :language: yaml + :start-at: solving: + :end-before: # docs .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/solving.csv .. _plotting_cf: @@ -459,11 +583,11 @@ overwrite the existing values. .. warning:: More comprehensive documentation for this segment will be released soon. -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: plotting: .. csv-table:: :header-rows: 1 - :widths: 25,7,22,30 + :widths: 22,7,22,33 :file: configtables/plotting.csv diff --git a/doc/costs.rst b/doc/costs.rst index 46b93482c..5ddbb3603 100644 --- a/doc/costs.rst +++ b/doc/costs.rst @@ -9,10 +9,10 @@ Techno-Economic Assumptions The database of cost assumptions is retrieved from the repository `PyPSA/technology-data `_ and then -saved to a file ``data/costs_{year}.csv``. The ``config.yaml`` provides options +saved to a file ``data/costs_{year}.csv``. The ``config/config.yaml`` provides options to choose a reference year and use a specific version of the repository. -.. literalinclude:: ../config.default.yaml +.. literalinclude:: ../config/config.default.yaml :language: yaml :start-at: costs: :end-at: version: @@ -48,7 +48,7 @@ Modifying Assumptions ===================== Some cost assumptions (e.g. marginal cost and capital cost) can be directly -set in the ``config.yaml`` (cf. Section :ref:`costs_cf` in +set in the ``config/config.yaml`` (cf. Section :ref:`costs_cf` in :ref:`config`). To change cost assumptions in more detail, make a copy of ``data/costs_{year}.csv`` and reference the new cost file in the ``Snakefile``: diff --git a/doc/foresight.rst b/doc/foresight.rst index f1ae2b38c..c1be34436 100644 --- a/doc/foresight.rst +++ b/doc/foresight.rst @@ -28,7 +28,7 @@ It does not affect the year for cost and technology assumptions, which is set se costs: year: 2030 -For running overnight scenarios, use in the ``config.yaml``: +For running overnight scenarios, use in the ``config/config.yaml``: .. code:: yaml @@ -44,7 +44,7 @@ Perfect foresight scenarios Perfect foresight is currently under development and not yet implemented. For running perfect foresight scenarios, in future versions you will be able to -set in the ``config.yaml``: +set in the ``config/config.yaml``: .. code:: yaml @@ -87,20 +87,24 @@ evolve with the myopic approach: vehicle-to-grid services. - The annual biomass potential (default year and scenario for which potential is - taken is 2030, defined `here - `_) + taken is 2030, as defined in config) + +.. literalinclude:: ../config/test/config.myopic.yaml + :language: yaml + :start-at: biomass: + :end-at: year: Configuration -------------- -For running myopic foresight transition scenarios, set in ``config.yaml``: +For running myopic foresight transition scenarios, set in ``config/config.yaml``: .. code:: yaml foresight: myopic -The following options included in the config.yaml file are relevant for the +The following options included in the ``config/config.yaml`` file are relevant for the myopic code. The ``{planning_horizons}`` wildcard indicates the year in which the network is @@ -108,7 +112,7 @@ optimized. For a myopic optimization, this is equivalent to the investment year. To set the investment years which are sequentially simulated for the myopic investment planning, select for example: -.. literalinclude:: ../test/config.myopic.yaml +.. literalinclude:: ../config/test/config.myopic.yaml :language: yaml :start-at: planning_horizons: :end-before: countries: @@ -163,7 +167,7 @@ Options The total carbon budget for the entire transition path can be indicated in the `sector_opts `_ -in ``config.yaml``. The carbon budget can be split among the +in ``config/config.yaml``. The carbon budget can be split among the ``planning_horizons`` following an exponential or beta decay. E.g. ``'cb40ex0'`` splits a carbon budget equal to 40 Gt :math:`_{CO_2}` following an exponential decay whose initial linear growth rate r is zero. They can also follow some @@ -203,6 +207,7 @@ The myopic code solves the network for the time steps included in network comprises additional generator, storage, and link capacities with p_nom_extendable=True. The non-solved network is saved in ``results/run_name/networks/prenetworks-brownfield``. + The base year is the first element in ``planning_horizons``. Step 1 is implemented with the rule add_baseyear for the base year and with the rule add_brownfield for the remaining planning_horizons. @@ -218,7 +223,7 @@ add_brownfield for the remaining planning_horizons. ``results/run_name/networks/prenetworks-brownfield``. Steps 2 and 3 are solved recursively for all the planning_horizons included in -``config.yaml``. +``config/config.yaml``. Rule overview -------------- diff --git a/doc/index.rst b/doc/index.rst index 521f080b1..c5d92e874 100644 --- a/doc/index.rst +++ b/doc/index.rst @@ -31,7 +31,9 @@ PyPSA-Eur: A Sector-Coupled Open Optimisation Model of the European Energy Syste :target: https://api.reuse.software/info/github.com/pypsa/pypsa-eur :alt: REUSE -| +.. image:: https://img.shields.io/stackexchange/stackoverflow/t/pypsa + :target: https://stackoverflow.com/questions/tagged/pypsa + :alt: Stackoverflow PyPSA-Eur is an open model dataset of the European energy system at the transmission network level that covers the full ENTSO-E area. It covers demand @@ -76,10 +78,10 @@ them: .. note:: You can find showcases of the model's capabilities in the Supplementary Materials of the - preprint `Benefits of a Hydrogen Network in Europe - `_, the Supplementary Materials of the `paper in Joule with a + Joule paper `The potential role of a hydrogen network in Europe + `_, the Supplementary Materials of another `paper in Joule with a description of the industry sector - `_, or in `a 2021 presentation + `_, or in `a 2021 presentation at EMP-E `_. The sector-coupled extension of PyPSA-Eur was initially described in the paper `Synergies of sector coupling and transmission @@ -177,10 +179,13 @@ For sector-coupling studies: :: @misc{PyPSAEurSec, author = "Fabian Neumann and Elisabeth Zeyen and Marta Victoria and Tom Brown", - title = "The Potential Role of a Hydrogen Network in Europe", - year = "2022", + title = "The potential role of a hydrogen network in Europe", + journal "Joule", + volume = "7", + pages = "1--25" + year = "2023", eprint = "2207.05816", - url = "https://arxiv.org/abs/2207.05816", + doi = "10.1016/j.joule.2022.04.016", } For sector-coupling studies with pathway optimisation: :: @@ -222,7 +227,10 @@ The included ``.nc`` files are PyPSA network files which can be imported with Py n = pypsa.Network(filename) +Operating Systems +================= +The PyPSA-Eur workflow is continuously tested for Linux, macOS and Windows (WSL only). .. toctree:: @@ -274,4 +282,5 @@ The included ``.nc`` files are PyPSA network files which can be imported with Py licenses limitations contributing + support publications diff --git a/doc/installation.rst b/doc/installation.rst index ed67f27da..01fdafebd 100644 --- a/doc/installation.rst +++ b/doc/installation.rst @@ -39,7 +39,7 @@ The environment can be installed and activated using .. code:: bash - .../pypsa-eur % mamba create -f envs/environment.yaml + .../pypsa-eur % mamba env create -f envs/environment.yaml .../pypsa-eur % mamba activate pypsa-eur @@ -119,19 +119,19 @@ Handling Configuration Files ============================ PyPSA-Eur has several configuration options that must be specified in a -``config.yaml`` file located in the root directory. An example configuration -``config.default.yaml`` is maintained in the repository, which will be used to -automatically create your customisable ``config.yaml`` on first use. More +``config/config.yaml`` file located in the root directory. An example configuration +``config/config.default.yaml`` is maintained in the repository, which will be used to +automatically create your customisable ``config/config.yaml`` on first use. More details on the configuration options are in :ref:`config`. You can also use ``snakemake`` to specify another file, e.g. -``config.mymodifications.yaml``, to update the settings of the ``config.yaml``. +``config/config.mymodifications.yaml``, to update the settings of the ``config/config.yaml``. .. code:: bash - .../pypsa-eur % snakemake -call --configfile config.mymodifications.yaml + .../pypsa-eur % snakemake -call --configfile config/config.mymodifications.yaml .. warning:: - Users are advised to regularly check their own ``config.yaml`` against changes - in the ``config.default.yaml`` when pulling a new version from the remote + Users are advised to regularly check their own ``config/config.yaml`` against changes + in the ``config/config.default.yaml`` when pulling a new version from the remote repository. diff --git a/doc/introduction.rst b/doc/introduction.rst index 0ae038aac..df0607232 100644 --- a/doc/introduction.rst +++ b/doc/introduction.rst @@ -74,7 +74,7 @@ what data to retrieve and what files to produce. Details are explained in :ref:`wildcards` and :ref:`scenario`. The model also has several further configuration options collected in the -``config.yaml`` file located in the root directory, which that are not part of +``config/config.yaml`` file located in the root directory, which that are not part of the scenarios. Options are explained in :ref:`config`. Folder Structure diff --git a/doc/preparation.rst b/doc/preparation.rst index a180bb0d6..5cdc80316 100644 --- a/doc/preparation.rst +++ b/doc/preparation.rst @@ -86,13 +86,13 @@ Rule ``build_powerplants`` .. automodule:: build_powerplants -.. _load_data: +.. _electricity_demand: -Rule ``build_load_data`` -============================= +Rule ``build_electricity_demand`` +================================== -.. automodule:: build_load_data +.. automodule:: build_electricity_demand .. _ship: diff --git a/doc/release_notes.rst b/doc/release_notes.rst index 426ab9eff..defe1dc4c 100644 --- a/doc/release_notes.rst +++ b/doc/release_notes.rst @@ -7,10 +7,130 @@ Release Notes ########################################## -Upcoming Release -================ +.. Upcoming Release +.. ================ -* new feature or bugfix +PyPSA-Eur 0.8.1 (27th July 2023) +================================ + +**New Features** + +* Add option to consider dynamic line rating based on wind speeds and + temperature according to `Glaum and Hofmann (2022) + `_. See configuration section ``lines: + dynamic_line_rating:`` for more details. (https://github.com/PyPSA/pypsa-eur/pull/675) + +* Add option to include a piecewise linear approximation of transmission losses, + e.g. by setting ``solving: options: transmission_losses: 2`` for an + approximation with two tangents. (https://github.com/PyPSA/pypsa-eur/pull/664) + +* Add plain hydrogen turbine as additional re-electrification option besides + hydrogen fuel cell. Add switches for both re-electrification options under + ``sector: hydrogen_turbine:`` and ``sector: hydrogen_fuel_cell:``. + (https://github.com/PyPSA/pypsa-eur/pull/647) + +* Added configuration option ``lines: max_extension:`` and ``links: + max_extension:``` to control the maximum capacity addition per line or link in + MW. (https://github.com/PyPSA/pypsa-eur/pull/665) + +* A ``param:`` section in the snakemake rule definitions was added to track + changed settings in ``config.yaml``. The goal is to automatically re-execute + rules where parameters have changed. See `Non-file parameters for rules + `_ + in the snakemake documentation. (https://github.com/PyPSA/pypsa-eur/pull/663) + +* A new function named ``sanitize_carrier`` ensures that all unique carrier + names are present in the network's carriers attribute, and adds nice names and + colors for each carrier according to the provided configuration dictionary. + (https://github.com/PyPSA/pypsa-eur/pull/653, + https://github.com/PyPSA/pypsa-eur/pull/690) + +* The configuration settings have been documented in more detail. + (https://github.com/PyPSA/pypsa-eur/pull/685) + +**Breaking Changes** + +* The configuration files are now located in the ``config`` directory. This + includes the ``config.default.yaml``, ``config.yaml`` as well as the test + configuration files which are now located in the ``config/test`` directory. + Config files that are still in the root directory will be ignored. + (https://github.com/PyPSA/pypsa-eur/pull/640) + +* Renamed script and rule name from ``build_load_data`` to + ``build_electricity_demand`` and ``retrieve_load_data`` to + ``retrieve_electricity_demand``. (https://github.com/PyPSA/pypsa-eur/pull/642, + https://github.com/PyPSA/pypsa-eur/pull/652) + +* Updated to new spatial clustering module introduced in PyPSA v0.25. + (https://github.com/PyPSA/pypsa-eur/pull/696) + +**Changes** + +* Handling networks with links with multiple inputs/outputs no longer requires + to override component attributes. + (https://github.com/PyPSA/pypsa-eur/pull/695) + +* Added configuration option ``enable: retrieve:`` to control whether data + retrieval rules from snakemake are enabled or not. Th default setting ``auto`` + will automatically detect and enable/disable the rules based on internet + connectivity. (https://github.com/PyPSA/pypsa-eur/pull/694) + +* Update to ``technology-data`` v0.6.0. + (https://github.com/PyPSA/pypsa-eur/pull/704) + +* Handle data bundle extraction paths via ``snakemake.output``. + +* Additional technologies are added to ``tech_color`` in the configuration files + to include previously unlisted carriers. + +* Doc: Added note that Windows is only tested in CI with WSL. + (https://github.com/PyPSA/pypsa-eur/issues/697) + +* Doc: Add support section. (https://github.com/PyPSA/pypsa-eur/pull/656) + +* Open ``rasterio`` files with ``rioxarray``. + (https://github.com/PyPSA/pypsa-eur/pull/474) + +* Migrate CI to ``micromamba``. (https://github.com/PyPSA/pypsa-eur/pull/700) + +**Bugs and Compatibility** + +* The new minimum PyPSA version is v0.25.1. + +* Removed ``vresutils`` dependency. + (https://github.com/PyPSA/pypsa-eur/pull/662) + +* Adapt to new ``powerplantmatching`` version. + (https://github.com/PyPSA/pypsa-eur/pull/687, + https://github.com/PyPSA/pypsa-eur/pull/701) + +* Bugfix: Correct typo in the CPLEX solver configuration in + ``config.default.yaml``. (https://github.com/PyPSA/pypsa-eur/pull/630) + +* Bugfix: Error in ``add_electricity`` where carriers were added multiple times + to the network, resulting in a non-unique carriers error. + +* Bugfix of optional reserve constraint. + (https://github.com/PyPSA/pypsa-eur/pull/645) + +* Fix broken equity constraints logic. + (https://github.com/PyPSA/pypsa-eur/pull/679) + +* Fix addition of load shedding generators. + (https://github.com/PyPSA/pypsa-eur/pull/649) + +* Fix automatic building of documentation on readthedocs.org. + (https://github.com/PyPSA/pypsa-eur/pull/658) + +* Bugfix: Update network clustering to avoid adding deleted links in clustered + network. (https://github.com/PyPSA/pypsa-eur/pull/678) + +* Address ``geopandas`` deprecations. + (https://github.com/PyPSA/pypsa-eur/pull/678) + +* Fix bug with underground hydrogen storage creation, where for some small model + regions no cavern storage is available. + (https://github.com/PyPSA/pypsa-eur/pull/672) PyPSA-Eur 0.8.0 (18th March 2023) @@ -338,7 +458,7 @@ PyPSA-Eur 0.5.0 (27th July 2022) * Network building is made deterministic by supplying a fixed random state to network clustering routines. -* Clustering strategies for generator and bus attributes can now be specified directly in the ``config.yaml``. +* Clustering strategies for generator and bus attributes can now be specified directly in the ``config/config.yaml``. * Iterative solving with impedance updates is skipped if there are no expandable lines. @@ -559,7 +679,7 @@ More OPSD integration: This will overwrite the capacities calculated from the heuristic approach in :func:`estimate_renewable_capacities()` [`#212 `_]. -* Electricity consumption data is now retrieved directly from the `OPSD website `_ using the rule :mod:`build_load_data`. +* Electricity consumption data is now retrieved directly from the `OPSD website `_ using the rule :mod:`build_electricity_demand`. The user can decide whether to take the ENTSO-E power statistics data (default) or the ENTSO-E transparency data [`#211 `_]. diff --git a/doc/requirements.txt b/doc/requirements.txt index d5c71da91..3e760c81f 100644 --- a/doc/requirements.txt +++ b/doc/requirements.txt @@ -2,12 +2,13 @@ # # SPDX-License-Identifier: CC0-1.0 +setuptools sphinx sphinx_book_theme sphinxcontrib-bibtex +myst-parser # recommark is deprecated, https://stackoverflow.com/a/71660856/13573820 pypsa -vresutils>=0.3.1 powerplantmatching>=0.5.5 atlite>=0.2.9 dask[distributed] diff --git a/doc/retrieve.rst b/doc/retrieve.rst index c06b330fe..cc93c3d98 100644 --- a/doc/retrieve.rst +++ b/doc/retrieve.rst @@ -42,7 +42,7 @@ The :ref:`tutorial` uses a smaller cutout than required for the full model (30 M build_cutout: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`toplevel_cf` **Outputs** @@ -69,7 +69,7 @@ This rule, as a substitute for :mod:`build_natura_raster`, downloads an already build_natura_raster: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`toplevel_cf` **Outputs** @@ -80,8 +80,8 @@ This rule, as a substitute for :mod:`build_natura_raster`, downloads an already For details see :mod:`build_natura_raster`. -Rule ``retrieve_load_data`` -================================ +Rule ``retrieve_electricity_demand`` +==================================== This rule downloads hourly electric load data for each country from the `OPSD platform `_. @@ -111,7 +111,7 @@ This rule downloads techno-economic assumptions from the `technology-data reposi version: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`costs_cf` **Outputs** diff --git a/doc/spatial_resolution.rst b/doc/spatial_resolution.rst index bbe5da056..0293a5cef 100644 --- a/doc/spatial_resolution.rst +++ b/doc/spatial_resolution.rst @@ -11,7 +11,7 @@ Spatial resolution The default nodal resolution of the model follows the electricity generation and transmission model `PyPSA-Eur `_, which clusters down the electricity transmission substations in each European country based on the k-means algorithm (See `cluster_network `_ for a complete explanation). This gives nodes which correspond to major load and generation centres (typically cities). -The total number of nodes for Europe is set in the ``config.yaml`` file under ``clusters``. The number of nodes can vary between 37, the number of independent countries / synchronous areas, and several hundred. With 200-300 nodes the model needs 100-150 GB RAM to solve with a commercial solver like Gurobi. +The total number of nodes for Europe is set in the ``config/config.yaml`` file under ``clusters``. The number of nodes can vary between 37, the number of independent countries / synchronous areas, and several hundred. With 200-300 nodes the model needs 100-150 GB RAM to solve with a commercial solver like Gurobi. Exemplary unsolved network clustered to 512 nodes: @@ -21,7 +21,7 @@ Exemplary unsolved network clustered to 37 nodes: .. image:: ../graphics/elec_s_37.png -The total number of nodes for Europe is set in the config.yaml file under `clusters `_. The number of nodes can vary between 37, the number of independent countries/synchronous areas, and several hundred. With 200-300 nodes, the model needs 100-150 GB RAM to solve with a commercial solver like Gurobi. +The total number of nodes for Europe is set in the ``config/config.yaml`` file under `clusters `_. The number of nodes can vary between 37, the number of independent countries/synchronous areas, and several hundred. With 200-300 nodes, the model needs 100-150 GB RAM to solve with a commercial solver like Gurobi. Not all of the sectors are at the full nodal resolution, and some demand for some sectors is distributed to nodes using heuristics that need to be corrected. Some networks are copper-plated to reduce computational times. Here are some examples of how spatial resolution is set for different sectors in PyPSA-Eur-Sec: diff --git a/doc/supply_demand.rst b/doc/supply_demand.rst index ed35bc387..b043268b1 100644 --- a/doc/supply_demand.rst +++ b/doc/supply_demand.rst @@ -133,12 +133,12 @@ The coefficient of performance (COP) of air- and ground-sourced heat pumps depen For the sink water temperature Tsink we assume 55 °C [`Config `_ file]. For the time- and location-dependent source temperatures Tsource, we rely on the `ERA5 `_ reanalysis weather data. The temperature differences are converted into COP time series using results from a regression analysis performed in the study by `Stafell et al. `_. For air-sourced heat pumps (ASHP), we use the function: .. math:: - COP (\Delta T) = 6.81 + 0.121\Delta T + 0.000630\Delta T^2 + COP (\Delta T) = 6.81 - 0.121\Delta T + 0.000630\Delta T^2 for ground-sourced heat pumps (GSHP), we use the function: .. math:: - COP(\Delta T) = 8.77 + 0.150\Delta T + 0.000734\Delta T^2 + COP(\Delta T) = 8.77 - 0.150\Delta T + 0.000734\Delta T^2 **Resistive heaters** @@ -189,7 +189,7 @@ higher costs and higher efficiency gains. They are added by step-wise linearisation in form of two additional generations in the `prepare_sector_network.py `_ script. -Settings in the config.yaml concerning the endogenously optimisation of building +Settings in the ``config/config.yaml`` concerning the endogenously optimisation of building renovation include `cost factor `_, `interest rate `_, `annualised cost `_, `tax weighting `_, and `construction index `_. Further information are given in the study by Zeyen et al. : `Mitigating heat demand peaks in buildings in a highly renewable European energy system, (2021) `_. diff --git a/doc/support.rst b/doc/support.rst new file mode 100644 index 000000000..1d512d594 --- /dev/null +++ b/doc/support.rst @@ -0,0 +1,14 @@ +.. + SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors + + SPDX-License-Identifier: CC-BY-4.0 + +####################### +Support +####################### + +* In case of code-related **questions**, please post on `stack overflow `_. +* For non-programming related and more general questions please refer to the `mailing list `_. +* To **discuss** with other PyPSA users, organise projects, share news, and get in touch with the community you can use the `discord server `_. +* For **bugs and feature requests**, please use the `issue tracker `_. +* We strongly welcome anyone interested in providing **contributions** to this project. If you have any ideas, suggestions or encounter problems, feel invited to file issues or make pull requests on `Github `_. For further information on how to contribute, please refer to :ref:`contributing`. diff --git a/doc/tutorial.rst b/doc/tutorial.rst index 254b58d60..f0ded3fb0 100644 --- a/doc/tutorial.rst +++ b/doc/tutorial.rst @@ -26,13 +26,13 @@ local machine. The tutorial will cover examples on how to configure and customise the PyPSA-Eur model and run the ``snakemake`` workflow step by step from network creation to the solved network. The configuration for the tutorial is located at ``test/config.electricity.yaml``. It includes parts deviating from -the default config file ``config.default.yaml``. To run the tutorial with this +the default config file ``config/config.default.yaml``. To run the tutorial with this configuration, execute .. code:: bash :class: full-width - snakemake -call --configfile test/config.electricity.yaml results/networks/elec_s_6_ec_lcopt_Co2L-24H.nc + snakemake -call results/test-elec/networks/elec_s_6_ec_lcopt_Co2L-24H.nc --configfile config/test/config.electricity.yaml This configuration is set to download a reduced data set via the rules :mod:`retrieve_databundle`, :mod:`retrieve_natura_raster`, :mod:`retrieve_cutout`. @@ -43,21 +43,21 @@ How to configure runs? The model can be adapted to only include selected countries (e.g. Belgium) instead of all European countries to limit the spatial scope. -.. literalinclude:: ../test/config.electricity.yaml +.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: countries: :end-before: snapshots: Likewise, the example's temporal scope can be restricted (e.g. to a single week). -.. literalinclude:: ../test/config.electricity.yaml +.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: snapshots: :end-before: electricity: It is also possible to allow less or more carbon-dioxide emissions. Here, we limit the emissions of Belgium to 100 Mt per year. -.. literalinclude:: ../test/config.electricity.yaml +.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: electricity: :end-before: extendable_carriers: @@ -65,7 +65,7 @@ It is also possible to allow less or more carbon-dioxide emissions. Here, we lim PyPSA-Eur also includes a database of existing conventional powerplants. We can select which types of existing powerplants we like to be extendable: -.. literalinclude:: ../test/config.electricity.yaml +.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: extendable_carriers: :end-before: renewable_carriers: @@ -74,7 +74,7 @@ To accurately model the temporal and spatial availability of renewables such as wind and solar energy, we rely on historical weather data. It is advisable to adapt the required range of coordinates to the selection of countries. -.. literalinclude:: ../test/config.electricity.yaml +.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: atlite: :end-before: renewable: @@ -83,7 +83,7 @@ We can also decide which weather data source should be used to calculate potentials and capacity factor time-series for each carrier. For example, we may want to use the ERA-5 dataset for solar and not the default SARAH-2 dataset. -.. literalinclude:: ../test/config.electricity.yaml +.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: solar: :end-at: cutout: @@ -91,7 +91,7 @@ want to use the ERA-5 dataset for solar and not the default SARAH-2 dataset. Finally, it is possible to pick a solver. For instance, this tutorial uses the open-source solver GLPK. -.. literalinclude:: ../test/config.electricity.yaml +.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: solver: :end-before: plotting: @@ -115,7 +115,7 @@ clustered down to 6 buses and every 24 hours aggregated to one snapshot. The com .. code:: bash - snakemake -call --configfile test/config.electricity.yaml results/networks/elec_s_6_ec_lcopt_Co2L-24H.nc + snakemake -call results/test-elec/networks/elec_s_6_ec_lcopt_Co2L-24H.nc --configfile config/test/config.electricity.yaml orders ``snakemake`` to run the rule :mod:`solve_network` that produces the solved network and stores it in ``results/networks`` with the name ``elec_s_6_ec_lcopt_Co2L-24H.nc``: @@ -155,8 +155,8 @@ This triggers a workflow of multiple preceding jobs that depend on each rule's i 19[label = "build_hydro_profile", color = "0.44 0.6 0.85", style="rounded"]; 20[label = "retrieve_cost_data", color = "0.30 0.6 0.85", style="rounded"]; 21[label = "build_powerplants", color = "0.16 0.6 0.85", style="rounded"]; - 22[label = "build_load_data", color = "0.00 0.6 0.85", style="rounded"]; - 23[label = "retrieve_load_data", color = "0.34 0.6 0.85", style="rounded,dashed"]; + 22[label = "build_electricity_demand", color = "0.00 0.6 0.85", style="rounded"]; + 23[label = "retrieve_electricity_demand", color = "0.34 0.6 0.85", style="rounded,dashed"]; 1 -> 0 2 -> 1 20 -> 1 @@ -232,7 +232,7 @@ In the terminal, this will show up as a list of jobs to be run: base_network 1 1 1 build_bus_regions 1 1 1 build_hydro_profile 1 1 1 - build_load_data 1 1 1 + build_electricity_demand 1 1 1 build_powerplants 1 1 1 build_renewable_profiles 4 1 1 build_shapes 1 1 1 @@ -276,21 +276,21 @@ You can produce any output file occurring in the ``Snakefile`` by running For example, you can explore the evolution of the PyPSA networks by running -#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/base.nc`` -#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/elec.nc`` -#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/elec_s.nc`` -#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/elec_s_6.nc`` -#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/elec_s_6_ec_lcopt_Co2L-24H.nc`` +#. ``snakemake resources/networks/base.nc -call --configfile config/test/config.electricity.yaml`` +#. ``snakemake resources/networks/elec.nc -call --configfile config/test/config.electricity.yaml`` +#. ``snakemake resources/networks/elec_s.nc -call --configfile config/test/config.electricity.yaml`` +#. ``snakemake resources/networks/elec_s_6.nc -call --configfile config/test/config.electricity.yaml`` +#. ``snakemake resources/networks/elec_s_6_ec_lcopt_Co2L-24H.nc -call --configfile config/test/config.electricity.yaml`` -To run all combinations of wildcard values provided in the ``config.yaml`` under ``scenario:``, +To run all combinations of wildcard values provided in the ``config/config.yaml`` under ``scenario:``, you can use the collection rule ``solve_elec_networks``. .. code:: bash - snakemake -call --configfile test/config.electricity.yaml solve_elec_networks + snakemake -call solve_elec_networks --configfile config/test/config.electricity.yaml If you now feel confident and want to tackle runs with larger temporal and -spatial scope, clean-up the repository and after modifying the ``config.yaml`` file +spatial scope, clean-up the repository and after modifying the ``config/config.yaml`` file target the collection rule ``solve_elec_networks`` again without providing the test configuration file. diff --git a/doc/tutorial_sector.rst b/doc/tutorial_sector.rst index 1d8e8ba57..faa8adca5 100644 --- a/doc/tutorial_sector.rst +++ b/doc/tutorial_sector.rst @@ -29,13 +29,13 @@ Overnight Scenarios Configuration ------------- -The default configuration file (``config.default.yaml``) is set up for running +The default configuration file (``config/config.default.yaml``) is set up for running overnight scenarios. Running a sector-coupled model unlocks many further configuration options. In the example below, we say that the gas network should be added and spatially resolved. We also say that the existing gas network may be retrofitted to transport hydrogen instead. -.. literalinclude:: ../test/config.overnight.yaml +.. literalinclude:: ../config/test/config.overnight.yaml :language: yaml :start-at: sector: :end-before: solving: @@ -45,7 +45,7 @@ Documentation for all options will be added successively to :ref:`config`. Scenarios can be defined like for electricity-only studies, but with additional wildcard options. -.. literalinclude:: ../test/config.overnight.yaml +.. literalinclude:: ../config/test/config.overnight.yaml :language: yaml :start-at: scenario: :end-before: countries: @@ -59,7 +59,7 @@ To run an overnight / greenfiled scenario with the specifications above, run .. code:: bash - snakemake -call --configfile test/config.overnight.yaml all + snakemake -call --configfile config/test/config.overnight.yaml all which will result in the following *additional* jobs ``snakemake`` wants to run on top of those already included in the electricity-only tutorial: @@ -140,8 +140,8 @@ successfully. 18[label = "retrieve_ship_raster", color = "0.15 0.6 0.85", style="rounded"]; 19[label = "retrieve_cost_data", color = "0.50 0.6 0.85", style="rounded"]; 20[label = "build_powerplants", color = "0.49 0.6 0.85", style="rounded"]; - 21[label = "build_load_data", color = "0.39 0.6 0.85", style="rounded"]; - 22[label = "retrieve_load_data", color = "0.05 0.6 0.85", style="rounded"]; + 21[label = "build_electricity_demand", color = "0.39 0.6 0.85", style="rounded"]; + 22[label = "retrieve_electricity_demand", color = "0.05 0.6 0.85", style="rounded"]; 23[label = "build_gas_input_locations", color = "0.45 0.6 0.85", style="rounded"]; 24[label = "prepare_network", color = "0.31 0.6 0.85", style="rounded"]; 25[label = "add_extra_components", color = "0.23 0.6 0.85", style="rounded"]; @@ -294,7 +294,7 @@ Scenarios can be defined like for electricity-only studies, but with additional wildcard options. For the myopic foresight mode, the ``{planning_horizons}`` wildcard defines the sequence of investment horizons. -.. literalinclude:: ../test/config.myopic.yaml +.. literalinclude:: ../config/test/config.myopic.yaml :language: yaml :start-at: scenario: :end-before: countries: @@ -304,7 +304,7 @@ For allowed wildcard values, refer to :ref:`wildcards`. In the myopic foresight mode, you can tweak for instance exogenously given transition paths, like the one for the share of primary steel production we change below: -.. literalinclude:: ../test/config.myopic.yaml +.. literalinclude:: ../config/test/config.myopic.yaml :language: yaml :start-at: industry: :end-before: solving: @@ -318,7 +318,7 @@ To run a myopic foresight scenario with the specifications above, run .. code:: bash - snakemake -call --configfile test/config.myopic.yaml all + snakemake -call --configfile config/test/config.myopic.yaml all which will result in the following *additional* jobs ``snakemake`` wants to run: @@ -367,8 +367,8 @@ implemented in the workflow: 18[label = "retrieve_ship_raster", color = "0.09 0.6 0.85", style="rounded"]; 19[label = "retrieve_cost_data", color = "0.04 0.6 0.85", style="rounded"]; 20[label = "build_powerplants", color = "0.28 0.6 0.85", style="rounded"]; - 21[label = "build_load_data", color = "0.46 0.6 0.85", style="rounded"]; - 22[label = "retrieve_load_data", color = "0.44 0.6 0.85", style="rounded"]; + 21[label = "build_electricity_demand", color = "0.46 0.6 0.85", style="rounded"]; + 22[label = "retrieve_electricity_demand", color = "0.44 0.6 0.85", style="rounded"]; 23[label = "build_energy_totals", color = "0.53 0.6 0.85", style="rounded"]; 24[label = "build_population_weighted_energy_totals", color = "0.03 0.6 0.85", style="rounded"]; 25[label = "build_clustered_population_layouts", color = "0.34 0.6 0.85", style="rounded"]; @@ -513,7 +513,7 @@ Scaling-Up ========== If you now feel confident and want to tackle runs with larger temporal, technological and -spatial scope, clean-up the repository and after modifying the ``config.yaml`` file +spatial scope, clean-up the repository and after modifying the ``config/config.yaml`` file target the collection rule ``all`` again without providing the test configuration file. diff --git a/doc/wildcards.rst b/doc/wildcards.rst index 30c58929d..75eec1922 100644 --- a/doc/wildcards.rst +++ b/doc/wildcards.rst @@ -117,6 +117,23 @@ The ``{sector_opts}`` wildcard .. warning:: More comprehensive documentation for this wildcard will be added soon. + To really understand the options here, look in scripts/prepare_sector_network.py + + # Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%); + # Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions + # xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours + # single letters are sectors: T for land transport, H for building heating, + # B for biomass supply, I for industry, shipping and aviation, + # A for agriculture, forestry and fishing + # solar+c0.5 reduces the capital cost of solar to 50\% of reference value + # solar+p3 multiplies the available installable potential by factor 3 + # seq400 sets the potential of CO2 sequestration to 400 Mt CO2 per year + # dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv + # for myopic/perfect foresight cb states the carbon budget in GtCO2 (cumulative + # emissions throughout the transition path in the timeframe determined by the + # planning_horizons), be:beta decay; ex:exponential decay + # cb40ex0 distributes a carbon budget of 40 GtCO2 following an exponential + # decay with initial growth rate 0 The ``{sector_opts}`` wildcard is only used for sector-coupling studies. diff --git a/envs/environment.fixed.yaml b/envs/environment.fixed.yaml index 516e5ec57..ca2ae848c 100644 --- a/envs/environment.fixed.yaml +++ b/envs/environment.fixed.yaml @@ -12,74 +12,93 @@ dependencies: - _libgcc_mutex=0.1 - _openmp_mutex=4.5 - affine=2.4.0 -- alsa-lib=1.2.8 +- alsa-lib=1.2.9 - ampl-mp=3.1.0 -- amply=0.1.5 +- amply=0.1.6 +- anyio=3.7.1 - appdirs=1.4.4 +- argon2-cffi=21.3.0 +- argon2-cffi-bindings=21.2.0 - asttokens=2.2.1 -- atlite=0.2.10 +- async-lru=2.0.3 +- atk-1.0=2.38.0 +- atlite=0.2.11 - attr=2.5.1 -- attrs=22.2.0 +- attrs=23.1.0 +- aws-c-auth=0.7.0 +- aws-c-cal=0.6.0 +- aws-c-common=0.8.23 +- aws-c-compression=0.2.17 +- aws-c-event-stream=0.3.1 +- aws-c-http=0.7.11 +- aws-c-io=0.13.28 +- aws-c-mqtt=0.8.14 +- aws-c-s3=0.3.13 +- aws-c-sdkutils=0.1.11 +- aws-checksums=0.1.16 +- aws-crt-cpp=0.20.3 +- aws-sdk-cpp=1.10.57 +- babel=2.12.1 - backcall=0.2.0 - backports=1.0 -- backports.functools_lru_cache=1.6.4 -- beautifulsoup4=4.11.2 -- blosc=1.21.3 -- bokeh=2.4.3 +- backports.functools_lru_cache=1.6.5 +- beautifulsoup4=4.12.2 +- bleach=6.0.0 +- blosc=1.21.4 +- bokeh=3.2.1 - boost-cpp=1.78.0 -- bottleneck=1.3.6 +- bottleneck=1.3.7 - branca=0.6.0 - brotli=1.0.9 - brotli-bin=1.0.9 -- brotlipy=0.7.0 +- brotli-python=1.0.9 - bzip2=1.0.8 -- c-ares=1.18.1 -- ca-certificates=2022.12.7 +- c-ares=1.19.1 +- c-blosc2=2.10.0 +- ca-certificates=2023.7.22 - cairo=1.16.0 - cartopy=0.21.1 -- cdsapi=0.5.1 -- certifi=2022.12.7 +- cdsapi=0.6.1 +- certifi=2023.7.22 - cffi=1.15.1 - cfitsio=4.2.0 - cftime=1.6.2 -- charset-normalizer=2.1.1 -- click=8.1.3 +- charset-normalizer=3.2.0 +- click=8.1.6 - click-plugins=1.1.1 - cligj=0.7.2 - cloudpickle=2.2.1 -- coin-or-cbc=2.10.8 -- coin-or-cgl=0.60.6 -- coin-or-clp=1.17.7 -- coin-or-osi=0.108.7 -- coin-or-utils=2.11.6 -- coincbc=2.10.8 - colorama=0.4.6 -- configargparse=1.5.3 +- comm=0.1.3 +- configargparse=1.7 - connection_pool=0.0.3 -- country_converter=0.8.0 -- cryptography=39.0.1 -- curl=7.88.0 +- contourpy=1.1.0 +- country_converter=1.0.0 +- curl=8.2.0 - cycler=0.11.0 -- cytoolz=0.12.0 -- dask=2023.2.0 -- dask-core=2023.2.0 +- cytoolz=0.12.2 +- dask=2023.7.1 +- dask-core=2023.7.1 - datrie=0.8.2 - dbus=1.13.6 +- debugpy=1.6.7 - decorator=5.1.1 +- defusedxml=0.7.1 - deprecation=2.1.0 - descartes=1.1.0 -- distributed=2023.2.0 +- distributed=2023.7.1 - distro=1.8.0 -- docutils=0.19 -- dpath=2.1.4 -- entsoe-py=0.5.8 +- docutils=0.20.1 +- dpath=2.1.6 +- entrypoints=0.4 +- entsoe-py=0.5.10 - et_xmlfile=1.1.0 -- exceptiongroup=1.1.0 +- exceptiongroup=1.1.2 - executing=1.2.0 - expat=2.5.0 -- fftw=3.3.10 -- filelock=3.9.0 -- fiona=1.9.1 +- filelock=3.12.2 +- fiona=1.9.4 +- flit-core=3.9.0 - folium=0.14.0 - font-ttf-dejavu-sans-mono=2.37 - font-ttf-inconsolata=3.000 @@ -88,291 +107,366 @@ dependencies: - fontconfig=2.14.2 - fonts-conda-ecosystem=1 - fonts-conda-forge=1 -- fonttools=4.38.0 +- fonttools=4.41.1 - freetype=2.12.1 - freexl=1.0.6 -- fsspec=2023.1.0 -- gdal=3.6.2 +- fribidi=1.0.10 +- fsspec=2023.6.0 +- gdal=3.7.0 +- gdk-pixbuf=2.42.10 - geographiclib=1.52 - geojson-rewind=1.0.2 -- geopandas=0.12.2 -- geopandas-base=0.12.2 +- geopandas=0.13.2 +- geopandas-base=0.13.2 - geopy=2.3.0 -- geos=3.11.1 +- geos=3.11.2 - geotiff=1.7.1 - gettext=0.21.1 +- gflags=2.2.2 - giflib=5.2.1 - gitdb=4.0.10 -- gitpython=3.1.30 -- glib=2.74.1 -- glib-tools=2.74.1 +- gitpython=3.1.32 +- glib=2.76.4 +- glib-tools=2.76.4 +- glog=0.6.0 +- gmp=6.2.1 - graphite2=1.3.13 -- gst-plugins-base=1.22.0 -- gstreamer=1.22.0 -- gstreamer-orc=0.4.33 -- harfbuzz=6.0.0 +- graphviz=8.1.0 +- gst-plugins-base=1.22.5 +- gstreamer=1.22.5 +- gtk2=2.24.33 +- gts=0.7.6 +- harfbuzz=7.3.0 - hdf4=4.2.15 -- hdf5=1.12.2 -- heapdict=1.0.1 +- hdf5=1.14.1 - humanfriendly=10.0 -- icu=70.1 +- icu=72.1 - idna=3.4 -- importlib-metadata=6.0.0 -- importlib_resources=5.10.2 +- importlib-metadata=6.8.0 +- importlib_metadata=6.8.0 +- importlib_resources=6.0.0 - iniconfig=2.0.0 -- ipopt=3.14.11 -- ipython=8.10.0 -- jack=1.9.22 +- ipopt=3.14.12 +- ipykernel=6.24.0 +- ipython=8.14.0 +- ipython_genutils=0.2.0 +- ipywidgets=8.0.7 - jedi=0.18.2 - jinja2=3.1.2 -- joblib=1.2.0 -- jpeg=9e +- joblib=1.3.0 - json-c=0.16 -- jsonschema=4.17.3 -- jupyter_core=5.2.0 -- kealib=1.5.0 +- json5=0.9.14 +- jsonschema=4.18.4 +- jsonschema-specifications=2023.7.1 +- jupyter=1.0.0 +- jupyter-lsp=2.2.0 +- jupyter_client=8.3.0 +- jupyter_console=6.6.3 +- jupyter_core=5.3.1 +- jupyter_events=0.6.3 +- jupyter_server=2.7.0 +- jupyter_server_terminals=0.4.4 +- jupyterlab=4.0.3 +- jupyterlab_pygments=0.2.2 +- jupyterlab_server=2.24.0 +- jupyterlab_widgets=3.0.8 +- kealib=1.5.1 - keyutils=1.6.1 - kiwisolver=1.4.4 -- krb5=1.20.1 +- krb5=1.21.1 - lame=3.100 -- lcms2=2.14 +- lcms2=2.15 - ld_impl_linux-64=2.40 - lerc=4.0.0 +- libabseil=20230125.3 - libaec=1.0.6 +- libarchive=3.6.2 +- libarrow=12.0.1 - libblas=3.9.0 - libbrotlicommon=1.0.9 - libbrotlidec=1.0.9 - libbrotlienc=1.0.9 -- libcap=2.66 +- libcap=2.67 - libcblas=3.9.0 - libclang=15.0.7 - libclang13=15.0.7 +- libcrc32c=1.1.2 - libcups=2.3.3 -- libcurl=7.88.0 -- libdb=6.2.32 -- libdeflate=1.17 +- libcurl=8.2.0 +- libdeflate=1.18 - libedit=3.1.20191231 - libev=4.33 -- libevent=2.1.10 +- libevent=2.1.12 +- libexpat=2.5.0 - libffi=3.4.2 -- libflac=1.4.2 -- libgcc-ng=12.2.0 +- libflac=1.4.3 +- libgcc-ng=13.1.0 - libgcrypt=1.10.1 -- libgdal=3.6.2 -- libgfortran-ng=12.2.0 -- libgfortran5=12.2.0 -- libglib=2.74.1 -- libgomp=12.2.0 -- libgpg-error=1.46 +- libgd=2.3.3 +- libgdal=3.7.0 +- libgfortran-ng=13.1.0 +- libgfortran5=13.1.0 +- libglib=2.76.4 +- libgomp=13.1.0 +- libgoogle-cloud=2.12.0 +- libgpg-error=1.47 +- libgrpc=1.56.2 - libiconv=1.17 +- libjpeg-turbo=2.1.5.1 - libkml=1.3.0 - liblapack=3.9.0 - liblapacke=3.9.0 - libllvm15=15.0.7 -- libnetcdf=4.8.1 -- libnghttp2=1.51.0 +- libnetcdf=4.9.2 +- libnghttp2=1.52.0 - libnsl=2.0.0 +- libnuma=2.0.16 - libogg=1.3.4 -- libopenblas=0.3.21 +- libopenblas=0.3.23 - libopus=1.3.1 - libpng=1.6.39 -- libpq=15.2 +- libpq=15.3 +- libprotobuf=4.23.3 +- librsvg=2.56.1 - librttopo=1.1.0 - libsndfile=1.2.0 +- libsodium=1.0.18 - libspatialindex=1.9.3 - libspatialite=5.0.1 -- libsqlite=3.40.0 -- libssh2=1.10.0 -- libstdcxx-ng=12.2.0 -- libsystemd0=252 -- libtiff=4.5.0 +- libsqlite=3.42.0 +- libssh2=1.11.0 +- libstdcxx-ng=13.1.0 +- libsystemd0=253 +- libthrift=0.18.1 +- libtiff=4.5.1 - libtool=2.4.7 -- libudev1=252 -- libuuid=2.32.1 +- libutf8proc=2.8.0 +- libuuid=2.38.1 - libvorbis=1.3.7 -- libwebp-base=1.2.4 -- libxcb=1.13 +- libwebp=1.3.1 +- libwebp-base=1.3.1 +- libxcb=1.15 - libxkbcommon=1.5.0 -- libxml2=2.10.3 +- libxml2=2.11.4 - libxslt=1.1.37 - libzip=1.9.2 - libzlib=1.2.13 -- linopy=0.1.3 - locket=1.0.0 -- lxml=4.9.2 +- lxml=4.9.3 - lz4=4.3.2 - lz4-c=1.9.4 - lzo=2.10 - mapclassify=2.5.0 -- markupsafe=2.1.2 +- markupsafe=2.1.3 - matplotlib=3.5.3 - matplotlib-base=3.5.3 - matplotlib-inline=0.1.6 - memory_profiler=0.61.0 -- metis=5.1.0 -- mpg123=1.31.2 -- msgpack-python=1.0.4 +- metis=5.1.1 +- mistune=3.0.0 +- mpg123=1.31.3 +- msgpack-python=1.0.5 - mumps-include=5.2.1 - mumps-seq=5.2.1 -- munch=2.5.0 +- munch=4.0.0 - munkres=1.1.4 -- mysql-common=8.0.32 -- mysql-libs=8.0.32 -- nbformat=5.7.3 -- ncurses=6.3 -- netcdf4=1.6.2 -- networkx=3.0 +- mysql-common=8.0.33 +- mysql-libs=8.0.33 +- nbclient=0.8.0 +- nbconvert=7.7.2 +- nbconvert-core=7.7.2 +- nbconvert-pandoc=7.7.2 +- nbformat=5.9.1 +- ncurses=6.4 +- nest-asyncio=1.5.6 +- netcdf4=1.6.4 +- networkx=3.1 - nomkl=1.0 +- notebook=7.0.0 +- notebook-shim=0.2.3 - nspr=4.35 -- nss=3.88 -- numexpr=2.8.3 -- numpy=1.23.5 +- nss=3.89 +- numexpr=2.8.4 +- numpy=1.25.1 - openjdk=17.0.3 - openjpeg=2.5.0 -- openpyxl=3.1.0 -- openssl=3.0.8 -- packaging=23.0 -- pandas=1.5.3 +- openpyxl=3.1.2 +- openssl=3.1.1 +- orc=1.9.0 +- overrides=7.3.1 +- packaging=23.1 +- pandas=2.0.3 +- pandoc=3.1.3 +- pandocfilters=1.5.0 +- pango=1.50.14 - parso=0.8.3 -- partd=1.3.0 +- partd=1.4.0 - patsy=0.5.3 - pcre2=10.40 - pexpect=4.8.0 - pickleshare=0.7.5 -- pillow=9.4.0 -- pip=23.0 +- pillow=10.0.0 +- pip=23.2.1 - pixman=0.40.0 - pkgutil-resolve-name=1.3.10 - plac=1.3.5 -- platformdirs=3.0.0 -- pluggy=1.0.0 +- platformdirs=3.9.1 +- pluggy=1.2.0 - ply=3.11 -- pooch=1.6.0 -- poppler=22.12.0 +- pooch=1.7.0 +- poppler=23.05.0 - poppler-data=0.4.12 -- postgresql=15.2 -- powerplantmatching=0.5.6 +- postgresql=15.3 +- powerplantmatching=0.5.7 - progressbar2=4.2.0 -- proj=9.1.0 -- prompt-toolkit=3.0.36 -- psutil=5.9.4 +- proj=9.2.1 +- prometheus_client=0.17.1 +- prompt-toolkit=3.0.39 +- prompt_toolkit=3.0.39 +- psutil=5.9.5 - pthread-stubs=0.4 - ptyprocess=0.7.0 - pulp=2.7.0 -- pulseaudio=16.1 +- pulseaudio-client=16.1 - pure_eval=0.2.2 +- py-cpuinfo=9.0.0 +- pyarrow=12.0.1 - pycountry=22.3.5 - pycparser=2.21 -- pygments=2.14.0 -- pyomo=6.4.4 -- pyopenssl=23.0.0 -- pyparsing=3.0.9 -- pyproj=3.4.1 -- pypsa=0.22.1 +- pygments=2.15.1 +- pyomo=6.6.1 +- pyparsing=3.1.0 +- pyproj=3.6.0 - pyqt=5.15.7 - pyqt5-sip=12.11.0 -- pyrsistent=0.19.3 - pyshp=2.3.1 - pysocks=1.7.1 -- pytables=3.7.0 -- pytest=7.2.1 -- python=3.10.9 +- pytables=3.8.0 +- pytest=7.4.0 +- python=3.10.12 - python-dateutil=2.8.2 -- python-fastjsonschema=2.16.2 -- python-utils=3.5.2 +- python-fastjsonschema=2.18.0 +- python-json-logger=2.0.7 +- python-tzdata=2023.3 +- python-utils=3.7.0 - python_abi=3.10 -- pytz=2022.7.1 +- pytz=2023.3 - pyxlsb=1.0.10 - pyyaml=6.0 +- pyzmq=25.1.0 - qt-main=5.15.8 -- rasterio=1.3.4 -- readline=8.1.2 -- requests=2.28.2 +- qtconsole=5.4.3 +- qtconsole-base=5.4.3 +- qtpy=2.3.1 +- rasterio=1.3.8 +- rdma-core=28.9 +- re2=2023.03.02 +- readline=8.2 +- referencing=0.30.0 +- requests=2.31.0 - reretry=0.11.8 +- rfc3339-validator=0.1.4 +- rfc3986-validator=0.1.1 +- rioxarray=0.14.1 +- rpds-py=0.9.2 - rtree=1.0.1 -- scikit-learn=1.2.1 -- scipy=1.10.0 +- s2n=1.3.46 +- scikit-learn=1.3.0 +- scipy=1.11.1 - scotch=6.0.9 - seaborn=0.12.2 - seaborn-base=0.12.2 -- setuptools=67.3.2 +- send2trash=1.8.2 +- setuptools=68.0.0 - setuptools-scm=7.1.0 - setuptools_scm=7.1.0 - shapely=2.0.1 -- sip=6.7.7 +- sip=6.7.10 - six=1.16.0 - smart_open=6.3.0 - smmap=3.0.5 -- snakemake-minimal=7.22.0 -- snappy=1.1.9 +- snakemake-minimal=7.30.2 +- snappy=1.1.10 +- sniffio=1.3.0 - snuggs=1.4.7 - sortedcontainers=2.4.0 - soupsieve=2.3.2.post1 -- sqlite=3.40.0 +- sqlite=3.42.0 - stack_data=0.6.2 -- statsmodels=0.13.5 +- statsmodels=0.14.0 - stopit=1.1.2 - tabula-py=2.6.0 - tabulate=0.9.0 - tblib=1.7.0 -- threadpoolctl=3.1.0 +- terminado=0.17.1 +- threadpoolctl=3.2.0 - throttler=1.2.1 - tiledb=2.13.2 +- tinycss2=1.2.1 - tk=8.6.12 - toml=0.10.2 - tomli=2.0.1 - toolz=0.12.0 -- toposort=1.9 -- tornado=6.2 -- tqdm=4.64.1 +- toposort=1.10 +- tornado=6.3.2 +- tqdm=4.65.0 - traitlets=5.9.0 -- typing-extensions=4.4.0 -- typing_extensions=4.4.0 -- tzcode=2022g -- tzdata=2022g +- typing-extensions=4.7.1 +- typing_extensions=4.7.1 +- typing_utils=0.1.0 +- tzcode=2023c +- tzdata=2023c +- ucx=1.14.1 - unicodedata2=15.0.0 - unidecode=1.3.6 - unixodbc=2.3.10 -- urllib3=1.26.14 +- urllib3=2.0.4 - wcwidth=0.2.6 -- wheel=0.38.4 -- wrapt=1.14.1 -- xarray=2023.2.0 +- webencodings=0.5.1 +- websocket-client=1.6.1 +- wheel=0.41.0 +- widgetsnbextension=4.0.8 +- wrapt=1.15.0 +- xarray=2023.7.0 - xcb-util=0.4.0 - xcb-util-image=0.4.0 - xcb-util-keysyms=0.4.0 - xcb-util-renderutil=0.3.9 - xcb-util-wm=0.4.1 - xerces-c=3.2.4 +- xkeyboard-config=2.39 - xlrd=2.0.1 - xorg-fixesproto=5.0 - xorg-inputproto=2.3.2 - xorg-kbproto=1.0.7 -- xorg-libice=1.0.10 -- xorg-libsm=1.2.3 -- xorg-libx11=1.7.2 -- xorg-libxau=1.0.9 +- xorg-libice=1.1.1 +- xorg-libsm=1.2.4 +- xorg-libx11=1.8.6 +- xorg-libxau=1.0.11 - xorg-libxdmcp=1.1.3 - xorg-libxext=1.3.4 - xorg-libxfixes=5.0.3 - xorg-libxi=1.7.10 -- xorg-libxrender=0.9.10 +- xorg-libxrender=0.9.11 - xorg-libxtst=1.2.3 - xorg-recordproto=1.14.2 - xorg-renderproto=0.11.1 - xorg-xextproto=7.3.0 +- xorg-xf86vidmodeproto=2.3.1 - xorg-xproto=7.0.31 -- xyzservices=2022.9.0 +- xyzservices=2023.7.0 - xz=5.2.6 - yaml=0.2.5 - yte=1.5.1 -- zict=2.2.0 -- zipp=3.13.0 +- zeromq=4.3.4 +- zict=3.0.0 +- zipp=3.16.2 - zlib=1.2.13 +- zlib-ng=2.0.7 - zstd=1.5.2 - pip: - - countrycode==0.2 - - highspy==1.5.0.dev0 - - pybind11==2.10.3 - - tsam==2.2.2 - - vresutils==0.3.1 + - gurobipy==10.0.2 + - linopy==0.2.2 + - pypsa==0.25.1 + - tsam==2.3.0 + - validators==0.20.0 diff --git a/envs/environment.yaml b/envs/environment.yaml index db533badc..c3af36bbd 100644 --- a/envs/environment.yaml +++ b/envs/environment.yaml @@ -10,7 +10,6 @@ dependencies: - python>=3.8 - pip -- pypsa>=0.21.3 - atlite>=0.2.9 - dask @@ -25,10 +24,11 @@ dependencies: - pytables - lxml - powerplantmatching>=0.5.5 -- numpy<1.24 +- numpy - pandas>=1.4 - geopandas>=0.11.0 - xarray +- rioxarray - netcdf4 - networkx - scipy @@ -53,6 +53,7 @@ dependencies: - descartes - rasterio!=1.2.10 + - pip: - - vresutils>=0.3.1 - tsam>=1.1.0 + - pypsa>=0.25.1 diff --git a/rules/build_electricity.smk b/rules/build_electricity.smk index 9be7408db..6964a87d2 100644 --- a/rules/build_electricity.smk +++ b/rules/build_electricity.smk @@ -18,22 +18,30 @@ if config["enable"].get("prepare_links_p_nom", False): "../scripts/prepare_links_p_nom.py" -rule build_load_data: +rule build_electricity_demand: + params: + snapshots=config["snapshots"], + countries=config["countries"], + load=config["load"], input: ancient("data/load_raw.csv"), output: RESOURCES + "load.csv", log: - LOGS + "build_load_data.log", + LOGS + "build_electricity_demand.log", resources: mem_mb=5000, conda: "../envs/environment.yaml" script: - "../scripts/build_load_data.py" + "../scripts/build_electricity_demand.py" rule build_powerplants: + params: + powerplants_filter=config["electricity"]["powerplants_filter"], + custom_powerplants=config["electricity"]["custom_powerplants"], + countries=config["countries"], input: base_network=RESOURCES + "networks/base.nc", custom_powerplants="data/custom_powerplants.csv", @@ -51,6 +59,9 @@ rule build_powerplants: rule base_network: + params: + countries=config["countries"], + snapshots=config["snapshots"], input: eg_buses="data/entsoegridkit/buses.csv", eg_lines="data/entsoegridkit/lines.csv", @@ -79,6 +90,8 @@ rule base_network: rule build_shapes: + params: + countries=config["countries"], input: naturalearth=ancient("data/bundle/naturalearth/ne_10m_admin_0_countries.shp"), eez=ancient("data/bundle/eez/World_EEZ_v8_2014.shp"), @@ -104,6 +117,8 @@ rule build_shapes: rule build_bus_regions: + params: + countries=config["countries"], input: country_shapes=RESOURCES + "country_shapes.geojson", offshore_shapes=RESOURCES + "offshore_shapes.geojson", @@ -125,6 +140,9 @@ rule build_bus_regions: if config["enable"].get("build_cutout", False): rule build_cutout: + params: + snapshots=config["snapshots"], + cutouts=config["atlite"]["cutouts"], input: regions_onshore=RESOURCES + "regions_onshore.geojson", regions_offshore=RESOURCES + "regions_offshore.geojson", @@ -172,7 +190,7 @@ rule build_ship_raster: ], ), output: - RESOURCES + "shipdensity_raster.nc", + RESOURCES + "shipdensity_raster.tif", log: LOGS + "build_ship_raster.log", resources: @@ -186,6 +204,8 @@ rule build_ship_raster: rule build_renewable_profiles: + params: + renewable=config["renewable"], input: base_network=RESOURCES + "networks/base.nc", corine=ancient("data/bundle/corine/g250_clc06_V18_5.tif"), @@ -202,7 +222,7 @@ rule build_renewable_profiles: ) ), ship_density=lambda w: ( - RESOURCES + "shipdensity_raster.nc" + RESOURCES + "shipdensity_raster.tif" if "ship_threshold" in config["renewable"][w.technology].keys() else [] ), @@ -235,6 +255,9 @@ rule build_renewable_profiles: rule build_hydro_profile: + params: + hydro=config["renewable"]["hydro"], + countries=config["countries"], input: country_shapes=RESOURCES + "country_shapes.geojson", eia_hydro_generation="data/eia_hydro_annual_generation.csv", @@ -251,7 +274,39 @@ rule build_hydro_profile: "../scripts/build_hydro_profile.py" +if config["lines"]["dynamic_line_rating"]["activate"]: + + rule build_line_rating: + input: + base_network=RESOURCES + "networks/base.nc", + cutout="cutouts/" + + CDIR + + config["lines"]["dynamic_line_rating"]["cutout"] + + ".nc", + output: + output=RESOURCES + "networks/line_rating.nc", + log: + LOGS + "build_line_rating.log", + benchmark: + BENCHMARKS + "build_line_rating" + threads: ATLITE_NPROCESSES + resources: + mem_mb=ATLITE_NPROCESSES * 1000, + conda: + "../envs/environment.yaml" + script: + "../scripts/build_line_rating.py" + + rule add_electricity: + params: + length_factor=config["lines"]["length_factor"], + scaling_factor=config["load"]["scaling_factor"], + countries=config["countries"], + renewable=config["renewable"], + electricity=config["electricity"], + conventional=config.get("conventional", {}), + costs=config["costs"], input: **{ f"profile_{tech}": RESOURCES + f"profile_{tech}.nc" @@ -264,6 +319,9 @@ rule add_electricity: if str(fn).startswith("data/") }, base_network=RESOURCES + "networks/base.nc", + line_rating=RESOURCES + "networks/line_rating.nc" + if config["lines"]["dynamic_line_rating"]["activate"] + else RESOURCES + "networks/base.nc", tech_costs=COSTS, regions=RESOURCES + "regions_onshore.geojson", powerplants=RESOURCES + "powerplants.csv", @@ -287,6 +345,15 @@ rule add_electricity: rule simplify_network: + params: + simplify_network=config["clustering"]["simplify_network"], + aggregation_strategies=config["clustering"].get("aggregation_strategies", {}), + focus_weights=config.get("focus_weights", None), + renewable_carriers=config["electricity"]["renewable_carriers"], + max_hours=config["electricity"]["max_hours"], + length_factor=config["lines"]["length_factor"], + p_max_pu=config["links"].get("p_max_pu", 1.0), + costs=config["costs"], input: network=RESOURCES + "networks/elec.nc", tech_costs=COSTS, @@ -312,6 +379,16 @@ rule simplify_network: rule cluster_network: + params: + cluster_network=config["clustering"]["cluster_network"], + aggregation_strategies=config["clustering"].get("aggregation_strategies", {}), + custom_busmap=config["enable"].get("custom_busmap", False), + focus_weights=config.get("focus_weights", None), + renewable_carriers=config["electricity"]["renewable_carriers"], + conventional_carriers=config["electricity"].get("conventional_carriers", []), + max_hours=config["electricity"]["max_hours"], + length_factor=config["lines"]["length_factor"], + costs=config["costs"], input: network=RESOURCES + "networks/elec_s{simpl}.nc", regions_onshore=RESOURCES + "regions_onshore_elec_s{simpl}.geojson", @@ -343,6 +420,10 @@ rule cluster_network: rule add_extra_components: + params: + extendable_carriers=config["electricity"]["extendable_carriers"], + max_hours=config["electricity"]["max_hours"], + costs=config["costs"], input: network=RESOURCES + "networks/elec_s{simpl}_{clusters}.nc", tech_costs=COSTS, @@ -362,6 +443,14 @@ rule add_extra_components: rule prepare_network: + params: + links=config["links"], + lines=config["lines"], + co2base=config["electricity"]["co2base"], + co2limit=config["electricity"]["co2limit"], + gaslimit=config["electricity"].get("gaslimit"), + max_hours=config["electricity"]["max_hours"], + costs=config["costs"], input: RESOURCES + "networks/elec_s{simpl}_{clusters}_ec.nc", tech_costs=COSTS, diff --git a/rules/build_sector.smk b/rules/build_sector.smk index 1b724d1a3..86f8bab2d 100644 --- a/rules/build_sector.smk +++ b/rules/build_sector.smk @@ -140,6 +140,8 @@ if not (config["sector"]["gas_network"] or config["sector"]["H2_retrofit"]): rule build_heat_demands: + params: + snapshots=config["snapshots"], input: pop_layout=RESOURCES + "pop_layout_{scope}.nc", regions_onshore=RESOURCES + "regions_onshore_elec_s{simpl}_{clusters}.geojson", @@ -160,6 +162,8 @@ rule build_heat_demands: rule build_temperature_profiles: + params: + snapshots=config["snapshots"], input: pop_layout=RESOURCES + "pop_layout_{scope}.nc", regions_onshore=RESOURCES + "regions_onshore_elec_s{simpl}_{clusters}.geojson", @@ -181,6 +185,8 @@ rule build_temperature_profiles: rule build_cop_profiles: + params: + heat_pump_sink_T=config["sector"]["heat_pump_sink_T"], input: temp_soil_total=RESOURCES + "temp_soil_total_elec_s{simpl}_{clusters}.nc", temp_soil_rural=RESOURCES + "temp_soil_rural_elec_s{simpl}_{clusters}.nc", @@ -208,6 +214,9 @@ rule build_cop_profiles: rule build_solar_thermal_profiles: + params: + snapshots=config["snapshots"], + solar_thermal=config["solar_thermal"], input: pop_layout=RESOURCES + "pop_layout_{scope}.nc", regions_onshore=RESOURCES + "regions_onshore_elec_s{simpl}_{clusters}.geojson", @@ -228,6 +237,9 @@ rule build_solar_thermal_profiles: rule build_energy_totals: + params: + countries=config["countries"], + energy=config["energy"], input: nuts3_shapes=RESOURCES + "nuts3_shapes.geojson", co2="data/eea/UNFCCC_v23.csv", @@ -253,6 +265,8 @@ rule build_energy_totals: rule build_biomass_potentials: + params: + biomass=config["biomass"], input: enspreso_biomass=HTTP.remote( "https://cidportal.jrc.ec.europa.eu/ftp/jrc-opendata/ENSPRESO/ENSPRESO_BIOMASS.xlsx", @@ -315,6 +329,10 @@ if not config["sector"]["biomass_transport"]: if config["sector"]["regional_co2_sequestration_potential"]["enable"]: rule build_sequestration_potentials: + params: + sequestration_potential=config["sector"][ + "regional_co2_sequestration_potential" + ], input: sequestration_potential=HTTP.remote( "https://raw.githubusercontent.com/ericzhou571/Co2Storage/main/resources/complete_map_2020_unit_Mt.geojson", @@ -368,6 +386,8 @@ rule build_salt_cavern_potentials: rule build_ammonia_production: + params: + countries=config["countries"], input: usgs="data/myb1-2017-nitro.xls", output: @@ -386,6 +406,9 @@ rule build_ammonia_production: rule build_industry_sector_ratios: + params: + industry=config["industry"], + ammonia=config["sector"].get("ammonia", False), input: ammonia_production=RESOURCES + "ammonia_production.csv", idees="data/jrc-idees-2015", @@ -405,6 +428,9 @@ rule build_industry_sector_ratios: rule build_industrial_production_per_country: + params: + industry=config["industry"], + countries=config["countries"], input: ammonia_production=RESOURCES + "ammonia_production.csv", jrc="data/jrc-idees-2015", @@ -426,6 +452,8 @@ rule build_industrial_production_per_country: rule build_industrial_production_per_country_tomorrow: + params: + industry=config["industry"], input: industrial_production_per_country=RESOURCES + "industrial_production_per_country.csv", @@ -450,6 +478,9 @@ rule build_industrial_production_per_country_tomorrow: rule build_industrial_distribution_key: + params: + hotmaps_locate_missing=config["industry"].get("hotmaps_locate_missing", False), + countries=config["countries"], input: regions_onshore=RESOURCES + "regions_onshore_elec_s{simpl}_{clusters}.geojson", clustered_pop_layout=RESOURCES + "pop_layout_elec_s{simpl}_{clusters}.csv", @@ -524,6 +555,9 @@ rule build_industrial_energy_demand_per_node: rule build_industrial_energy_demand_per_country_today: + params: + countries=config["countries"], + industry=config["industry"], input: jrc="data/jrc-idees-2015", ammonia_production=RESOURCES + "ammonia_production.csv", @@ -570,6 +604,9 @@ rule build_industrial_energy_demand_per_node_today: if config["sector"]["retrofitting"]["retro_endogen"]: rule build_retro_cost: + params: + retrofitting=config["sector"]["retrofitting"], + countries=config["countries"], input: building_stock="data/retro/data_building_stock.csv", data_tabula="data/retro/tabula-calculator-calcsetbuilding.csv", @@ -640,6 +677,9 @@ rule build_shipping_demand: rule build_transport_demand: + params: + snapshots=config["snapshots"], + sector=config["sector"], input: clustered_pop_layout=RESOURCES + "pop_layout_elec_s{simpl}_{clusters}.csv", pop_weighted_energy_totals=RESOURCES @@ -666,13 +706,24 @@ rule build_transport_demand: rule prepare_sector_network: params: + co2_budget=config["co2_budget"], + conventional_carriers=config["existing_capacities"]["conventional_carriers"], + foresight=config["foresight"], + costs=config["costs"], + sector=config["sector"], + industry=config["industry"], + pypsa_eur=config["pypsa_eur"], + length_factor=config["lines"]["length_factor"], + planning_horizons=config["scenario"]["planning_horizons"], + countries=config["countries"], + emissions_scope=config["energy"]["emissions"], + eurostat_report_year=config["energy"]["eurostat_report_year"], RDIR=RDIR, input: **build_retro_cost_output, **build_biomass_transport_costs_output, **gas_infrastructure, **build_sequestration_potentials_output, - overrides="data/override_component_attrs", network=RESOURCES + "networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc", energy_totals_name=RESOURCES + "energy_totals.csv", eurostat=input_eurostat, diff --git a/rules/common.smk b/rules/common.smk index 8f0c7cbb2..3fc2c721c 100644 --- a/rules/common.smk +++ b/rules/common.smk @@ -23,6 +23,22 @@ def memory(w): return int(factor * (10000 + 195 * int(w.clusters))) +# Check if the workflow has access to the internet by trying to access the HEAD of specified url +def has_internet_access(url="www.zenodo.org") -> bool: + import http.client as http_client + + # based on answer and comments from + # https://stackoverflow.com/a/29854274/11318472 + conn = http_client.HTTPConnection(url, timeout=5) # need access to zenodo anyway + try: + conn.request("HEAD", "/") + return True + except: + return False + finally: + conn.close() + + def input_eurostat(w): # 2016 includes BA, 2017 does not report_year = config["energy"]["eurostat_report_year"] diff --git a/rules/postprocess.smk b/rules/postprocess.smk index d5095358c..105318f3c 100644 --- a/rules/postprocess.smk +++ b/rules/postprocess.smk @@ -9,8 +9,10 @@ localrules: rule plot_network: + params: + foresight=config["foresight"], + plotting=config["plotting"], input: - overrides="data/override_component_attrs", network=RESULTS + "postnetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc", regions=RESOURCES + "regions_onshore_elec_s{simpl}_{clusters}.geojson", @@ -37,7 +39,7 @@ rule copy_config: params: RDIR=RDIR, output: - RESULTS + "configs/config.yaml", + RESULTS + "config/config.yaml", threads: 1 resources: mem_mb=1000, @@ -51,7 +53,7 @@ rule copy_config: rule copy_conda_env: output: - RESULTS + "configs/environment.yaml", + RESULTS + "config/environment.yaml", threads: 1 resources: mem_mb=500, @@ -67,9 +69,12 @@ rule copy_conda_env: rule make_summary: params: + foresight=config["foresight"], + costs=config["costs"], + snapshots=config["snapshots"], + scenario=config["scenario"], RDIR=RDIR, input: - overrides="data/override_component_attrs", networks=expand( RESULTS + "postnetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc", @@ -114,6 +119,10 @@ rule make_summary: rule plot_summary: params: + countries=config["countries"], + planning_horizons=config["scenario"]["planning_horizons"], + sector_opts=config["scenario"]["sector_opts"], + plotting=config["plotting"], RDIR=RDIR, input: costs=RESULTS + "csvs/costs.csv", diff --git a/rules/retrieve.smk b/rules/retrieve.smk index 37deb44d0..a253ec0c0 100644 --- a/rules/retrieve.smk +++ b/rules/retrieve.smk @@ -2,7 +2,14 @@ # # SPDX-License-Identifier: MIT -if config["enable"].get("retrieve_databundle", True): +if config["enable"].get("retrieve", "auto") == "auto": + config["enable"]["retrieve"] = has_internet_access() + +if config["enable"]["retrieve"] is False: + print("Datafile downloads disabled in config[retrieve] or no internet access.") + + +if config["enable"]["retrieve"] and config["enable"].get("retrieve_databundle", True): datafiles = [ "ch_cantons.csv", "je-e-21.03.02.xls", @@ -32,7 +39,7 @@ if config["enable"].get("retrieve_databundle", True): "../scripts/retrieve_databundle.py" -if config["enable"].get("retrieve_cutout", True): +if config["enable"]["retrieve"] and config["enable"].get("retrieve_cutout", True): rule retrieve_cutout: input: @@ -51,7 +58,7 @@ if config["enable"].get("retrieve_cutout", True): move(input[0], output[0]) -if config["enable"].get("retrieve_cost_data", True): +if config["enable"]["retrieve"] and config["enable"].get("retrieve_cost_data", True): rule retrieve_cost_data: input: @@ -73,7 +80,9 @@ if config["enable"].get("retrieve_cost_data", True): move(input[0], output[0]) -if config["enable"].get("retrieve_natura_raster", True): +if config["enable"]["retrieve"] and config["enable"].get( + "retrieve_natura_raster", True +): rule retrieve_natura_raster: input: @@ -93,7 +102,9 @@ if config["enable"].get("retrieve_natura_raster", True): move(input[0], output[0]) -if config["enable"].get("retrieve_sector_databundle", True): +if config["enable"]["retrieve"] and config["enable"].get( + "retrieve_sector_databundle", True +): datafiles = [ "data/eea/UNFCCC_v23.csv", "data/switzerland-sfoe/switzerland-new_format.csv", @@ -120,7 +131,9 @@ if config["enable"].get("retrieve_sector_databundle", True): "../scripts/retrieve_sector_databundle.py" -if config["sector"]["gas_network"] or config["sector"]["H2_retrofit"]: +if config["enable"]["retrieve"] and ( + config["sector"]["gas_network"] or config["sector"]["H2_retrofit"] +): datafiles = [ "IGGIELGN_LNGs.geojson", "IGGIELGN_BorderPoints.geojson", @@ -140,37 +153,41 @@ if config["sector"]["gas_network"] or config["sector"]["H2_retrofit"]: "../scripts/retrieve_gas_infrastructure_data.py" -rule retrieve_load_data: - input: - HTTP.remote( - "data.open-power-system-data.org/time_series/2019-06-05/time_series_60min_singleindex.csv", - keep_local=True, - static=True, - ), - output: - "data/load_raw.csv", - log: - LOGS + "retrieve_load_data.log", - resources: - mem_mb=5000, - retries: 2 - run: - move(input[0], output[0]) - - -rule retrieve_ship_raster: - input: - HTTP.remote( - "https://zenodo.org/record/6953563/files/shipdensity_global.zip", - keep_local=True, - static=True, - ), - output: - "data/shipdensity_global.zip", - log: - LOGS + "retrieve_ship_raster.log", - resources: - mem_mb=5000, - retries: 2 - run: - move(input[0], output[0]) +if config["enable"]["retrieve"]: + + rule retrieve_electricity_demand: + input: + HTTP.remote( + "data.open-power-system-data.org/time_series/2019-06-05/time_series_60min_singleindex.csv", + keep_local=True, + static=True, + ), + output: + "data/load_raw.csv", + log: + LOGS + "retrieve_electricity_demand.log", + resources: + mem_mb=5000, + retries: 2 + run: + move(input[0], output[0]) + + +if config["enable"]["retrieve"]: + + rule retrieve_ship_raster: + input: + HTTP.remote( + "https://zenodo.org/record/6953563/files/shipdensity_global.zip", + keep_local=True, + static=True, + ), + output: + "data/shipdensity_global.zip", + log: + LOGS + "retrieve_ship_raster.log", + resources: + mem_mb=5000, + retries: 2 + run: + move(input[0], output[0]) diff --git a/rules/solve_electricity.smk b/rules/solve_electricity.smk index 8ddeca92f..f73a5b0c5 100644 --- a/rules/solve_electricity.smk +++ b/rules/solve_electricity.smk @@ -4,6 +4,13 @@ rule solve_network: + params: + solving=config["solving"], + foresight=config["foresight"], + planning_horizons=config["scenario"]["planning_horizons"], + co2_sequestration_potential=config["sector"].get( + "co2_sequestration_potential", 200 + ), input: network=RESOURCES + "networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc", output: @@ -14,8 +21,6 @@ rule solve_network: ), python=LOGS + "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_python.log", - memory=LOGS - + "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_memory.log", benchmark: BENCHMARKS + "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}" threads: 4 @@ -30,6 +35,8 @@ rule solve_network: rule solve_operations_network: + params: + options=config["solving"]["options"], input: network=RESULTS + "networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc", output: @@ -41,8 +48,6 @@ rule solve_operations_network: ), python=LOGS + "solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_python.log", - memory=LOGS - + "solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_memory.log", benchmark: ( BENCHMARKS diff --git a/rules/solve_myopic.smk b/rules/solve_myopic.smk index 041bee841..ba2787a18 100644 --- a/rules/solve_myopic.smk +++ b/rules/solve_myopic.smk @@ -4,8 +4,12 @@ rule add_existing_baseyear: + params: + baseyear=config["scenario"]["planning_horizons"][0], + sector=config["sector"], + existing_capacities=config["existing_capacities"], + costs=config["costs"], input: - overrides="data/override_component_attrs", network=RESULTS + "prenetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc", powerplants=RESOURCES + "powerplants.csv", @@ -42,8 +46,11 @@ rule add_existing_baseyear: rule add_brownfield: + params: + H2_retrofit=config["sector"]["H2_retrofit"], + H2_retrofit_capacity_per_CH4=config["sector"]["H2_retrofit_capacity_per_CH4"], + threshold_capacity=config["existing_capacities"]["threshold_capacity"], input: - overrides="data/override_component_attrs", network=RESULTS + "prenetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc", network_p=solved_previous_horizon, #solved network at previous time step @@ -74,12 +81,18 @@ ruleorder: add_existing_baseyear > add_brownfield rule solve_sector_network_myopic: + params: + solving=config["solving"], + foresight=config["foresight"], + planning_horizons=config["scenario"]["planning_horizons"], + co2_sequestration_potential=config["sector"].get( + "co2_sequestration_potential", 200 + ), input: - overrides="data/override_component_attrs", network=RESULTS + "prenetworks-brownfield/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc", costs="data/costs_{planning_horizons}.csv", - config=RESULTS + "configs/config.yaml", + config=RESULTS + "config/config.yaml", output: RESULTS + "postnetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc", @@ -90,8 +103,6 @@ rule solve_sector_network_myopic: + "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_solver.log", python=LOGS + "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_python.log", - memory=LOGS - + "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_memory.log", threads: 4 resources: mem_mb=config["solving"]["mem"], diff --git a/rules/solve_overnight.smk b/rules/solve_overnight.smk index c39662ec8..d0313f303 100644 --- a/rules/solve_overnight.smk +++ b/rules/solve_overnight.smk @@ -4,13 +4,19 @@ rule solve_sector_network: + params: + solving=config["solving"], + foresight=config["foresight"], + planning_horizons=config["scenario"]["planning_horizons"], + co2_sequestration_potential=config["sector"].get( + "co2_sequestration_potential", 200 + ), input: - overrides="data/override_component_attrs", network=RESULTS + "prenetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc", costs="data/costs_{}.csv".format(config["costs"]["year"]), - config=RESULTS + "configs/config.yaml", - #env=RDIR + 'configs/environment.yaml', + config=RESULTS + "config/config.yaml", + #env=RDIR + 'config/environment.yaml', output: RESULTS + "postnetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc", @@ -21,8 +27,6 @@ rule solve_sector_network: + "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_solver.log", python=LOGS + "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_python.log", - memory=LOGS - + "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_memory.log", threads: config["solving"]["solver"].get("threads", 4) resources: mem_mb=config["solving"]["mem"], diff --git a/scripts/_helpers.py b/scripts/_helpers.py index 281ee9c28..fc7bc9e0b 100644 --- a/scripts/_helpers.py +++ b/scripts/_helpers.py @@ -72,92 +72,6 @@ def configure_logging(snakemake, skip_handlers=False): logging.basicConfig(**kwargs) -def load_network(import_name=None, custom_components=None): - """ - Helper for importing a pypsa.Network with additional custom components. - - Parameters - ---------- - import_name : str - As in pypsa.Network(import_name) - custom_components : dict - Dictionary listing custom components. - For using ``snakemake.config['override_components']`` - in ``config.yaml`` define: - - .. code:: yaml - - override_components: - ShadowPrice: - component: ["shadow_prices","Shadow price for a global constraint.",np.nan] - attributes: - name: ["string","n/a","n/a","Unique name","Input (required)"] - value: ["float","n/a",0.,"shadow value","Output"] - - Returns - ------- - pypsa.Network - """ - import pypsa - from pypsa.descriptors import Dict - - override_components = None - override_component_attrs = None - - if custom_components is not None: - override_components = pypsa.components.components.copy() - override_component_attrs = Dict( - {k: v.copy() for k, v in pypsa.components.component_attrs.items()} - ) - for k, v in custom_components.items(): - override_components.loc[k] = v["component"] - override_component_attrs[k] = pd.DataFrame( - columns=["type", "unit", "default", "description", "status"] - ) - for attr, val in v["attributes"].items(): - override_component_attrs[k].loc[attr] = val - - return pypsa.Network( - import_name=import_name, - override_components=override_components, - override_component_attrs=override_component_attrs, - ) - - -def load_network_for_plots(fn, tech_costs, config, combine_hydro_ps=True): - import pypsa - from add_electricity import load_costs, update_transmission_costs - - n = pypsa.Network(fn) - - n.loads["carrier"] = n.loads.bus.map(n.buses.carrier) + " load" - n.stores["carrier"] = n.stores.bus.map(n.buses.carrier) - - n.links["carrier"] = ( - n.links.bus0.map(n.buses.carrier) + "-" + n.links.bus1.map(n.buses.carrier) - ) - n.lines["carrier"] = "AC line" - n.transformers["carrier"] = "AC transformer" - - n.lines["s_nom"] = n.lines["s_nom_min"] - n.links["p_nom"] = n.links["p_nom_min"] - - if combine_hydro_ps: - n.storage_units.loc[ - n.storage_units.carrier.isin({"PHS", "hydro"}), "carrier" - ] = "hydro+PHS" - - # if the carrier was not set on the heat storage units - # bus_carrier = n.storage_units.bus.map(n.buses.carrier) - # n.storage_units.loc[bus_carrier == "heat","carrier"] = "water tanks" - - Nyears = n.snapshot_weightings.objective.sum() / 8760.0 - costs = load_costs(tech_costs, config["costs"], config["electricity"], Nyears) - update_transmission_costs(n, costs) - - return n - - def update_p_nom_max(n): # if extendable carriers (solar/onwind/...) have capacity >= 0, # e.g. existing assets from the OPSD project are included to the network, @@ -277,23 +191,6 @@ def update_to(b=1, bsize=1, tsize=None): urllib.request.urlretrieve(url, file, reporthook=update_to) -def get_aggregation_strategies(aggregation_strategies): - # default aggregation strategies that cannot be defined in .yaml format must be specified within - # the function, otherwise (when defaults are passed in the function's definition) they get lost - # when custom values are specified in the config. - - import numpy as np - from pypsa.networkclustering import _make_consense - - bus_strategies = dict(country=_make_consense("Bus", "country")) - bus_strategies.update(aggregation_strategies.get("buses", {})) - - generator_strategies = {"build_year": lambda x: 0, "lifetime": lambda x: np.inf} - generator_strategies.update(aggregation_strategies.get("generators", {})) - - return bus_strategies, generator_strategies - - def mock_snakemake(rulename, configfiles=[], **wildcards): """ This function is expected to be executed from the 'scripts'-directory of ' @@ -384,41 +281,12 @@ def make_accessable(*ios): return snakemake -def override_component_attrs(directory): - """Tell PyPSA that links can have multiple outputs by - overriding the component_attrs. This can be done for - as many buses as you need with format busi for i = 2,3,4,5,.... - See https://pypsa.org/doc/components.html#link-with-multiple-outputs-or-inputs - - Parameters - ---------- - directory : string - Folder where component attributes to override are stored - analogous to ``pypsa/component_attrs``, e.g. `links.csv`. - - Returns - ------- - Dictionary of overridden component attributes. - """ - - attrs = Dict({k: v.copy() for k, v in component_attrs.items()}) - - for component, list_name in components.list_name.items(): - fn = f"{directory}/{list_name}.csv" - if os.path.isfile(fn): - overrides = pd.read_csv(fn, index_col=0, na_values="n/a") - attrs[component] = overrides.combine_first(attrs[component]) - - return attrs - - def generate_periodic_profiles(dt_index, nodes, weekly_profile, localize=None): """ Give a 24*7 long list of weekly hourly profiles, generate this for each country for the period dt_index, taking account of time zones and summer time. """ - weekly_profile = pd.Series(weekly_profile, range(24 * 7)) week_df = pd.DataFrame(index=dt_index, columns=nodes) diff --git a/scripts/add_brownfield.py b/scripts/add_brownfield.py index dc7828380..597792c06 100644 --- a/scripts/add_brownfield.py +++ b/scripts/add_brownfield.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Prepares brownfield data from previous planning horizon. """ @@ -17,7 +16,7 @@ import numpy as np import pypsa -from _helpers import override_component_attrs, update_config_with_sector_opts +from _helpers import update_config_with_sector_opts from add_existing_baseyear import add_build_year_to_new_assets @@ -50,7 +49,7 @@ def add_brownfield(n, n_p, year): ) ] - threshold = snakemake.config["existing_capacities"]["threshold_capacity"] + threshold = snakemake.params.threshold_capacity if not chp_heat.empty: threshold_chp_heat = ( @@ -88,7 +87,7 @@ def add_brownfield(n, n_p, year): # deal with gas network pipe_carrier = ["gas pipeline"] - if snakemake.config["sector"]["H2_retrofit"]: + if snakemake.params.H2_retrofit: # drop capacities of previous year to avoid duplicating to_drop = n.links.carrier.isin(pipe_carrier) & (n.links.build_year != year) n.mremove("Link", n.links.loc[to_drop].index) @@ -99,7 +98,7 @@ def add_brownfield(n, n_p, year): & (n.links.build_year != year) ].index gas_pipes_i = n.links[n.links.carrier.isin(pipe_carrier)].index - CH4_per_H2 = 1 / snakemake.config["sector"]["H2_retrofit_capacity_per_CH4"] + CH4_per_H2 = 1 / snakemake.params.H2_retrofit_capacity_per_CH4 fr = "H2 pipeline retrofitted" to = "gas pipeline" # today's pipe capacity @@ -148,12 +147,11 @@ def add_brownfield(n, n_p, year): year = int(snakemake.wildcards.planning_horizons) - overrides = override_component_attrs(snakemake.input.overrides) - n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides) + n = pypsa.Network(snakemake.input.network) add_build_year_to_new_assets(n, year) - n_p = pypsa.Network(snakemake.input.network_p, override_component_attrs=overrides) + n_p = pypsa.Network(snakemake.input.network_p) add_brownfield(n, n_p, year) diff --git a/scripts/add_electricity.py b/scripts/add_electricity.py index ef6ff3470..24567477d 100755 --- a/scripts/add_electricity.py +++ b/scripts/add_electricity.py @@ -2,8 +2,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - -# coding: utf-8 """ Adds electrical generators and existing hydro storage units to a base network. @@ -41,7 +39,7 @@ length_factor: .. seealso:: - Documentation of the configuration file ``config.yaml`` at :ref:`costs_cf`, + Documentation of the configuration file ``config/config.yaml`` at :ref:`costs_cf`, :ref:`electricity_cf`, :ref:`load_cf`, :ref:`renewable_cf`, :ref:`lines_cf` Inputs @@ -85,16 +83,18 @@ """ import logging +from itertools import product import geopandas as gpd import numpy as np import pandas as pd import powerplantmatching as pm import pypsa +import scipy.sparse as sparse import xarray as xr from _helpers import configure_logging, update_p_nom_max from powerplantmatching.export import map_country_bus -from vresutils import transfer as vtransfer +from shapely.prepared import prep idx = pd.IndexSlice @@ -121,21 +121,71 @@ def calculate_annuity(n, r): return 1 / n -def _add_missing_carriers_from_costs(n, costs, carriers): - missing_carriers = pd.Index(carriers).difference(n.carriers.index) - if missing_carriers.empty: - return +def add_missing_carriers(n, carriers): + """ + Function to add missing carriers to the network without raising errors. + """ + missing_carriers = set(carriers) - set(n.carriers.index) + if len(missing_carriers) > 0: + n.madd("Carrier", missing_carriers) + + +def sanitize_carriers(n, config): + """ + Sanitize the carrier information in a PyPSA Network object. + + The function ensures that all unique carrier names are present in the network's + carriers attribute, and adds nice names and colors for each carrier according + to the provided configuration dictionary. + + Parameters + ---------- + n : pypsa.Network + A PyPSA Network object that represents an electrical power system. + config : dict + A dictionary containing configuration information, specifically the + "plotting" key with "nice_names" and "tech_colors" keys for carriers. + + Returns + ------- + None + The function modifies the 'n' PyPSA Network object in-place, updating the + carriers attribute with nice names and colors. + + Warnings + -------- + Raises a warning if any carrier's "tech_colors" are not defined in the config dictionary. + """ + + for c in n.iterate_components(): + if "carrier" in c.df: + add_missing_carriers(n, c.df.carrier) - emissions_cols = ( - costs.columns.to_series().loc[lambda s: s.str.endswith("_emissions")].values + carrier_i = n.carriers.index + nice_names = ( + pd.Series(config["plotting"]["nice_names"]) + .reindex(carrier_i) + .fillna(carrier_i.to_series().str.title()) + ) + n.carriers["nice_name"] = n.carriers.nice_name.where( + n.carriers.nice_name != "", nice_names ) - suptechs = missing_carriers.str.split("-").str[0] - emissions = costs.loc[suptechs, emissions_cols].fillna(0.0) - emissions.index = missing_carriers - n.import_components_from_dataframe(emissions, "Carrier") + colors = pd.Series(config["plotting"]["tech_colors"]).reindex(carrier_i) + if colors.isna().any(): + missing_i = list(colors.index[colors.isna()]) + logger.warning(f"tech_colors for carriers {missing_i} not defined in config.") + n.carriers["color"] = n.carriers.color.where(n.carriers.color != "", colors) + + +def add_co2_emissions(n, costs, carriers): + """ + Add CO2 emissions to the network's carriers attribute. + """ + suptechs = n.carriers.loc[carriers].index.str.split("-").str[0] + n.carriers.loc[carriers, "co2_emissions"] = costs.co2_emissions[suptechs].values -def load_costs(tech_costs, config, elec_config, Nyears=1.0): +def load_costs(tech_costs, config, max_hours, Nyears=1.0): # set all asset costs and other parameters costs = pd.read_csv(tech_costs, index_col=[0, 1]).sort_index() @@ -178,7 +228,6 @@ def costs_for_storage(store, link1, link2=None, max_hours=1.0): dict(capital_cost=capital_cost, marginal_cost=0.0, co2_emissions=0.0) ) - max_hours = elec_config["max_hours"] costs.loc["battery"] = costs_for_storage( costs.loc["battery storage"], costs.loc["battery inverter"], @@ -216,6 +265,21 @@ def load_powerplants(ppl_fn): ) +def shapes_to_shapes(orig, dest): + """ + Adopted from vresutils.transfer.Shapes2Shapes() + """ + orig_prepped = list(map(prep, orig)) + transfer = sparse.lil_matrix((len(dest), len(orig)), dtype=float) + + for i, j in product(range(len(dest)), range(len(orig))): + if orig_prepped[j].intersects(dest[i]): + area = orig[j].intersection(dest[i]).area + transfer[i, j] = area / dest[i].area + + return transfer + + def attach_load(n, regions, load, nuts3_shapes, countries, scaling=1.0): substation_lv_i = n.buses.index[n.buses["substation_lv"]] regions = gpd.read_file(regions).set_index("name").reindex(substation_lv_i) @@ -232,9 +296,7 @@ def upsample(cntry, group): return pd.DataFrame({group.index[0]: l}) else: nuts3_cntry = nuts3.loc[nuts3.country == cntry] - transfer = vtransfer.Shapes2Shapes( - group, nuts3_cntry.geometry, normed=False - ).T.tocsr() + transfer = shapes_to_shapes(group, nuts3_cntry.geometry).T.tocsr() gdp_n = pd.Series( transfer.dot(nuts3_cntry["gdp"].fillna(1.0).values), index=group.index ) @@ -295,57 +357,56 @@ def update_transmission_costs(n, costs, length_factor=1.0): def attach_wind_and_solar( - n, costs, input_profiles, technologies, extendable_carriers, line_length_factor=1 + n, costs, input_profiles, carriers, extendable_carriers, line_length_factor=1 ): - # TODO: rename tech -> carrier, technologies -> carriers - _add_missing_carriers_from_costs(n, costs, technologies) + add_missing_carriers(n, carriers) - for tech in technologies: - if tech == "hydro": + for car in carriers: + if car == "hydro": continue - with xr.open_dataset(getattr(input_profiles, "profile_" + tech)) as ds: + with xr.open_dataset(getattr(input_profiles, "profile_" + car)) as ds: if ds.indexes["bus"].empty: continue - suptech = tech.split("-", 2)[0] - if suptech == "offwind": + supcar = car.split("-", 2)[0] + if supcar == "offwind": underwater_fraction = ds["underwater_fraction"].to_pandas() connection_cost = ( line_length_factor * ds["average_distance"].to_pandas() * ( underwater_fraction - * costs.at[tech + "-connection-submarine", "capital_cost"] + * costs.at[car + "-connection-submarine", "capital_cost"] + (1.0 - underwater_fraction) - * costs.at[tech + "-connection-underground", "capital_cost"] + * costs.at[car + "-connection-underground", "capital_cost"] ) ) capital_cost = ( costs.at["offwind", "capital_cost"] - + costs.at[tech + "-station", "capital_cost"] + + costs.at[car + "-station", "capital_cost"] + connection_cost ) logger.info( "Added connection cost of {:0.0f}-{:0.0f} Eur/MW/a to {}".format( - connection_cost.min(), connection_cost.max(), tech + connection_cost.min(), connection_cost.max(), car ) ) else: - capital_cost = costs.at[tech, "capital_cost"] + capital_cost = costs.at[car, "capital_cost"] n.madd( "Generator", ds.indexes["bus"], - " " + tech, + " " + car, bus=ds.indexes["bus"], - carrier=tech, - p_nom_extendable=tech in extendable_carriers["Generator"], + carrier=car, + p_nom_extendable=car in extendable_carriers["Generator"], p_nom_max=ds["p_nom_max"].to_pandas(), weight=ds["weight"].to_pandas(), - marginal_cost=costs.at[suptech, "marginal_cost"], + marginal_cost=costs.at[supcar, "marginal_cost"], capital_cost=capital_cost, - efficiency=costs.at[suptech, "efficiency"], + efficiency=costs.at[supcar, "efficiency"], p_max_pu=ds["profile"].transpose("time", "bus").to_pandas(), ) @@ -356,11 +417,19 @@ def attach_conventional_generators( ppl, conventional_carriers, extendable_carriers, - conventional_config, + conventional_params, conventional_inputs, ): - carriers = set(conventional_carriers) | set(extendable_carriers["Generator"]) - _add_missing_carriers_from_costs(n, costs, carriers) + carriers = list(set(conventional_carriers) | set(extendable_carriers["Generator"])) + add_missing_carriers(n, carriers) + add_co2_emissions(n, costs, carriers) + + # Replace carrier "natural gas" with the respective technology (OCGT or + # CCGT) to align with PyPSA names of "carriers" and avoid filtering "natural + # gas" powerplants in ppl.query("carrier in @carriers") + ppl.loc[ppl["carrier"] == "natural gas", "carrier"] = ppl.loc[ + ppl["carrier"] == "natural gas", "technology" + ] ppl = ( ppl.query("carrier in @carriers") @@ -393,17 +462,19 @@ def attach_conventional_generators( lifetime=(ppl.dateout - ppl.datein).fillna(np.inf), ) - for carrier in conventional_config: + for carrier in conventional_params: # Generators with technology affected idx = n.generators.query("carrier == @carrier").index - for attr in list(set(conventional_config[carrier]) & set(n.generators)): - values = conventional_config[carrier][attr] + for attr in list(set(conventional_params[carrier]) & set(n.generators)): + values = conventional_params[carrier][attr] if f"conventional_{carrier}_{attr}" in conventional_inputs: # Values affecting generators of technology k country-specific # First map generator buses to countries; then map countries to p_max_pu - values = pd.read_csv(values, index_col=0).iloc[:, 0] + values = pd.read_csv( + snakemake.input[f"conventional_{carrier}_{attr}"], index_col=0 + ).iloc[:, 0] bus_values = n.buses.country.map(values) n.generators[attr].update( n.generators.loc[idx].bus.map(bus_values).dropna() @@ -413,8 +484,9 @@ def attach_conventional_generators( n.generators.loc[idx, attr] = values -def attach_hydro(n, costs, ppl, profile_hydro, hydro_capacities, carriers, **config): - _add_missing_carriers_from_costs(n, costs, carriers) +def attach_hydro(n, costs, ppl, profile_hydro, hydro_capacities, carriers, **params): + add_missing_carriers(n, carriers) + add_co2_emissions(n, costs, carriers) ppl = ( ppl.query('carrier == "hydro"') @@ -468,9 +540,9 @@ def attach_hydro(n, costs, ppl, profile_hydro, hydro_capacities, carriers, **con ) if "PHS" in carriers and not phs.empty: - # fill missing max hours to config value and + # fill missing max hours to params value and # assume no natural inflow due to lack of data - max_hours = config.get("PHS_max_hours", 6) + max_hours = params.get("PHS_max_hours", 6) phs = phs.replace({"max_hours": {0: max_hours}}) n.madd( "StorageUnit", @@ -486,7 +558,7 @@ def attach_hydro(n, costs, ppl, profile_hydro, hydro_capacities, carriers, **con ) if "hydro" in carriers and not hydro.empty: - hydro_max_hours = config.get("hydro_max_hours") + hydro_max_hours = params.get("hydro_max_hours") assert hydro_max_hours is not None, "No path for hydro capacities given." @@ -546,7 +618,8 @@ def attach_extendable_generators(n, costs, ppl, carriers): logger.warning( "The function `attach_extendable_generators` is deprecated in v0.5.0." ) - _add_missing_carriers_from_costs(n, costs, carriers) + add_missing_carriers(n, carriers) + add_co2_emissions(n, costs, carriers) for tech in carriers: if tech.startswith("OCGT"): @@ -628,7 +701,7 @@ def attach_OPSD_renewables(n, tech_map): buses = n.buses.loc[gens.bus.unique()] gens_per_bus = gens.groupby("bus").p_nom.count() - caps = map_country_bus(df.query("Fueltype == @fueltype"), buses) + caps = map_country_bus(df.query("Fueltype == @fueltype and lat == lat"), buses) caps = caps.groupby(["bus"]).Capacity.sum() caps = caps / gens_per_bus.reindex(caps.index, fill_value=1) @@ -636,16 +709,7 @@ def attach_OPSD_renewables(n, tech_map): n.generators.p_nom_min.update(gens.bus.map(caps).dropna()) -def estimate_renewable_capacities(n, config): - year = config["electricity"]["estimate_renewable_capacities"]["year"] - tech_map = config["electricity"]["estimate_renewable_capacities"][ - "technology_mapping" - ] - countries = config["countries"] - expansion_limit = config["electricity"]["estimate_renewable_capacities"][ - "expansion_limit" - ] - +def estimate_renewable_capacities(n, year, tech_map, expansion_limit, countries): if not len(countries) or not len(tech_map): return @@ -686,19 +750,28 @@ def estimate_renewable_capacities(n, config): ) -def add_nice_carrier_names(n, config): - carrier_i = n.carriers.index - nice_names = ( - pd.Series(config["plotting"]["nice_names"]) - .reindex(carrier_i) - .fillna(carrier_i.to_series().str.title()) - ) - n.carriers["nice_name"] = nice_names - colors = pd.Series(config["plotting"]["tech_colors"]).reindex(carrier_i) - if colors.isna().any(): - missing_i = list(colors.index[colors.isna()]) - logger.warning(f"tech_colors for carriers {missing_i} not defined in config.") - n.carriers["color"] = colors +def attach_line_rating( + n, rating, s_max_pu, correction_factor, max_voltage_difference, max_line_rating +): + # TODO: Only considers overhead lines + n.lines_t.s_max_pu = (rating / n.lines.s_nom[rating.columns]) * correction_factor + if max_voltage_difference: + x_pu = ( + n.lines.type.map(n.line_types["x_per_length"]) + * n.lines.length + / (n.lines.v_nom**2) + ) + # need to clip here as cap values might be below 1 + # -> would mean the line cannot be operated at actual given pessimistic ampacity + s_max_pu_cap = ( + np.deg2rad(max_voltage_difference) / (x_pu * n.lines.s_nom) + ).clip(lower=1) + n.lines_t.s_max_pu = n.lines_t.s_max_pu.clip( + lower=1, upper=s_max_pu_cap, axis=1 + ) + if max_line_rating: + n.lines_t.s_max_pu = n.lines_t.s_max_pu.clip(upper=max_line_rating) + n.lines_t.s_max_pu *= s_max_pu if __name__ == "__main__": @@ -708,48 +781,33 @@ def add_nice_carrier_names(n, config): snakemake = mock_snakemake("add_electricity") configure_logging(snakemake) + params = snakemake.params + n = pypsa.Network(snakemake.input.base_network) Nyears = n.snapshot_weightings.objective.sum() / 8760.0 costs = load_costs( snakemake.input.tech_costs, - snakemake.config["costs"], - snakemake.config["electricity"], + params.costs, + params.electricity["max_hours"], Nyears, ) ppl = load_powerplants(snakemake.input.powerplants) - if "renewable_carriers" in snakemake.config["electricity"]: - renewable_carriers = set(snakemake.config["electricity"]["renewable_carriers"]) - else: - logger.warning( - "Missing key `renewable_carriers` under config entry `electricity`. " - "In future versions, this will raise an error. " - "Falling back to carriers listed under `renewable`." - ) - renewable_carriers = snakemake.config["renewable"] - - extendable_carriers = snakemake.config["electricity"]["extendable_carriers"] - if not (set(renewable_carriers) & set(extendable_carriers["Generator"])): - logger.warning( - "No renewables found in config entry `extendable_carriers`. " - "In future versions, these have to be explicitly listed. " - "Falling back to all renewables." - ) - - conventional_carriers = snakemake.config["electricity"]["conventional_carriers"] - attach_load( n, snakemake.input.regions, snakemake.input.load, snakemake.input.nuts3_shapes, - snakemake.config["countries"], - snakemake.config["load"]["scaling_factor"], + params.countries, + params.scaling_factor, ) - update_transmission_costs(n, costs, snakemake.config["lines"]["length_factor"]) + update_transmission_costs(n, costs, params.length_factor) + renewable_carriers = set(params.electricity["renewable_carriers"]) + extendable_carriers = params.electricity["extendable_carriers"] + conventional_carriers = params.electricity["conventional_carriers"] conventional_inputs = { k: v for k, v in snakemake.input.items() if k.startswith("conventional_") } @@ -759,7 +817,7 @@ def add_nice_carrier_names(n, config): ppl, conventional_carriers, extendable_carriers, - snakemake.config.get("conventional", {}), + params.conventional, conventional_inputs, ) @@ -769,71 +827,53 @@ def add_nice_carrier_names(n, config): snakemake.input, renewable_carriers, extendable_carriers, - snakemake.config["lines"]["length_factor"], + params.length_factor, ) if "hydro" in renewable_carriers: - conf = snakemake.config["renewable"]["hydro"] + para = params.renewable["hydro"] attach_hydro( n, costs, ppl, snakemake.input.profile_hydro, snakemake.input.hydro_capacities, - conf.pop("carriers", []), - **conf, - ) - - if "estimate_renewable_capacities" not in snakemake.config["electricity"]: - logger.warning( - "Missing key `estimate_renewable_capacities` under config entry `electricity`. " - "In future versions, this will raise an error. " - "Falling back to whether ``estimate_renewable_capacities_from_capacity_stats`` is in the config." - ) - if ( - "estimate_renewable_capacities_from_capacity_stats" - in snakemake.config["electricity"] - ): - estimate_renewable_caps = { - "enable": True, - **snakemake.config["electricity"][ - "estimate_renewable_capacities_from_capacity_stats" - ], - } - else: - estimate_renewable_caps = {"enable": False} - else: - estimate_renewable_caps = snakemake.config["electricity"][ - "estimate_renewable_capacities" - ] - if "enable" not in estimate_renewable_caps: - logger.warning( - "Missing key `enable` under config entry `estimate_renewable_capacities`. " - "In future versions, this will raise an error. Falling back to False." + para.pop("carriers", []), + **para, ) - estimate_renewable_caps = {"enable": False} - if "from_opsd" not in estimate_renewable_caps: - logger.warning( - "Missing key `from_opsd` under config entry `estimate_renewable_capacities`. " - "In future versions, this will raise an error. " - "Falling back to whether `renewable_capacities_from_opsd` is non-empty." - ) - from_opsd = bool( - snakemake.config["electricity"].get("renewable_capacities_from_opsd", False) - ) - estimate_renewable_caps["from_opsd"] = from_opsd + estimate_renewable_caps = params.electricity["estimate_renewable_capacities"] if estimate_renewable_caps["enable"]: + tech_map = estimate_renewable_caps["technology_mapping"] + expansion_limit = estimate_renewable_caps["expansion_limit"] + year = estimate_renewable_caps["year"] + if estimate_renewable_caps["from_opsd"]: - tech_map = snakemake.config["electricity"]["estimate_renewable_capacities"][ - "technology_mapping" - ] attach_OPSD_renewables(n, tech_map) - estimate_renewable_capacities(n, snakemake.config) + estimate_renewable_capacities( + n, year, tech_map, expansion_limit, params.countries + ) update_p_nom_max(n) - add_nice_carrier_names(n, snakemake.config) + line_rating_config = snakemake.config["lines"]["dynamic_line_rating"] + if line_rating_config["activate"]: + rating = xr.open_dataarray(snakemake.input.line_rating).to_pandas().transpose() + s_max_pu = snakemake.config["lines"]["s_max_pu"] + correction_factor = line_rating_config["correction_factor"] + max_voltage_difference = line_rating_config["max_voltage_difference"] + max_line_rating = line_rating_config["max_line_rating"] + + attach_line_rating( + n, + rating, + s_max_pu, + correction_factor, + max_voltage_difference, + max_line_rating, + ) + + sanitize_carriers(n, snakemake.config) n.meta = snakemake.config n.export_to_netcdf(snakemake.output[0]) diff --git a/scripts/add_existing_baseyear.py b/scripts/add_existing_baseyear.py index a81d606d8..b2c534e6b 100644 --- a/scripts/add_existing_baseyear.py +++ b/scripts/add_existing_baseyear.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Adds existing power and heat generation capacities for initial planning horizon. @@ -22,7 +21,8 @@ import numpy as np import pypsa import xarray as xr -from _helpers import override_component_attrs, update_config_with_sector_opts +from _helpers import update_config_with_sector_opts +from add_electricity import sanitize_carriers from prepare_sector_network import cluster_heat_buses, define_spatial, prepare_costs cc = coco.CountryConverter() @@ -38,7 +38,6 @@ def add_build_year_to_new_assets(n, baseyear): baseyear : int year in which optimized assets are built """ - # Give assets with lifetimes and no build year the build year baseyear for c in n.iterate_components(["Link", "Generator", "Store"]): assets = c.df.index[(c.df.lifetime != np.inf) & (c.df.build_year == 0)] @@ -62,7 +61,6 @@ def add_existing_renewables(df_agg): Append existing renewables to the df_agg pd.DataFrame with the conventional power plants. """ - carriers = {"solar": "solar", "onwind": "onwind", "offwind": "offwind-ac"} for tech in ["solar", "onwind", "offwind"]: @@ -131,10 +129,14 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas "Oil": "oil", "OCGT": "OCGT", "CCGT": "CCGT", - "Natural Gas": "gas", "Bioenergy": "urban central solid biomass CHP", } + # Replace Fueltype "Natural Gas" with the respective technology (OCGT or CCGT) + df_agg.loc[df_agg["Fueltype"] == "Natural Gas", "Fueltype"] = df_agg.loc[ + df_agg["Fueltype"] == "Natural Gas", "Technology" + ] + fueltype_to_drop = [ "Hydro", "Wind", @@ -160,7 +162,7 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas # Fill missing DateOut dateout = ( df_agg.loc[biomass_i, "DateIn"] - + snakemake.config["costs"]["fill_values"]["lifetime"] + + snakemake.params.costs["fill_values"]["lifetime"] ) df_agg.loc[biomass_i, "DateOut"] = df_agg.loc[biomass_i, "DateOut"].fillna(dateout) @@ -221,7 +223,7 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas capacity = df.loc[grouping_year, generator] capacity = capacity[~capacity.isna()] capacity = capacity[ - capacity > snakemake.config["existing_capacities"]["threshold_capacity"] + capacity > snakemake.params.existing_capacities["threshold_capacity"] ] suffix = "-ac" if generator == "offwind" else "" name_suffix = f" {generator}{suffix}-{grouping_year}" @@ -585,7 +587,7 @@ def add_heating_capacities_installed_before_baseyear( ) # delete links with capacities below threshold - threshold = snakemake.config["existing_capacities"]["threshold_capacity"] + threshold = snakemake.params.existing_capacities["threshold_capacity"] n.mremove( "Link", [ @@ -603,25 +605,26 @@ def add_heating_capacities_installed_before_baseyear( snakemake = mock_snakemake( "add_existing_baseyear", + configfiles="config/test/config.myopic.yaml", simpl="", - clusters="45", - ll="v1.0", + clusters="5", + ll="v1.5", opts="", - sector_opts="8760H-T-H-B-I-A-solar+p3-dist1", - planning_horizons=2020, + sector_opts="24H-T-H-B-I-A-solar+p3-dist1", + planning_horizons=2030, ) logging.basicConfig(level=snakemake.config["logging"]["level"]) update_config_with_sector_opts(snakemake.config, snakemake.wildcards.sector_opts) - options = snakemake.config["sector"] + options = snakemake.params.sector opts = snakemake.wildcards.sector_opts.split("-") - baseyear = snakemake.config["scenario"]["planning_horizons"][0] + baseyear = snakemake.params.baseyear + + n = pypsa.Network(snakemake.input.network) - overrides = override_component_attrs(snakemake.input.overrides) - n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides) # define spatial resolution of carriers spatial = define_spatial(n.buses[n.buses.carrier == "AC"].index, options) add_build_year_to_new_assets(n, baseyear) @@ -629,14 +632,12 @@ def add_heating_capacities_installed_before_baseyear( Nyears = n.snapshot_weightings.generators.sum() / 8760.0 costs = prepare_costs( snakemake.input.costs, - snakemake.config["costs"], + snakemake.params.costs, Nyears, ) - grouping_years_power = snakemake.config["existing_capacities"][ - "grouping_years_power" - ] - grouping_years_heat = snakemake.config["existing_capacities"]["grouping_years_heat"] + grouping_years_power = snakemake.params.existing_capacities["grouping_years_power"] + grouping_years_heat = snakemake.params.existing_capacities["grouping_years_heat"] add_power_capacities_installed_before_baseyear( n, grouping_years_power, costs, baseyear ) @@ -653,7 +654,7 @@ def add_heating_capacities_installed_before_baseyear( .to_pandas() .reindex(index=n.snapshots) ) - default_lifetime = snakemake.config["costs"]["fill_values"]["lifetime"] + default_lifetime = snakemake.params.costs["fill_values"]["lifetime"] add_heating_capacities_installed_before_baseyear( n, baseyear, @@ -670,4 +671,6 @@ def add_heating_capacities_installed_before_baseyear( n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards))) + sanitize_carriers(n, snakemake.config) + n.export_to_netcdf(snakemake.output[0]) diff --git a/scripts/add_extra_components.py b/scripts/add_extra_components.py index b507148da..e00e1e5fa 100644 --- a/scripts/add_extra_components.py +++ b/scripts/add_extra_components.py @@ -27,7 +27,7 @@ Store: .. seealso:: - Documentation of the configuration file ``config.yaml`` at :ref:`costs_cf`, + Documentation of the configuration file ``config/config.yaml`` at :ref:`costs_cf`, :ref:`electricity_cf` Inputs @@ -44,7 +44,7 @@ Description ----------- -The rule :mod:`add_extra_components` attaches additional extendable components to the clustered and simplified network. These can be configured in the ``config.yaml`` at ``electricity: extendable_carriers:``. It processes ``networks/elec_s{simpl}_{clusters}.nc`` to build ``networks/elec_s{simpl}_{clusters}_ec.nc``, which in contrast to the former (depending on the configuration) contain with **zero** initial capacity +The rule :mod:`add_extra_components` attaches additional extendable components to the clustered and simplified network. These can be configured in the ``config/config.yaml`` at ``electricity: extendable_carriers:``. It processes ``networks/elec_s{simpl}_{clusters}.nc`` to build ``networks/elec_s{simpl}_{clusters}_ec.nc``, which in contrast to the former (depending on the configuration) contain with **zero** initial capacity - ``StorageUnits`` of carrier 'H2' and/or 'battery'. If this option is chosen, every bus is given an extendable ``StorageUnit`` of the corresponding carrier. The energy and power capacities are linked through a parameter that specifies the energy capacity as maximum hours at full dispatch power and is configured in ``electricity: max_hours:``. This linkage leads to one investment variable per storage unit. The default ``max_hours`` lead to long-term hydrogen and short-term battery storage units. @@ -56,22 +56,17 @@ import pandas as pd import pypsa from _helpers import configure_logging -from add_electricity import ( - _add_missing_carriers_from_costs, - add_nice_carrier_names, - load_costs, -) +from add_electricity import load_costs, sanitize_carriers idx = pd.IndexSlice logger = logging.getLogger(__name__) -def attach_storageunits(n, costs, elec_opts): - carriers = elec_opts["extendable_carriers"]["StorageUnit"] - max_hours = elec_opts["max_hours"] +def attach_storageunits(n, costs, extendable_carriers, max_hours): + carriers = extendable_carriers["StorageUnit"] - _add_missing_carriers_from_costs(n, costs, carriers) + n.madd("Carrier", carriers) buses_i = n.buses.index @@ -99,10 +94,10 @@ def attach_storageunits(n, costs, elec_opts): ) -def attach_stores(n, costs, elec_opts): - carriers = elec_opts["extendable_carriers"]["Store"] +def attach_stores(n, costs, extendable_carriers): + carriers = extendable_carriers["Store"] - _add_missing_carriers_from_costs(n, costs, carriers) + n.madd("Carrier", carriers) buses_i = n.buses.index bus_sub_dict = {k: n.buses[k].values for k in ["x", "y", "country"]} @@ -162,6 +157,8 @@ def attach_stores(n, costs, elec_opts): marginal_cost=costs.at["battery", "marginal_cost"], ) + n.madd("Carrier", ["battery charger", "battery discharger"]) + n.madd( "Link", b_buses_i + " charger", @@ -187,11 +184,10 @@ def attach_stores(n, costs, elec_opts): ) -def attach_hydrogen_pipelines(n, costs, elec_opts): - ext_carriers = elec_opts["extendable_carriers"] - as_stores = ext_carriers.get("Store", []) +def attach_hydrogen_pipelines(n, costs, extendable_carriers): + as_stores = extendable_carriers.get("Store", []) - if "H2 pipeline" not in ext_carriers.get("Link", []): + if "H2 pipeline" not in extendable_carriers.get("Link", []): return assert "H2" in as_stores, ( @@ -213,6 +209,8 @@ def attach_hydrogen_pipelines(n, costs, elec_opts): h2_links.index = h2_links.apply(lambda c: f"H2 pipeline {c.bus0}-{c.bus1}", axis=1) # add pipelines + n.add("Carrier", "H2 pipeline") + n.madd( "Link", h2_links.index, @@ -235,18 +233,19 @@ def attach_hydrogen_pipelines(n, costs, elec_opts): configure_logging(snakemake) n = pypsa.Network(snakemake.input.network) - elec_config = snakemake.config["electricity"] + extendable_carriers = snakemake.params.extendable_carriers + max_hours = snakemake.params.max_hours Nyears = n.snapshot_weightings.objective.sum() / 8760.0 costs = load_costs( - snakemake.input.tech_costs, snakemake.config["costs"], elec_config, Nyears + snakemake.input.tech_costs, snakemake.params.costs, max_hours, Nyears ) - attach_storageunits(n, costs, elec_config) - attach_stores(n, costs, elec_config) - attach_hydrogen_pipelines(n, costs, elec_config) + attach_storageunits(n, costs, extendable_carriers, max_hours) + attach_stores(n, costs, extendable_carriers) + attach_hydrogen_pipelines(n, costs, extendable_carriers) - add_nice_carrier_names(n, snakemake.config) + sanitize_carriers(n, snakemake.config) n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards))) n.export_to_netcdf(snakemake.output[0]) diff --git a/scripts/base_network.py b/scripts/base_network.py index 24097b1d4..87504ce7c 100644 --- a/scripts/base_network.py +++ b/scripts/base_network.py @@ -38,7 +38,7 @@ type: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`snapshots_cf`, :ref:`toplevel_cf`, :ref:`electricity_cf`, :ref:`load_cf`, :ref:`lines_cf`, :ref:`links_cf`, :ref:`transformers_cf` @@ -714,6 +714,7 @@ def base_network( n.name = "PyPSA-Eur" n.set_snapshots(pd.date_range(freq="h", **config["snapshots"])) + n.madd("Carrier", ["AC", "DC"]) n.import_components_from_dataframe(buses, "Bus") n.import_components_from_dataframe(lines, "Line") diff --git a/scripts/build_ammonia_production.py b/scripts/build_ammonia_production.py index d78d627eb..1bcdf9ae5 100644 --- a/scripts/build_ammonia_production.py +++ b/scripts/build_ammonia_production.py @@ -30,7 +30,7 @@ ammonia.index = cc.convert(ammonia.index, to="iso2") years = [str(i) for i in range(2013, 2018)] - countries = ammonia.index.intersection(snakemake.config["countries"]) + countries = ammonia.index.intersection(snakemake.params.countries) ammonia = ammonia.loc[countries, years].astype(float) # convert from ktonN to ktonNH3 diff --git a/scripts/build_biomass_potentials.py b/scripts/build_biomass_potentials.py index 7387418af..d200a78e4 100644 --- a/scripts/build_biomass_potentials.py +++ b/scripts/build_biomass_potentials.py @@ -68,7 +68,6 @@ def enspreso_biomass_potentials(year=2020, scenario="ENS_Low"): Biomass potentials for given year and scenario in TWh/a by commodity and NUTS2 region. """ - glossary = pd.read_excel( str(snakemake.input.enspreso_biomass), sheet_name="Glossary", @@ -124,7 +123,6 @@ def disaggregate_nuts0(bio): ------- pd.DataFrame """ - pop = build_nuts_population_data() # get population in nuts2 @@ -149,7 +147,6 @@ def build_nuts2_shapes(): - add RS, AL, BA country shapes (not covered in NUTS 2013) - consistently name ME, MK """ - nuts2 = gpd.GeoDataFrame( gpd.read_file(snakemake.input.nuts2).set_index("id").geometry ) @@ -186,7 +183,6 @@ def convert_nuts2_to_regions(bio_nuts2, regions): ------- gpd.GeoDataFrame """ - # calculate area of nuts2 regions bio_nuts2["area_nuts2"] = area(bio_nuts2) @@ -201,7 +197,7 @@ def convert_nuts2_to_regions(bio_nuts2, regions): ) overlay[adjust_cols] = overlay[adjust_cols].multiply(overlay["share"], axis=0) - bio_regions = overlay.groupby("name").sum() + bio_regions = overlay.dissolve("name", aggfunc="sum") bio_regions.drop(["area_nuts2", "share"], axis=1, inplace=True) @@ -214,9 +210,9 @@ def convert_nuts2_to_regions(bio_nuts2, regions): snakemake = mock_snakemake("build_biomass_potentials", simpl="", clusters="5") - config = snakemake.config["biomass"] - year = config["year"] - scenario = config["scenario"] + params = snakemake.params.biomass + year = params["year"] + scenario = params["scenario"] enspreso = enspreso_biomass_potentials(year, scenario) @@ -232,7 +228,7 @@ def convert_nuts2_to_regions(bio_nuts2, regions): df.to_csv(snakemake.output.biomass_potentials_all) - grouper = {v: k for k, vv in config["classes"].items() for v in vv} + grouper = {v: k for k, vv in params["classes"].items() for v in vv} df = df.groupby(grouper, axis=1).sum() df *= 1e6 # TWh/a to MWh/a diff --git a/scripts/build_biomass_transport_costs.py b/scripts/build_biomass_transport_costs.py index 8b6b69275..9271b6002 100644 --- a/scripts/build_biomass_transport_costs.py +++ b/scripts/build_biomass_transport_costs.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Reads biomass transport costs for different countries of the JRC report. diff --git a/scripts/build_bus_regions.py b/scripts/build_bus_regions.py index f1a0558a2..a6500bb08 100644 --- a/scripts/build_bus_regions.py +++ b/scripts/build_bus_regions.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Creates Voronoi shapes for each bus representing both onshore and offshore regions. @@ -15,7 +14,7 @@ countries: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`toplevel_cf` Inputs @@ -57,9 +56,10 @@ def voronoi_partition_pts(points, outline): """ - Compute the polygons of a voronoi partition of `points` within the - polygon `outline`. Taken from - https://github.com/FRESNA/vresutils/blob/master/vresutils/graph.py + Compute the polygons of a voronoi partition of `points` within the polygon + `outline`. Taken from + https://github.com/FRESNA/vresutils/blob/master/vresutils/graph.py. + Attributes ---------- points : Nx2 - ndarray[dtype=float] @@ -116,7 +116,7 @@ def voronoi_partition_pts(points, outline): snakemake = mock_snakemake("build_bus_regions") configure_logging(snakemake) - countries = snakemake.config["countries"] + countries = snakemake.params.countries n = pypsa.Network(snakemake.input.base_network) diff --git a/scripts/build_clustered_population_layouts.py b/scripts/build_clustered_population_layouts.py index bc81c29a1..083f3de46 100644 --- a/scripts/build_clustered_population_layouts.py +++ b/scripts/build_clustered_population_layouts.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build population layouts for all clustered model regions as total as well as split by urban and rural population. diff --git a/scripts/build_cop_profiles.py b/scripts/build_cop_profiles.py index fa04e4a1c..4b1d952ea 100644 --- a/scripts/build_cop_profiles.py +++ b/scripts/build_cop_profiles.py @@ -2,13 +2,12 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build coefficient of performance (COP) time series for air- or ground-sourced heat pumps. -The COP is a function of the temperature difference between -source and sink. +The COP is a function of the temperature difference between source and +sink. The quadratic regression used is based on Staffell et al. (2012) https://doi.org/10.1039/C2EE22653G. @@ -40,7 +39,7 @@ def coefficient_of_performance(delta_T, source="air"): for source in ["air", "soil"]: source_T = xr.open_dataarray(snakemake.input[f"temp_{source}_{area}"]) - delta_T = snakemake.config["sector"]["heat_pump_sink_T"] - source_T + delta_T = snakemake.params.heat_pump_sink_T - source_T cop = coefficient_of_performance(delta_T, source) diff --git a/scripts/build_cutout.py b/scripts/build_cutout.py index fd148cacb..9a7f9e008 100644 --- a/scripts/build_cutout.py +++ b/scripts/build_cutout.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Create cutouts with `atlite `_. @@ -26,7 +25,7 @@ {cutout}: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`atlite_cf` Inputs @@ -107,9 +106,9 @@ snakemake = mock_snakemake("build_cutout", cutout="europe-2013-era5") configure_logging(snakemake) - cutout_params = snakemake.config["atlite"]["cutouts"][snakemake.wildcards.cutout] + cutout_params = snakemake.params.cutouts[snakemake.wildcards.cutout] - snapshots = pd.date_range(freq="h", **snakemake.config["snapshots"]) + snapshots = pd.date_range(freq="h", **snakemake.params.snapshots) time = [snapshots[0], snapshots[-1]] cutout_params["time"] = slice(*cutout_params.get("time", time)) diff --git a/scripts/build_load_data.py b/scripts/build_electricity_demand.py similarity index 94% rename from scripts/build_load_data.py rename to scripts/build_electricity_demand.py index 01e3fb1e0..ba1fb8817 100755 --- a/scripts/build_load_data.py +++ b/scripts/build_electricity_demand.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020 @JanFrederickUnnewehr, The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ This rule downloads the load data from `Open Power System Data Time series. @@ -26,7 +25,7 @@ .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`load_cf` Inputs @@ -276,20 +275,20 @@ def manual_adjustment(load, fn_load, powerstatistics): if "snakemake" not in globals(): from _helpers import mock_snakemake - snakemake = mock_snakemake("build_load_data") + snakemake = mock_snakemake("build_electricity_demand") configure_logging(snakemake) - powerstatistics = snakemake.config["load"]["power_statistics"] - interpolate_limit = snakemake.config["load"]["interpolate_limit"] - countries = snakemake.config["countries"] - snapshots = pd.date_range(freq="h", **snakemake.config["snapshots"]) + powerstatistics = snakemake.params.load["power_statistics"] + interpolate_limit = snakemake.params.load["interpolate_limit"] + countries = snakemake.params.countries + snapshots = pd.date_range(freq="h", **snakemake.params.snapshots) years = slice(snapshots[0], snapshots[-1]) - time_shift = snakemake.config["load"]["time_shift_for_large_gaps"] + time_shift = snakemake.params.load["time_shift_for_large_gaps"] load = load_timeseries(snakemake.input[0], years, countries, powerstatistics) - if snakemake.config["load"]["manual_adjustments"]: + if snakemake.params.load["manual_adjustments"]: load = manual_adjustment(load, snakemake.input[0], powerstatistics) logger.info(f"Linearly interpolate gaps of size {interpolate_limit} and less.") diff --git a/scripts/build_energy_totals.py b/scripts/build_energy_totals.py index 1480732ae..891c4e2a9 100644 --- a/scripts/build_energy_totals.py +++ b/scripts/build_energy_totals.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build total energy demands per country using JRC IDEES, eurostat, and EEA data. """ @@ -124,7 +123,6 @@ def build_eurostat(input_eurostat, countries, report_year, year): """ Return multi-index for all countries' energy data in TWh/a. """ - filenames = { 2016: f"/{year}-Energy-Balances-June2016edition.xlsx", 2017: f"/{year}-ENERGY-BALANCES-June2017edition.xlsx", @@ -163,7 +161,6 @@ def build_swiss(year): """ Return a pd.Series of Swiss energy data in TWh/a. """ - fn = snakemake.input.swiss df = pd.read_csv(fn, index_col=[0, 1]).loc["CH", str(year)] @@ -740,16 +737,16 @@ def build_transport_data(countries, population, idees): logging.basicConfig(level=snakemake.config["logging"]["level"]) - config = snakemake.config["energy"] + params = snakemake.params.energy nuts3 = gpd.read_file(snakemake.input.nuts3_shapes).set_index("index") population = nuts3["pop"].groupby(nuts3.country).sum() - countries = snakemake.config["countries"] + countries = snakemake.params.countries idees_countries = pd.Index(countries).intersection(eu28) - data_year = config["energy_totals_year"] - report_year = snakemake.config["energy"]["eurostat_report_year"] + data_year = params["energy_totals_year"] + report_year = snakemake.params.energy["eurostat_report_year"] input_eurostat = snakemake.input.eurostat eurostat = build_eurostat(input_eurostat, countries, report_year, data_year) swiss = build_swiss(data_year) @@ -758,8 +755,8 @@ def build_transport_data(countries, population, idees): energy = build_energy_totals(countries, eurostat, swiss, idees) energy.to_csv(snakemake.output.energy_name) - base_year_emissions = config["base_emissions_year"] - emissions_scope = snakemake.config["energy"]["emissions"] + base_year_emissions = params["base_emissions_year"] + emissions_scope = snakemake.params.energy["emissions"] eea_co2 = build_eea_co2(snakemake.input.co2, base_year_emissions, emissions_scope) eurostat_co2 = build_eurostat_co2( input_eurostat, countries, report_year, base_year_emissions diff --git a/scripts/build_gas_input_locations.py b/scripts/build_gas_input_locations.py index 314cb767d..a3b945abc 100644 --- a/scripts/build_gas_input_locations.py +++ b/scripts/build_gas_input_locations.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2021-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build import locations for fossil gas from entry-points, LNG terminals and production sites with data from SciGRID_gas and Global Energy Monitor. diff --git a/scripts/build_gas_network.py b/scripts/build_gas_network.py index b34ebe9fc..23f58caa4 100644 --- a/scripts/build_gas_network.py +++ b/scripts/build_gas_network.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Preprocess gas network based on data from bthe SciGRID_gas project (https://www.gas.scigrid.de/). @@ -22,14 +21,14 @@ def diameter_to_capacity(pipe_diameter_mm): """ Calculate pipe capacity in MW based on diameter in mm. - 20 inch (500 mm) 50 bar -> 1.5 GW CH4 pipe capacity (LHV) - 24 inch (600 mm) 50 bar -> 5 GW CH4 pipe capacity (LHV) - 36 inch (900 mm) 50 bar -> 11.25 GW CH4 pipe capacity (LHV) - 48 inch (1200 mm) 80 bar -> 21.7 GW CH4 pipe capacity (LHV) + 20 inch (500 mm) 50 bar -> 1.5 GW CH4 pipe capacity (LHV) 24 inch + (600 mm) 50 bar -> 5 GW CH4 pipe capacity (LHV) 36 inch (900 + mm) 50 bar -> 11.25 GW CH4 pipe capacity (LHV) 48 inch (1200 mm) 80 + bar -> 21.7 GW CH4 pipe capacity (LHV) - Based on p.15 of https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf + Based on p.15 of + https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf """ - # slopes definitions m0 = (1500 - 0) / (500 - 0) m1 = (5000 - 1500) / (600 - 500) diff --git a/scripts/build_heat_demand.py b/scripts/build_heat_demand.py index 6164d25d4..734942600 100644 --- a/scripts/build_heat_demand.py +++ b/scripts/build_heat_demand.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build heat demand time series using heating degree day (HDD) approximation. """ @@ -28,7 +27,7 @@ cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1) client = Client(cluster, asynchronous=True) - time = pd.date_range(freq="h", **snakemake.config["snapshots"]) + time = pd.date_range(freq="h", **snakemake.params.snapshots) cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time) clustered_regions = ( diff --git a/scripts/build_hydro_profile.py b/scripts/build_hydro_profile.py index 279bd7a18..bed666f20 100644 --- a/scripts/build_hydro_profile.py +++ b/scripts/build_hydro_profile.py @@ -4,7 +4,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build hydroelectric inflow time-series for each country. @@ -21,7 +20,7 @@ clip_min_inflow: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`toplevel_cf`, :ref:`renewable_cf` Inputs @@ -131,10 +130,10 @@ def get_eia_annual_hydro_generation(fn, countries): snakemake = mock_snakemake("build_hydro_profile") configure_logging(snakemake) - config_hydro = snakemake.config["renewable"]["hydro"] + params_hydro = snakemake.params.hydro cutout = atlite.Cutout(snakemake.input.cutout) - countries = snakemake.config["countries"] + countries = snakemake.params.countries country_shapes = ( gpd.read_file(snakemake.input.country_shapes) .set_index("name")["geometry"] @@ -152,7 +151,7 @@ def get_eia_annual_hydro_generation(fn, countries): normalize_using_yearly=eia_stats, ) - if "clip_min_inflow" in config_hydro: - inflow = inflow.where(inflow > config_hydro["clip_min_inflow"], 0) + if "clip_min_inflow" in params_hydro: + inflow = inflow.where(inflow > params_hydro["clip_min_inflow"], 0) inflow.to_netcdf(snakemake.output[0]) diff --git a/scripts/build_industrial_distribution_key.py b/scripts/build_industrial_distribution_key.py index 5f2f6893b..e93e43c2d 100644 --- a/scripts/build_industrial_distribution_key.py +++ b/scripts/build_industrial_distribution_key.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build spatial distribution of industries from Hotmaps database. """ @@ -27,7 +26,6 @@ def locate_missing_industrial_sites(df): Should only be used if the model's spatial resolution is coarser than individual cities. """ - try: from geopy.extra.rate_limiter import RateLimiter from geopy.geocoders import Nominatim @@ -71,12 +69,11 @@ def prepare_hotmaps_database(regions): """ Load hotmaps database of industrial sites and map onto bus regions. """ - df = pd.read_csv(snakemake.input.hotmaps_industrial_database, sep=";", index_col=0) df[["srid", "coordinates"]] = df.geom.str.split(";", expand=True) - if snakemake.config["industry"].get("hotmaps_locate_missing", False): + if snakemake.params.hotmaps_locate_missing: df = locate_missing_industrial_sites(df) # remove those sites without valid locations @@ -103,7 +100,6 @@ def build_nodal_distribution_key(hotmaps, regions, countries): """ Build nodal distribution keys for each sector. """ - sectors = hotmaps.Subsector.unique() keys = pd.DataFrame(index=regions.index, columns=sectors, dtype=float) @@ -147,7 +143,7 @@ def build_nodal_distribution_key(hotmaps, regions, countries): logging.basicConfig(level=snakemake.config["logging"]["level"]) - countries = snakemake.config["countries"] + countries = snakemake.params.countries regions = gpd.read_file(snakemake.input.regions_onshore).set_index("name") diff --git a/scripts/build_industrial_energy_demand_per_country_today.py b/scripts/build_industrial_energy_demand_per_country_today.py index 3fa9ef56f..9ca0d003d 100644 --- a/scripts/build_industrial_energy_demand_per_country_today.py +++ b/scripts/build_industrial_energy_demand_per_country_today.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build industrial energy demand per country. """ @@ -102,8 +101,8 @@ def add_ammonia_energy_demand(demand): def get_ammonia_by_fuel(x): fuels = { - "gas": config["MWh_CH4_per_tNH3_SMR"], - "electricity": config["MWh_elec_per_tNH3_SMR"], + "gas": params["MWh_CH4_per_tNH3_SMR"], + "electricity": params["MWh_elec_per_tNH3_SMR"], } return pd.Series({k: x * v for k, v in fuels.items()}) @@ -113,7 +112,7 @@ def get_ammonia_by_fuel(x): index=demand.index, fill_value=0.0 ) - ammonia = pd.DataFrame({"ammonia": ammonia * config["MWh_NH3_per_tNH3"]}).T + ammonia = pd.DataFrame({"ammonia": ammonia * params["MWh_NH3_per_tNH3"]}).T demand["Ammonia"] = ammonia.unstack().reindex(index=demand.index, fill_value=0.0) @@ -179,9 +178,9 @@ def industrial_energy_demand(countries, year): snakemake = mock_snakemake("build_industrial_energy_demand_per_country_today") - config = snakemake.config["industry"] - year = config.get("reference_year", 2015) - countries = pd.Index(snakemake.config["countries"]) + params = snakemake.params.industry + year = params.get("reference_year", 2015) + countries = pd.Index(snakemake.params.countries) demand = industrial_energy_demand(countries.intersection(eu28), year) diff --git a/scripts/build_industrial_energy_demand_per_node.py b/scripts/build_industrial_energy_demand_per_node.py index b75b2058e..55c10c5d6 100644 --- a/scripts/build_industrial_energy_demand_per_node.py +++ b/scripts/build_industrial_energy_demand_per_node.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build industrial energy demand per model region. """ diff --git a/scripts/build_industrial_energy_demand_per_node_today.py b/scripts/build_industrial_energy_demand_per_node_today.py index da1ec2d7a..d845e7046 100644 --- a/scripts/build_industrial_energy_demand_per_node_today.py +++ b/scripts/build_industrial_energy_demand_per_node_today.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build industrial energy demand per model region. """ diff --git a/scripts/build_industrial_production_per_country.py b/scripts/build_industrial_production_per_country.py index 8a4c19c24..74cb19497 100644 --- a/scripts/build_industrial_production_per_country.py +++ b/scripts/build_industrial_production_per_country.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build industrial production per country. """ @@ -247,7 +246,6 @@ def separate_basic_chemicals(demand, year): """ Separate basic chemicals into ammonia, chlorine, methanol and HVC. """ - ammonia = pd.read_csv(snakemake.input.ammonia_production, index_col=0) there = ammonia.index.intersection(demand.index) @@ -266,9 +264,9 @@ def separate_basic_chemicals(demand, year): # assume HVC, methanol, chlorine production proportional to non-ammonia basic chemicals distribution_key = demand["Basic chemicals"] / demand["Basic chemicals"].sum() - demand["HVC"] = config["HVC_production_today"] * 1e3 * distribution_key - demand["Chlorine"] = config["chlorine_production_today"] * 1e3 * distribution_key - demand["Methanol"] = config["methanol_production_today"] * 1e3 * distribution_key + demand["HVC"] = params["HVC_production_today"] * 1e3 * distribution_key + demand["Chlorine"] = params["chlorine_production_today"] * 1e3 * distribution_key + demand["Methanol"] = params["methanol_production_today"] * 1e3 * distribution_key demand.drop(columns=["Basic chemicals"], inplace=True) @@ -281,11 +279,11 @@ def separate_basic_chemicals(demand, year): logging.basicConfig(level=snakemake.config["logging"]["level"]) - countries = snakemake.config["countries"] + countries = snakemake.params.countries - year = snakemake.config["industry"]["reference_year"] + year = snakemake.params.industry["reference_year"] - config = snakemake.config["industry"] + params = snakemake.params.industry jrc_dir = snakemake.input.jrc eurostat_dir = snakemake.input.eurostat diff --git a/scripts/build_industrial_production_per_country_tomorrow.py b/scripts/build_industrial_production_per_country_tomorrow.py index e554e1599..ffed51952 100644 --- a/scripts/build_industrial_production_per_country_tomorrow.py +++ b/scripts/build_industrial_production_per_country_tomorrow.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build future industrial production per country. """ @@ -16,7 +15,7 @@ snakemake = mock_snakemake("build_industrial_production_per_country_tomorrow") - config = snakemake.config["industry"] + params = snakemake.params.industry investment_year = int(snakemake.wildcards.planning_horizons) @@ -26,8 +25,8 @@ keys = ["Integrated steelworks", "Electric arc"] total_steel = production[keys].sum(axis=1) - st_primary_fraction = get(config["St_primary_fraction"], investment_year) - dri_fraction = get(config["DRI_fraction"], investment_year) + st_primary_fraction = get(params["St_primary_fraction"], investment_year) + dri_fraction = get(params["DRI_fraction"], investment_year) int_steel = production["Integrated steelworks"].sum() fraction_persistent_primary = st_primary_fraction * total_steel.sum() / int_steel @@ -52,7 +51,7 @@ key_pri = "Aluminium - primary production" key_sec = "Aluminium - secondary production" - al_primary_fraction = get(config["Al_primary_fraction"], investment_year) + al_primary_fraction = get(params["Al_primary_fraction"], investment_year) fraction_persistent_primary = ( al_primary_fraction * total_aluminium.sum() / production[key_pri].sum() ) @@ -61,15 +60,15 @@ production[key_sec] = total_aluminium - production[key_pri] production["HVC (mechanical recycling)"] = ( - get(config["HVC_mechanical_recycling_fraction"], investment_year) + get(params["HVC_mechanical_recycling_fraction"], investment_year) * production["HVC"] ) production["HVC (chemical recycling)"] = ( - get(config["HVC_chemical_recycling_fraction"], investment_year) + get(params["HVC_chemical_recycling_fraction"], investment_year) * production["HVC"] ) - production["HVC"] *= get(config["HVC_primary_fraction"], investment_year) + production["HVC"] *= get(params["HVC_primary_fraction"], investment_year) fn = snakemake.output.industrial_production_per_country_tomorrow production.to_csv(fn, float_format="%.2f") diff --git a/scripts/build_industrial_production_per_node.py b/scripts/build_industrial_production_per_node.py index 7b40cb7c7..7b69948ad 100644 --- a/scripts/build_industrial_production_per_node.py +++ b/scripts/build_industrial_production_per_node.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build industrial production per model region. """ diff --git a/scripts/build_industry_sector_ratios.py b/scripts/build_industry_sector_ratios.py index 5f5f7b906..457050026 100644 --- a/scripts/build_industry_sector_ratios.py +++ b/scripts/build_industry_sector_ratios.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build specific energy consumption by carrier and industries. """ @@ -186,10 +185,10 @@ def iron_and_steel(): df[sector] = df["Electric arc"] # add H2 consumption for DRI at 1.7 MWh H2 /ton steel - df.at["hydrogen", sector] = config["H2_DRI"] + df.at["hydrogen", sector] = params["H2_DRI"] # add electricity consumption in DRI shaft (0.322 MWh/tSl) - df.at["elec", sector] += config["elec_DRI"] + df.at["elec", sector] += params["elec_DRI"] ## Integrated steelworks # could be used in combination with CCS) @@ -384,19 +383,19 @@ def chemicals_industry(): assert s_emi.index[0] == sector # convert from MtHVC/a to ktHVC/a - s_out = config["HVC_production_today"] * 1e3 + s_out = params["HVC_production_today"] * 1e3 # tCO2/t material df.loc["process emission", sector] += ( s_emi["Process emissions"] - - config["petrochemical_process_emissions"] * 1e3 - - config["NH3_process_emissions"] * 1e3 + - params["petrochemical_process_emissions"] * 1e3 + - params["NH3_process_emissions"] * 1e3 ) / s_out # emissions originating from feedstock, could be non-fossil origin # tCO2/t material df.loc["process emission from feedstock", sector] += ( - config["petrochemical_process_emissions"] * 1e3 + params["petrochemical_process_emissions"] * 1e3 ) / s_out # convert from ktoe/a to GWh/a @@ -406,18 +405,18 @@ def chemicals_industry(): # subtract ammonia energy demand (in ktNH3/a) ammonia = pd.read_csv(snakemake.input.ammonia_production, index_col=0) ammonia_total = ammonia.loc[ammonia.index.intersection(eu28), str(year)].sum() - df.loc["methane", sector] -= ammonia_total * config["MWh_CH4_per_tNH3_SMR"] - df.loc["elec", sector] -= ammonia_total * config["MWh_elec_per_tNH3_SMR"] + df.loc["methane", sector] -= ammonia_total * params["MWh_CH4_per_tNH3_SMR"] + df.loc["elec", sector] -= ammonia_total * params["MWh_elec_per_tNH3_SMR"] # subtract chlorine demand - chlorine_total = config["chlorine_production_today"] - df.loc["hydrogen", sector] -= chlorine_total * config["MWh_H2_per_tCl"] - df.loc["elec", sector] -= chlorine_total * config["MWh_elec_per_tCl"] + chlorine_total = params["chlorine_production_today"] + df.loc["hydrogen", sector] -= chlorine_total * params["MWh_H2_per_tCl"] + df.loc["elec", sector] -= chlorine_total * params["MWh_elec_per_tCl"] # subtract methanol demand - methanol_total = config["methanol_production_today"] - df.loc["methane", sector] -= methanol_total * config["MWh_CH4_per_tMeOH"] - df.loc["elec", sector] -= methanol_total * config["MWh_elec_per_tMeOH"] + methanol_total = params["methanol_production_today"] + df.loc["methane", sector] -= methanol_total * params["MWh_CH4_per_tMeOH"] + df.loc["elec", sector] -= methanol_total * params["MWh_elec_per_tMeOH"] # MWh/t material df.loc[sources, sector] = df.loc[sources, sector] / s_out @@ -428,37 +427,37 @@ def chemicals_industry(): sector = "HVC (mechanical recycling)" df[sector] = 0.0 - df.loc["elec", sector] = config["MWh_elec_per_tHVC_mechanical_recycling"] + df.loc["elec", sector] = params["MWh_elec_per_tHVC_mechanical_recycling"] # HVC chemical recycling sector = "HVC (chemical recycling)" df[sector] = 0.0 - df.loc["elec", sector] = config["MWh_elec_per_tHVC_chemical_recycling"] + df.loc["elec", sector] = params["MWh_elec_per_tHVC_chemical_recycling"] # Ammonia sector = "Ammonia" df[sector] = 0.0 - if snakemake.config["sector"].get("ammonia", False): - df.loc["ammonia", sector] = config["MWh_NH3_per_tNH3"] + if snakemake.params.ammonia: + df.loc["ammonia", sector] = params["MWh_NH3_per_tNH3"] else: - df.loc["hydrogen", sector] = config["MWh_H2_per_tNH3_electrolysis"] - df.loc["elec", sector] = config["MWh_elec_per_tNH3_electrolysis"] + df.loc["hydrogen", sector] = params["MWh_H2_per_tNH3_electrolysis"] + df.loc["elec", sector] = params["MWh_elec_per_tNH3_electrolysis"] # Chlorine sector = "Chlorine" df[sector] = 0.0 - df.loc["hydrogen", sector] = config["MWh_H2_per_tCl"] - df.loc["elec", sector] = config["MWh_elec_per_tCl"] + df.loc["hydrogen", sector] = params["MWh_H2_per_tCl"] + df.loc["elec", sector] = params["MWh_elec_per_tCl"] # Methanol sector = "Methanol" df[sector] = 0.0 - df.loc["methane", sector] = config["MWh_CH4_per_tMeOH"] - df.loc["elec", sector] = config["MWh_elec_per_tMeOH"] + df.loc["methane", sector] = params["MWh_CH4_per_tMeOH"] + df.loc["elec", sector] = params["MWh_elec_per_tMeOH"] # Other chemicals @@ -1466,10 +1465,10 @@ def other_industrial_sectors(): snakemake = mock_snakemake("build_industry_sector_ratios") - # TODO make config option + # TODO make params option year = 2015 - config = snakemake.config["industry"] + params = snakemake.params.industry df = pd.concat( [ diff --git a/scripts/build_line_rating.py b/scripts/build_line_rating.py new file mode 100755 index 000000000..7ece1c9d1 --- /dev/null +++ b/scripts/build_line_rating.py @@ -0,0 +1,155 @@ +# -*- coding: utf-8 -*- +# SPDX-FileCopyrightText: : 2017-2020 The PyPSA-Eur Authors +# +# SPDX-License-Identifier: MIT + +# coding: utf-8 +""" +Adds dynamic line rating timeseries to the base network. + +Relevant Settings +----------------- + +.. code:: yaml + + lines: + cutout: + line_rating: + + +.. seealso:: + Documentation of the configuration file ``config.yaml` +Inputs +------ + +- ``data/cutouts``: +- ``networks/base.nc``: confer :ref:`base` + +Outputs +------- + +- ``resources/line_rating.nc`` + + +Description +----------- + +The rule :mod:`build_line_rating` calculates the line rating for transmission lines. +The line rating provides the maximal capacity of a transmission line considering the heat exchange with the environment. + +The following heat gains and losses are considered: + +- heat gain through resistive losses +- heat gain through solar radiation +- heat loss through radiation of the trasnmission line +- heat loss through forced convection with wind +- heat loss through natural convection + + +With a heat balance considering the maximum temperature threshold of the transmission line, +the maximal possible capacity factor "s_max_pu" for each transmission line at each time step is calculated. +""" + +import logging +import re + +import atlite +import geopandas as gpd +import numpy as np +import pandas as pd +import pypsa +import xarray as xr +from _helpers import configure_logging +from shapely.geometry import LineString as Line +from shapely.geometry import Point + + +def calculate_resistance(T, R_ref, T_ref=293, alpha=0.00403): + """ + Calculates the resistance at other temperatures than the reference + temperature. + + Parameters + ---------- + T : Temperature at which resistance is calculated in [°C] or [K] + R_ref : Resistance at reference temperature in [Ohm] or [Ohm/Per Length Unit] + T_ref : Reference temperature in [°C] or [K] + alpha: Temperature coefficient in [1/K] + Defaults are: + * T_ref : 20 °C + * alpha : 0.00403 1/K + + Returns + ------- + Resistance of at given temperature. + """ + R = R_ref * (1 + alpha * (T - T_ref)) + return R + + +def calculate_line_rating(n, cutout): + """ + Calculates the maximal allowed power flow in each line for each time step + considering the maximal temperature. + + Parameters + ---------- + n : pypsa.Network object containing information on grid + + Returns + ------- + xarray DataArray object with maximal power. + """ + relevant_lines = n.lines[(n.lines["underground"] == False)] + buses = relevant_lines[["bus0", "bus1"]].values + x = n.buses.x + y = n.buses.y + shapes = [Line([Point(x[b0], y[b0]), Point(x[b1], y[b1])]) for (b0, b1) in buses] + shapes = gpd.GeoSeries(shapes, index=relevant_lines.index) + if relevant_lines.r_pu.eq(0).all(): + # Overwrite standard line resistance with line resistance obtained from line type + r_per_length = n.line_types["r_per_length"] + R = ( + relevant_lines.join(r_per_length, on=["type"])["r_per_length"] / 1000 + ) # in meters + # If line type with bundles is given retrieve number of conductors per bundle + relevant_lines["n_bundle"] = ( + relevant_lines["type"] + .where(relevant_lines["type"].str.contains("bundle")) + .dropna() + .apply(lambda x: int(re.findall(r"(\d+)-bundle", x)[0])) + ) + # Set default number of bundles per line + relevant_lines["n_bundle"].fillna(1, inplace=True) + R *= relevant_lines["n_bundle"] + R = calculate_resistance(T=353, R_ref=R) + Imax = cutout.line_rating(shapes, R, D=0.0218, Ts=353, epsilon=0.8, alpha=0.8) + line_factor = relevant_lines.eval("v_nom * n_bundle * num_parallel") / 1e3 # in mW + da = xr.DataArray( + data=np.sqrt(3) * Imax * line_factor.values.reshape(-1, 1), + attrs=dict( + description="Maximal possible power in MW for given line considering line rating" + ), + ) + return da + + +if __name__ == "__main__": + if "snakemake" not in globals(): + from _helpers import mock_snakemake + + snakemake = mock_snakemake( + "build_line_rating", + network="elec", + simpl="", + clusters="5", + ll="v1.0", + opts="Co2L-4H", + ) + configure_logging(snakemake) + + n = pypsa.Network(snakemake.input.base_network) + cutout = atlite.Cutout(snakemake.input.cutout) + + da = calculate_line_rating(n, cutout) + da.to_netcdf(snakemake.output[0]) diff --git a/scripts/build_natura_raster.py b/scripts/build_natura_raster.py index 9246508eb..3cd62fd95 100644 --- a/scripts/build_natura_raster.py +++ b/scripts/build_natura_raster.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Rasters the vector data of the `Natura 2000. @@ -19,7 +18,7 @@ cutout: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`renewable_cf` Inputs diff --git a/scripts/build_population_layouts.py b/scripts/build_population_layouts.py index a9308b7e1..e864d9259 100644 --- a/scripts/build_population_layouts.py +++ b/scripts/build_population_layouts.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build mapping between cutout grid cells and population (total, urban, rural). """ diff --git a/scripts/build_population_weighted_energy_totals.py b/scripts/build_population_weighted_energy_totals.py index 85d7a8b31..879e3b9b2 100644 --- a/scripts/build_population_weighted_energy_totals.py +++ b/scripts/build_population_weighted_energy_totals.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Distribute country-level energy demands by population. """ diff --git a/scripts/build_powerplants.py b/scripts/build_powerplants.py index a8a652499..cbe945050 100755 --- a/scripts/build_powerplants.py +++ b/scripts/build_powerplants.py @@ -21,7 +21,7 @@ custom_powerplants: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`electricity` Inputs @@ -98,13 +98,15 @@ def add_custom_powerplants(ppl, custom_powerplants, custom_ppl_query=False): def replace_natural_gas_technology(df): - mapping = {"Steam Turbine": "OCGT", "Combustion Engine": "OCGT"} - tech = df.Technology.replace(mapping).fillna("OCGT") - return df.Technology.where(df.Fueltype != "Natural Gas", tech) + mapping = {"Steam Turbine": "CCGT", "Combustion Engine": "OCGT"} + tech = df.Technology.replace(mapping).fillna("CCGT") + return df.Technology.mask(df.Fueltype == "Natural Gas", tech) def replace_natural_gas_fueltype(df): - return df.Fueltype.where(df.Fueltype != "Natural Gas", df.Technology) + return df.Fueltype.mask( + (df.Technology == "OCGT") | (df.Technology == "CCGT"), "Natural Gas" + ) if __name__ == "__main__": @@ -115,7 +117,7 @@ def replace_natural_gas_fueltype(df): configure_logging(snakemake) n = pypsa.Network(snakemake.input.base_network) - countries = snakemake.config["countries"] + countries = snakemake.params.countries ppl = ( pm.powerplants(from_url=True) @@ -134,12 +136,12 @@ def replace_natural_gas_fueltype(df): ppl = ppl.query('not (Country in @available_countries and Fueltype == "Bioenergy")') ppl = pd.concat([ppl, opsd]) - ppl_query = snakemake.config["electricity"]["powerplants_filter"] + ppl_query = snakemake.params.powerplants_filter if isinstance(ppl_query, str): ppl.query(ppl_query, inplace=True) # add carriers from own powerplant files: - custom_ppl_query = snakemake.config["electricity"]["custom_powerplants"] + custom_ppl_query = snakemake.params.custom_powerplants ppl = add_custom_powerplants( ppl, snakemake.input.custom_powerplants, custom_ppl_query ) @@ -149,6 +151,7 @@ def replace_natural_gas_fueltype(df): logging.warning(f"No powerplants known in: {', '.join(countries_wo_ppl)}") substations = n.buses.query("substation_lv") + ppl = ppl.dropna(subset=["lat", "lon"]) ppl = map_country_bus(ppl, substations) bus_null_b = ppl["bus"].isnull() diff --git a/scripts/build_renewable_profiles.py b/scripts/build_renewable_profiles.py index ea4dfa9af..88a43f537 100644 --- a/scripts/build_renewable_profiles.py +++ b/scripts/build_renewable_profiles.py @@ -4,7 +4,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Calculates for each network node the (i) installable capacity (based on land- use), (ii) the available generation time series (based on weather data), and @@ -43,7 +42,7 @@ resource: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`snapshots_cf`, :ref:`atlite_cf`, :ref:`renewable_cf` Inputs @@ -65,7 +64,7 @@ - ``resources/offshore_shapes.geojson``: confer :ref:`shapes` - ``resources/regions_onshore.geojson``: (if not offshore wind), confer :ref:`busregions` - ``resources/regions_offshore.geojson``: (if offshore wind), :ref:`busregions` -- ``"cutouts/" + config["renewable"][{technology}]['cutout']``: :ref:`cutout` +- ``"cutouts/" + params["renewable"][{technology}]['cutout']``: :ref:`cutout` - ``networks/base.nc``: :ref:`base` Outputs @@ -189,7 +188,7 @@ import numpy as np import xarray as xr from _helpers import configure_logging -from dask.distributed import Client, LocalCluster +from dask.distributed import Client from pypsa.geo import haversine from shapely.geometry import LineString @@ -205,20 +204,23 @@ nprocesses = int(snakemake.threads) noprogress = snakemake.config["run"].get("disable_progressbar", True) - config = snakemake.config["renewable"][snakemake.wildcards.technology] - resource = config["resource"] # pv panel config / wind turbine config - correction_factor = config.get("correction_factor", 1.0) - capacity_per_sqkm = config["capacity_per_sqkm"] - p_nom_max_meth = config.get("potential", "conservative") + noprogress = noprogress or not snakemake.config["atlite"]["show_progress"] + params = snakemake.params.renewable[snakemake.wildcards.technology] + resource = params["resource"] # pv panel params / wind turbine params + correction_factor = params.get("correction_factor", 1.0) + capacity_per_sqkm = params["capacity_per_sqkm"] + p_nom_max_meth = params.get("potential", "conservative") - if isinstance(config.get("corine", {}), list): - config["corine"] = {"grid_codes": config["corine"]} + if isinstance(params.get("corine", {}), list): + params["corine"] = {"grid_codes": params["corine"]} if correction_factor != 1.0: logger.info(f"correction_factor is set as {correction_factor}") - cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1) - client = Client(cluster, asynchronous=True) + if nprocesses > 1: + client = Client(n_workers=nprocesses, threads_per_worker=1) + else: + client = None cutout = atlite.Cutout(snakemake.input.cutout) regions = gpd.read_file(snakemake.input.regions) @@ -230,13 +232,13 @@ regions = regions.set_index("name").rename_axis("bus") buses = regions.index - res = config.get("excluder_resolution", 100) + res = params.get("excluder_resolution", 100) excluder = atlite.ExclusionContainer(crs=3035, res=res) - if config["natura"]: + if params["natura"]: excluder.add_raster(snakemake.input.natura, nodata=0, allow_no_overlap=True) - corine = config.get("corine", {}) + corine = params.get("corine", {}) if "grid_codes" in corine: codes = corine["grid_codes"] excluder.add_raster(snakemake.input.corine, codes=codes, invert=True, crs=3035) @@ -247,28 +249,28 @@ snakemake.input.corine, codes=codes, buffer=buffer, crs=3035 ) - if "ship_threshold" in config: + if "ship_threshold" in params: shipping_threshold = ( - config["ship_threshold"] * 8760 * 6 + params["ship_threshold"] * 8760 * 6 ) # approximation because 6 years of data which is hourly collected func = functools.partial(np.less, shipping_threshold) excluder.add_raster( snakemake.input.ship_density, codes=func, crs=4326, allow_no_overlap=True ) - if config.get("max_depth"): + if params.get("max_depth"): # lambda not supported for atlite + multiprocessing # use named function np.greater with partially frozen argument instead # and exclude areas where: -max_depth > grid cell depth - func = functools.partial(np.greater, -config["max_depth"]) + func = functools.partial(np.greater, -params["max_depth"]) excluder.add_raster(snakemake.input.gebco, codes=func, crs=4326, nodata=-1000) - if "min_shore_distance" in config: - buffer = config["min_shore_distance"] + if "min_shore_distance" in params: + buffer = params["min_shore_distance"] excluder.add_geometry(snakemake.input.country_shapes, buffer=buffer) - if "max_shore_distance" in config: - buffer = config["max_shore_distance"] + if "max_shore_distance" in params: + buffer = params["max_shore_distance"] excluder.add_geometry( snakemake.input.country_shapes, buffer=buffer, invert=True ) @@ -290,7 +292,8 @@ potential = capacity_per_sqkm * availability.sum("bus") * area func = getattr(cutout, resource.pop("method")) - resource["dask_kwargs"] = {"scheduler": client} + if client is not None: + resource["dask_kwargs"] = {"scheduler": client} capacity_factor = correction_factor * func(capacity_factor=True, **resource) layout = capacity_factor * area * capacity_per_sqkm profile, capacities = func( @@ -359,13 +362,13 @@ # select only buses with some capacity and minimal capacity factor ds = ds.sel( bus=( - (ds["profile"].mean("time") > config.get("min_p_max_pu", 0.0)) - & (ds["p_nom_max"] > config.get("min_p_nom_max", 0.0)) + (ds["profile"].mean("time") > params.get("min_p_max_pu", 0.0)) + & (ds["p_nom_max"] > params.get("min_p_nom_max", 0.0)) ) ) - if "clip_p_max_pu" in config: - min_p_max_pu = config["clip_p_max_pu"] + if "clip_p_max_pu" in params: + min_p_max_pu = params["clip_p_max_pu"] ds["profile"] = ds["profile"].where(ds["profile"] >= min_p_max_pu, 0) ds.to_netcdf(snakemake.output.profile) diff --git a/scripts/build_retro_cost.py b/scripts/build_retro_cost.py index 037139d1e..c830415ed 100644 --- a/scripts/build_retro_cost.py +++ b/scripts/build_retro_cost.py @@ -3,7 +3,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ This script calculates the space heating savings through better insulation of the thermal envelope of a building and corresponding costs for different @@ -150,7 +149,6 @@ def prepare_building_stock_data(): type and period """ - building_data = pd.read_csv(snakemake.input.building_stock, usecols=list(range(13))) # standardize data @@ -307,7 +305,7 @@ def prepare_building_stock_data(): u_values.set_index(["country_code", "subsector", "bage", "type"], inplace=True) # only take in config.yaml specified countries into account - countries = snakemake.config["countries"] + countries = snakemake.params.countries area_tot = area_tot.loc[countries] return u_values, country_iso_dic, countries, area_tot, area @@ -318,7 +316,6 @@ def prepare_building_topology(u_values, same_building_topology=True): Reads in typical building topologies (e.g. average surface of building elements) and typical losses through thermal bridging and air ventilation. """ - data_tabula = pd.read_csv( snakemake.input.data_tabula, skiprows=lambda x: x in range(1, 11), @@ -516,7 +513,7 @@ def prepare_cost_retro(country_iso_dic): def prepare_temperature_data(): """ - returns the temperature dependent data for each country: + Returns the temperature dependent data for each country: d_heat : length of heating season pd.Series(index=countries) [days/year] on those days, daily average temperature is below @@ -624,7 +621,7 @@ def calculate_costs(u_values, l, cost_retro, window_assumptions): def calculate_new_u(u_values, l, l_weight, window_assumptions, k=0.035): """ - calculate U-values after building retrofitting, depending on the old + Calculate U-values after building retrofitting, depending on the old U-values (u_values). This is for simple insulation measuers, adding an additional layer of insulation. @@ -685,7 +682,7 @@ def map_tabula_to_hotmaps(df_tabula, df_hotmaps, column_prefix): def get_solar_gains_per_year(window_area): """ - returns solar heat gains during heating season in [kWh/a] depending on the + Returns solar heat gains during heating season in [kWh/a] depending on the window area [m^2] of the building, assuming a equal distributed window orientation (east, south, north, west) """ @@ -701,8 +698,8 @@ def get_solar_gains_per_year(window_area): def map_to_lstrength(l_strength, df): """ - renames column names from a pandas dataframe to map tabula retrofitting - strengths [2 = moderate, 3 = ambitious] to l_strength + Renames column names from a pandas dataframe to map tabula retrofitting + strengths [2 = moderate, 3 = ambitious] to l_strength. """ middle = len(l_strength) // 2 map_to_l = pd.MultiIndex.from_arrays( @@ -721,7 +718,7 @@ def map_to_lstrength(l_strength, df): def calculate_heat_losses(u_values, data_tabula, l_strength, temperature_factor): """ - calculates total annual heat losses Q_ht for different insulation + Calculates total annual heat losses Q_ht for different insulation thicknesses (l_strength), depending on current insulation state (u_values), standard building topologies and air ventilation from TABULA (data_tabula) and the accumulated difference between internal and external temperature @@ -843,7 +840,7 @@ def calculate_heat_losses(u_values, data_tabula, l_strength, temperature_factor) def calculate_heat_gains(data_tabula, heat_transfer_perm2, d_heat): """ - calculates heat gains Q_gain [W/m^2], which consititure from gains by: + Calculates heat gains Q_gain [W/m^2], which consititure from gains by: (1) solar radiation (2) internal heat gains """ @@ -888,7 +885,7 @@ def calculate_space_heat_savings( u_values, data_tabula, l_strength, temperature_factor, d_heat ): """ - calculates space heat savings (dE_space [per unit of unrefurbished state]) + Calculates space heat savings (dE_space [per unit of unrefurbished state]) through retrofitting of the thermal envelope by additional insulation material (l_strength[m]) """ @@ -1043,7 +1040,7 @@ def sample_dE_costs_area( # ******** config ********************************************************* - retro_opts = snakemake.config["sector"]["retrofitting"] + retro_opts = snakemake.params.retrofitting interest_rate = retro_opts["interest_rate"] annualise_cost = retro_opts["annualise_cost"] # annualise the investment costs tax_weighting = retro_opts[ diff --git a/scripts/build_salt_cavern_potentials.py b/scripts/build_salt_cavern_potentials.py index 082c688f1..956ed4319 100644 --- a/scripts/build_salt_cavern_potentials.py +++ b/scripts/build_salt_cavern_potentials.py @@ -2,12 +2,11 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build salt cavern potentials for hydrogen storage. -Technical Potential of Salt Caverns for Hydrogen Storage in Europe -CC-BY 4.0 +Technical Potential of Salt Caverns for Hydrogen Storage in Europe CC-BY +4.0 https://doi.org/10.20944/preprints201910.0187.v1 https://doi.org/10.1016/j.ijhydene.2019.12.161 @@ -39,7 +38,6 @@ def load_bus_regions(onshore_path, offshore_path): """ Load pypsa-eur on- and offshore regions and concat. """ - bus_regions_offshore = gpd.read_file(offshore_path) bus_regions_onshore = gpd.read_file(onshore_path) bus_regions = concat_gdf([bus_regions_offshore, bus_regions_onshore]) diff --git a/scripts/build_sequestration_potentials.py b/scripts/build_sequestration_potentials.py index e17d4f0e7..e19a96da6 100644 --- a/scripts/build_sequestration_potentials.py +++ b/scripts/build_sequestration_potentials.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build regionalised geological sequestration potential for carbon dioxide using data from `CO2Stop @@ -16,7 +15,7 @@ countries: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`toplevel_cf` Inputs @@ -235,6 +234,7 @@ def nuts3(country_shapes, nuts3, nuts3pop, nuts3gdp, ch_cantons, ch_popgdp): manual = gpd.GeoDataFrame( [["BA1", "BA", 3871.0], ["RS1", "RS", 7210.0], ["AL1", "AL", 2893.0]], columns=["NUTS_ID", "country", "pop"], + geometry=gpd.GeoSeries(), ) manual["geometry"] = manual["country"].map(country_shapes) manual = manual.dropna() @@ -255,13 +255,11 @@ def nuts3(country_shapes, nuts3, nuts3pop, nuts3gdp, ch_cantons, ch_popgdp): snakemake = mock_snakemake("build_shapes") configure_logging(snakemake) - country_shapes = countries( - snakemake.input.naturalearth, snakemake.config["countries"] - ) + country_shapes = countries(snakemake.input.naturalearth, snakemake.params.countries) country_shapes.reset_index().to_file(snakemake.output.country_shapes) offshore_shapes = eez( - country_shapes, snakemake.input.eez, snakemake.config["countries"] + country_shapes, snakemake.input.eez, snakemake.params.countries ) offshore_shapes.reset_index().to_file(snakemake.output.offshore_shapes) diff --git a/scripts/build_ship_raster.py b/scripts/build_ship_raster.py index d290e6168..90e006b0b 100644 --- a/scripts/build_ship_raster.py +++ b/scripts/build_ship_raster.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2022 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Transforms the global ship density data from the `World Bank Data Catalogue. @@ -20,7 +19,7 @@ cutout: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`renewable_cf` Inputs @@ -46,7 +45,7 @@ import os import zipfile -import xarray as xr +import rioxarray from _helpers import configure_logging from build_natura_raster import determine_cutout_xXyY @@ -64,10 +63,10 @@ with zipfile.ZipFile(snakemake.input.ship_density) as zip_f: zip_f.extract("shipdensity_global.tif") - with xr.open_rasterio("shipdensity_global.tif") as ship_density: + with rioxarray.open_rasterio("shipdensity_global.tif") as ship_density: ship_density = ship_density.drop(["band"]).sel( x=slice(min(xs), max(Xs)), y=slice(max(Ys), min(ys)) ) - ship_density.to_netcdf(snakemake.output[0]) + ship_density.rio.to_raster(snakemake.output[0]) os.remove("shipdensity_global.tif") diff --git a/scripts/build_solar_thermal_profiles.py b/scripts/build_solar_thermal_profiles.py index 1cec57f17..d285691a4 100644 --- a/scripts/build_solar_thermal_profiles.py +++ b/scripts/build_solar_thermal_profiles.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build solar thermal collector time series. """ @@ -28,9 +27,9 @@ cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1) client = Client(cluster, asynchronous=True) - config = snakemake.config["solar_thermal"] + config = snakemake.params.solar_thermal - time = pd.date_range(freq="h", **snakemake.config["snapshots"]) + time = pd.date_range(freq="h", **snakemake.params.snapshots) cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time) clustered_regions = ( diff --git a/scripts/build_temperature_profiles.py b/scripts/build_temperature_profiles.py index b1973fd87..9db37c257 100644 --- a/scripts/build_temperature_profiles.py +++ b/scripts/build_temperature_profiles.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build time series for air and soil temperatures per clustered model region. """ @@ -28,7 +27,7 @@ cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1) client = Client(cluster, asynchronous=True) - time = pd.date_range(freq="h", **snakemake.config["snapshots"]) + time = pd.date_range(freq="h", **snakemake.params.snapshots) cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time) clustered_regions = ( diff --git a/scripts/build_transport_demand.py b/scripts/build_transport_demand.py index a684036d0..c5bf46329 100644 --- a/scripts/build_transport_demand.py +++ b/scripts/build_transport_demand.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Build land transport demand per clustered model region including efficiency improvements due to drivetrain changes, time series for electric vehicle @@ -124,7 +123,6 @@ def bev_availability_profile(fn, snapshots, nodes, options): """ Derive plugged-in availability for passenger electric vehicles. """ - traffic = pd.read_csv(fn, skiprows=2, usecols=["count"]).squeeze("columns") avail_max = options["bev_avail_max"] @@ -177,9 +175,9 @@ def bev_dsm_profile(snapshots, nodes, options): snakemake.input.pop_weighted_energy_totals, index_col=0 ) - options = snakemake.config["sector"] + options = snakemake.params.sector - snapshots = pd.date_range(freq="h", **snakemake.config["snapshots"], tz="UTC") + snapshots = pd.date_range(freq="h", **snakemake.params.snapshots, tz="UTC") nyears = len(snapshots) / 8760 diff --git a/scripts/cluster_gas_network.py b/scripts/cluster_gas_network.py index d180041cb..e7554dff3 100755 --- a/scripts/cluster_gas_network.py +++ b/scripts/cluster_gas_network.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Cluster gas transmission network to clustered model regions. """ @@ -30,7 +29,6 @@ def load_bus_regions(onshore_path, offshore_path): """ Load pypsa-eur on- and offshore regions and concat. """ - bus_regions_offshore = gpd.read_file(offshore_path) bus_regions_onshore = gpd.read_file(onshore_path) bus_regions = concat_gdf([bus_regions_offshore, bus_regions_onshore]) diff --git a/scripts/cluster_network.py b/scripts/cluster_network.py index e2cba28fc..f0fd80ebf 100644 --- a/scripts/cluster_network.py +++ b/scripts/cluster_network.py @@ -27,7 +27,7 @@ length_factor: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`toplevel_cf`, :ref:`renewable_cf`, :ref:`solving_cf`, :ref:`lines_cf` Inputs @@ -89,7 +89,7 @@ **Is it possible to run the model without the** ``simplify_network`` **rule?** No, the network clustering methods in the PyPSA module - `pypsa.networkclustering `_ + `pypsa.clustering.spatial `_ do not work reliably with multiple voltage levels and transformers. .. tip:: @@ -133,8 +133,8 @@ import pyomo.environ as po import pypsa import seaborn as sns -from _helpers import configure_logging, get_aggregation_strategies, update_p_nom_max -from pypsa.networkclustering import ( +from _helpers import configure_logging, update_p_nom_max +from pypsa.clustering.spatial import ( busmap_by_greedy_modularity, busmap_by_hac, busmap_by_kmeans, @@ -186,7 +186,7 @@ def get_feature_for_hac(n, buses_i=None, feature=None): if "offwind" in carriers: carriers.remove("offwind") carriers = np.append( - carriers, network.generators.carrier.filter(like="offwind").unique() + carriers, n.generators.carrier.filter(like="offwind").unique() ) if feature.split("-")[1] == "cap": @@ -395,10 +395,6 @@ def clustering_for_n_clusters( extended_link_costs=0, focus_weights=None, ): - bus_strategies, generator_strategies = get_aggregation_strategies( - aggregation_strategies - ) - if not isinstance(custom_busmap, pd.Series): busmap = busmap_for_n_clusters( n, n_clusters, solver_name, focus_weights, algorithm, feature @@ -406,15 +402,20 @@ def clustering_for_n_clusters( else: busmap = custom_busmap + line_strategies = aggregation_strategies.get("lines", dict()) + generator_strategies = aggregation_strategies.get("generators", dict()) + one_port_strategies = aggregation_strategies.get("one_ports", dict()) + clustering = get_clustering_from_busmap( n, busmap, - bus_strategies=bus_strategies, aggregate_generators_weighted=True, aggregate_generators_carriers=aggregate_carriers, aggregate_one_ports=["Load", "StorageUnit"], line_length_factor=line_length_factor, + line_strategies=line_strategies, generator_strategies=generator_strategies, + one_port_strategies=one_port_strategies, scale_link_capital_costs=False, ) @@ -424,7 +425,10 @@ def clustering_for_n_clusters( n.links.eval("underwater_fraction * length").div(nc.links.length).dropna() ) nc.links["capital_cost"] = nc.links["capital_cost"].add( - (nc.links.length - n.links.length).clip(lower=0).mul(extended_link_costs), + (nc.links.length - n.links.length) + .clip(lower=0) + .mul(extended_link_costs) + .dropna(), fill_value=0, ) @@ -457,31 +461,23 @@ def plot_busmap_for_n_clusters(n, n_clusters, fn=None): if "snakemake" not in globals(): from _helpers import mock_snakemake - snakemake = mock_snakemake("cluster_network", simpl="", clusters="5") + snakemake = mock_snakemake("cluster_network", simpl="", clusters="37c") configure_logging(snakemake) - n = pypsa.Network(snakemake.input.network) - - focus_weights = snakemake.config.get("focus_weights", None) + params = snakemake.params + solver_name = snakemake.config["solving"]["solver"]["name"] - renewable_carriers = pd.Index( - [ - tech - for tech in n.generators.carrier.unique() - if tech in snakemake.config["renewable"] - ] - ) + n = pypsa.Network(snakemake.input.network) - exclude_carriers = snakemake.config["clustering"]["cluster_network"].get( - "exclude_carriers", [] - ) + exclude_carriers = params.cluster_network["exclude_carriers"] aggregate_carriers = set(n.generators.carrier) - set(exclude_carriers) + conventional_carriers = set(params.conventional_carriers) if snakemake.wildcards.clusters.endswith("m"): n_clusters = int(snakemake.wildcards.clusters[:-1]) - conventional = set( - snakemake.config["electricity"].get("conventional_carriers", []) - ) - aggregate_carriers = conventional.intersection(aggregate_carriers) + aggregate_carriers = params.conventional_carriers & aggregate_carriers + elif snakemake.wildcards.clusters.endswith("c"): + n_clusters = int(snakemake.wildcards.clusters[:-1]) + aggregate_carriers = aggregate_carriers - conventional_carriers elif snakemake.wildcards.clusters == "all": n_clusters = len(n.buses) else: @@ -491,37 +487,20 @@ def plot_busmap_for_n_clusters(n, n_clusters, fn=None): # Fast-path if no clustering is necessary busmap = n.buses.index.to_series() linemap = n.lines.index.to_series() - clustering = pypsa.networkclustering.Clustering( + clustering = pypsa.clustering.spatial.Clustering( n, busmap, linemap, linemap, pd.Series(dtype="O") ) else: - line_length_factor = snakemake.config["lines"]["length_factor"] Nyears = n.snapshot_weightings.objective.sum() / 8760 hvac_overhead_cost = load_costs( snakemake.input.tech_costs, - snakemake.config["costs"], - snakemake.config["electricity"], + params.costs, + params.max_hours, Nyears, ).at["HVAC overhead", "capital_cost"] - def consense(x): - v = x.iat[0] - assert ( - x == v - ).all() or x.isnull().all(), "The `potential` configuration option must agree for all renewable carriers, for now!" - return v - - aggregation_strategies = snakemake.config["clustering"].get( - "aggregation_strategies", {} - ) - # translate str entries of aggregation_strategies to pd.Series functions: - aggregation_strategies = { - p: {k: getattr(pd.Series, v) for k, v in aggregation_strategies[p].items()} - for p in aggregation_strategies.keys() - } - - custom_busmap = snakemake.config["enable"].get("custom_busmap", False) + custom_busmap = params.custom_busmap if custom_busmap: custom_busmap = pd.read_csv( snakemake.input.custom_busmap, index_col=0, squeeze=True @@ -529,21 +508,18 @@ def consense(x): custom_busmap.index = custom_busmap.index.astype(str) logger.info(f"Imported custom busmap from {snakemake.input.custom_busmap}") - cluster_config = snakemake.config.get("clustering", {}).get( - "cluster_network", {} - ) clustering = clustering_for_n_clusters( n, n_clusters, custom_busmap, aggregate_carriers, - line_length_factor, - aggregation_strategies, - snakemake.config["solving"]["solver"]["name"], - cluster_config.get("algorithm", "hac"), - cluster_config.get("feature", "solar+onwind-time"), + params.length_factor, + params.aggregation_strategies, + solver_name, + params.cluster_network["algorithm"], + params.cluster_network["feature"], hvac_overhead_cost, - focus_weights, + params.focus_weights, ) update_p_nom_max(clustering.network) diff --git a/scripts/copy_config.py b/scripts/copy_config.py index c79e578c8..79d2e32b0 100644 --- a/scripts/copy_config.py +++ b/scripts/copy_config.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Copy used configuration files and important scripts for archiving. """ @@ -13,7 +12,7 @@ import yaml files = { - "config.yaml": "config.yaml", + "config/config.yaml": "config.yaml", "Snakefile": "Snakefile", "scripts/solve_network.py": "solve_network.py", "scripts/prepare_sector_network.py": "prepare_sector_network.py", @@ -25,7 +24,7 @@ snakemake = mock_snakemake("copy_config") - basepath = Path(f"results/{snakemake.params.RDIR}configs/") + basepath = Path(f"results/{snakemake.params.RDIR}config/") for f, name in files.items(): copy(f, basepath / name) diff --git a/scripts/make_summary.py b/scripts/make_summary.py index 5d1ee3dc2..56ee98c90 100644 --- a/scripts/make_summary.py +++ b/scripts/make_summary.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Create summary CSV files for all scenario runs including costs, capacities, capacity factors, curtailment, energy balances, prices and other metrics. @@ -17,7 +16,6 @@ import numpy as np import pandas as pd import pypsa -from _helpers import override_component_attrs from prepare_sector_network import prepare_costs idx = pd.IndexSlice @@ -199,7 +197,7 @@ def calculate_costs(n, label, costs): def calculate_cumulative_cost(): - planning_horizons = snakemake.config["scenario"]["planning_horizons"] + planning_horizons = snakemake.params.scenario["planning_horizons"] cumulative_cost = pd.DataFrame( index=df["costs"].sum().index, @@ -301,9 +299,9 @@ def calculate_energy(n, label, energy): ) # remove values where bus is missing (bug in nomopyomo) no_bus = c.df.index[c.df["bus" + port] == ""] - totals.loc[no_bus] = n.component_attrs[c.name].loc[ - "p" + port, "default" - ] + totals.loc[no_bus] = float( + n.component_attrs[c.name].loc["p" + port, "default"] + ) c_energies -= totals.groupby(c.df.carrier).sum() c_energies = pd.concat([c_energies], keys=[c.list_name]) @@ -320,7 +318,6 @@ def calculate_supply(n, label, supply): Calculate the max dispatch of each component at the buses aggregated by carrier. """ - bus_carriers = n.buses.carrier.unique() for i in bus_carriers: @@ -372,7 +369,6 @@ def calculate_supply_energy(n, label, supply_energy): Calculate the total energy supply/consuption of each component at the buses aggregated by carrier. """ - bus_carriers = n.buses.carrier.unique() for i in bus_carriers: @@ -662,8 +658,7 @@ def make_summaries(networks_dict): for label, filename in networks_dict.items(): logger.info(f"Make summary for scenario {label}, using {filename}") - overrides = override_component_attrs(snakemake.input.overrides) - n = pypsa.Network(filename, override_component_attrs=overrides) + n = pypsa.Network(filename) assign_carriers(n) assign_locations(n) @@ -691,19 +686,19 @@ def to_csv(df): (cluster, ll, opt + sector_opt, planning_horizon): "results/" + snakemake.params.RDIR + f"/postnetworks/elec_s{simpl}_{cluster}_l{ll}_{opt}_{sector_opt}_{planning_horizon}.nc" - for simpl in snakemake.config["scenario"]["simpl"] - for cluster in snakemake.config["scenario"]["clusters"] - for opt in snakemake.config["scenario"]["opts"] - for sector_opt in snakemake.config["scenario"]["sector_opts"] - for ll in snakemake.config["scenario"]["ll"] - for planning_horizon in snakemake.config["scenario"]["planning_horizons"] + for simpl in snakemake.params.scenario["simpl"] + for cluster in snakemake.params.scenario["clusters"] + for opt in snakemake.params.scenario["opts"] + for sector_opt in snakemake.params.scenario["sector_opts"] + for ll in snakemake.params.scenario["ll"] + for planning_horizon in snakemake.params.scenario["planning_horizons"] } - Nyears = len(pd.date_range(freq="h", **snakemake.config["snapshots"])) / 8760 + Nyears = len(pd.date_range(freq="h", **snakemake.params.snapshots)) / 8760 costs_db = prepare_costs( snakemake.input.costs, - snakemake.config["costs"], + snakemake.params.costs, Nyears, ) @@ -713,7 +708,7 @@ def to_csv(df): to_csv(df) - if snakemake.config["foresight"] == "myopic": + if snakemake.params.foresight == "myopic": cumulative_cost = calculate_cumulative_cost() cumulative_cost.to_csv( "results/" + snakemake.params.RDIR + "/csvs/cumulative_cost.csv" diff --git a/scripts/plot_network.py b/scripts/plot_network.py index 7c194b0cc..ae1d0e0ae 100644 --- a/scripts/plot_network.py +++ b/scripts/plot_network.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Creates plots for optimised network topologies, including electricity, gas and hydrogen networks, and regional generation, storage and conversion capacities @@ -21,7 +20,6 @@ import matplotlib.pyplot as plt import pandas as pd import pypsa -from _helpers import override_component_attrs from make_summary import assign_carriers from plot_summary import preferred_order, rename_techs from pypsa.plot import add_legend_circles, add_legend_lines, add_legend_patches @@ -71,7 +69,7 @@ def plot_map( transmission=False, with_legend=True, ): - tech_colors = snakemake.config["plotting"]["tech_colors"] + tech_colors = snakemake.params.plotting["tech_colors"] n = network.copy() assign_location(n) @@ -117,9 +115,7 @@ def plot_map( costs = costs.stack() # .sort_index() # hack because impossible to drop buses... - eu_location = snakemake.config["plotting"].get( - "eu_node_location", dict(x=-5.5, y=46) - ) + eu_location = snakemake.params.plotting.get("eu_node_location", dict(x=-5.5, y=46)) n.buses.loc["EU gas", "x"] = eu_location["x"] n.buses.loc["EU gas", "y"] = eu_location["y"] @@ -316,7 +312,7 @@ def plot_h2_map(network, regions): h2_new = n.links[n.links.carrier == "H2 pipeline"] h2_retro = n.links[n.links.carrier == "H2 pipeline retrofitted"] - if snakemake.config["foresight"] == "myopic": + if snakemake.params.foresight == "myopic": # sum capacitiy for pipelines from different investment periods h2_new = group_pipes(h2_new) @@ -559,7 +555,7 @@ def plot_ch4_map(network): link_widths_used = max_usage / linewidth_factor link_widths_used[max_usage < line_lower_threshold] = 0.0 - tech_colors = snakemake.config["plotting"]["tech_colors"] + tech_colors = snakemake.params.plotting["tech_colors"] pipe_colors = { "gas pipeline": "#f08080", @@ -701,7 +697,7 @@ def plot_map_without(network): # hack because impossible to drop buses... if "EU gas" in n.buses.index: - eu_location = snakemake.config["plotting"].get( + eu_location = snakemake.params.plotting.get( "eu_node_location", dict(x=-5.5, y=46) ) n.buses.loc["EU gas", "x"] = eu_location["x"] @@ -877,7 +873,7 @@ def plot_series(network, carrier="AC", name="test"): stacked=True, linewidth=0.0, color=[ - snakemake.config["plotting"]["tech_colors"][i.replace(suffix, "")] + snakemake.params.plotting["tech_colors"][i.replace(suffix, "")] for i in new_columns ], ) @@ -933,12 +929,11 @@ def plot_series(network, carrier="AC", name="test"): logging.basicConfig(level=snakemake.config["logging"]["level"]) - overrides = override_component_attrs(snakemake.input.overrides) - n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides) + n = pypsa.Network(snakemake.input.network) regions = gpd.read_file(snakemake.input.regions).set_index("name") - map_opts = snakemake.config["plotting"]["map"] + map_opts = snakemake.params.plotting["map"] if map_opts["boundaries"] is None: map_opts["boundaries"] = regions.total_bounds[[0, 2, 1, 3]] + [-1, 1, -1, 1] diff --git a/scripts/plot_summary.py b/scripts/plot_summary.py index af028116e..e7de5473d 100644 --- a/scripts/plot_summary.py +++ b/scripts/plot_summary.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Creates plots from summary CSV files. """ @@ -143,10 +142,10 @@ def plot_costs(): df = df.groupby(df.index.map(rename_techs)).sum() - to_drop = df.index[df.max(axis=1) < snakemake.config["plotting"]["costs_threshold"]] + to_drop = df.index[df.max(axis=1) < snakemake.params.plotting["costs_threshold"]] logger.info( - f"Dropping technology with costs below {snakemake.config['plotting']['costs_threshold']} EUR billion per year" + f"Dropping technology with costs below {snakemake.params['plotting']['costs_threshold']} EUR billion per year" ) logger.debug(df.loc[to_drop]) @@ -166,7 +165,7 @@ def plot_costs(): kind="bar", ax=ax, stacked=True, - color=[snakemake.config["plotting"]["tech_colors"][i] for i in new_index], + color=[snakemake.params.plotting["tech_colors"][i] for i in new_index], ) handles, labels = ax.get_legend_handles_labels() @@ -174,7 +173,7 @@ def plot_costs(): handles.reverse() labels.reverse() - ax.set_ylim([0, snakemake.config["plotting"]["costs_max"]]) + ax.set_ylim([0, snakemake.params.plotting["costs_max"]]) ax.set_ylabel("System Cost [EUR billion per year]") @@ -202,11 +201,11 @@ def plot_energy(): df = df.groupby(df.index.map(rename_techs)).sum() to_drop = df.index[ - df.abs().max(axis=1) < snakemake.config["plotting"]["energy_threshold"] + df.abs().max(axis=1) < snakemake.params.plotting["energy_threshold"] ] logger.info( - f"Dropping all technology with energy consumption or production below {snakemake.config['plotting']['energy_threshold']} TWh/a" + f"Dropping all technology with energy consumption or production below {snakemake.params['plotting']['energy_threshold']} TWh/a" ) logger.debug(df.loc[to_drop]) @@ -228,7 +227,7 @@ def plot_energy(): kind="bar", ax=ax, stacked=True, - color=[snakemake.config["plotting"]["tech_colors"][i] for i in new_index], + color=[snakemake.params.plotting["tech_colors"][i] for i in new_index], ) handles, labels = ax.get_legend_handles_labels() @@ -238,8 +237,8 @@ def plot_energy(): ax.set_ylim( [ - snakemake.config["plotting"]["energy_min"], - snakemake.config["plotting"]["energy_max"], + snakemake.params.plotting["energy_min"], + snakemake.params.plotting["energy_max"], ] ) @@ -288,7 +287,7 @@ def plot_balances(): df = df.groupby(df.index.map(rename_techs)).sum() to_drop = df.index[ - df.abs().max(axis=1) < snakemake.config["plotting"]["energy_threshold"] / 10 + df.abs().max(axis=1) < snakemake.params.plotting["energy_threshold"] / 10 ] if v[0] in co2_carriers: @@ -297,7 +296,7 @@ def plot_balances(): units = "TWh/a" logger.debug( - f"Dropping technology energy balance smaller than {snakemake.config['plotting']['energy_threshold']/10} {units}" + f"Dropping technology energy balance smaller than {snakemake.params['plotting']['energy_threshold']/10} {units}" ) logger.debug(df.loc[to_drop]) @@ -318,7 +317,7 @@ def plot_balances(): kind="bar", ax=ax, stacked=True, - color=[snakemake.config["plotting"]["tech_colors"][i] for i in new_index], + color=[snakemake.params.plotting["tech_colors"][i] for i in new_index], ) handles, labels = ax.get_legend_handles_labels() @@ -441,7 +440,6 @@ def plot_carbon_budget_distribution(input_eurostat): """ Plot historical carbon emissions in the EU and decarbonization path. """ - import seaborn as sns sns.set() @@ -457,10 +455,10 @@ def plot_carbon_budget_distribution(input_eurostat): ax1 = plt.subplot(gs1[0, 0]) ax1.set_ylabel("CO$_2$ emissions (Gt per year)", fontsize=22) ax1.set_ylim([0, 5]) - ax1.set_xlim([1990, snakemake.config["scenario"]["planning_horizons"][-1] + 1]) + ax1.set_xlim([1990, snakemake.params.planning_horizons[-1] + 1]) path_cb = "results/" + snakemake.params.RDIR + "/csvs/" - countries = snakemake.config["countries"] + countries = snakemake.params.countries e_1990 = co2_emissions_year(countries, input_eurostat, opts, year=1990) CO2_CAP = pd.read_csv(path_cb + "carbon_budget_distribution.csv", index_col=0) @@ -557,7 +555,7 @@ def plot_carbon_budget_distribution(input_eurostat): plot_balances() - for sector_opts in snakemake.config["scenario"]["sector_opts"]: + for sector_opts in snakemake.params.sector_opts: opts = sector_opts.split("-") for o in opts: if "cb" in o: diff --git a/scripts/prepare_links_p_nom.py b/scripts/prepare_links_p_nom.py index 7c63f3a4f..4b915d22a 100644 --- a/scripts/prepare_links_p_nom.py +++ b/scripts/prepare_links_p_nom.py @@ -4,7 +4,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Extracts capacities of HVDC links from `Wikipedia. @@ -19,7 +18,7 @@ prepare_links_p_nom: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`toplevel_cf` Inputs diff --git a/scripts/prepare_network.py b/scripts/prepare_network.py index 79b5c9d4e..7b7f77f94 100755 --- a/scripts/prepare_network.py +++ b/scripts/prepare_network.py @@ -34,7 +34,7 @@ max_hours: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`costs_cf`, :ref:`electricity_cf` Inputs @@ -233,7 +233,22 @@ def enforce_autarky(n, only_crossborder=False): n.mremove("Link", links_rm) -def set_line_nom_max(n, s_nom_max_set=np.inf, p_nom_max_set=np.inf): +def set_line_nom_max( + n, + s_nom_max_set=np.inf, + p_nom_max_set=np.inf, + s_nom_max_ext=np.inf, + p_nom_max_ext=np.inf, +): + if np.isfinite(s_nom_max_ext) and s_nom_max_ext > 0: + logger.info(f"Limiting line extensions to {s_nom_max_ext} MW") + n.lines["s_nom_max"] = n.lines["s_nom"] + s_nom_max_ext + + if np.isfinite(p_nom_max_ext) and p_nom_max_ext > 0: + logger.info(f"Limiting line extensions to {p_nom_max_ext} MW") + hvdc = n.links.index[n.links.carrier == "DC"] + n.links.loc[hvdc, "p_nom_max"] = n.links.loc[hvdc, "p_nom"] + p_nom_max_ext + n.lines.s_nom_max.clip(upper=s_nom_max_set, inplace=True) n.links.p_nom_max.clip(upper=p_nom_max_set, inplace=True) @@ -253,12 +268,12 @@ def set_line_nom_max(n, s_nom_max_set=np.inf, p_nom_max_set=np.inf): Nyears = n.snapshot_weightings.objective.sum() / 8760.0 costs = load_costs( snakemake.input.tech_costs, - snakemake.config["costs"], - snakemake.config["electricity"], + snakemake.params.costs, + snakemake.params.max_hours, Nyears, ) - set_line_s_max_pu(n, snakemake.config["lines"]["s_max_pu"]) + set_line_s_max_pu(n, snakemake.params.lines["s_max_pu"]) for o in opts: m = re.match(r"^\d+h$", o, re.IGNORECASE) @@ -277,11 +292,11 @@ def set_line_nom_max(n, s_nom_max_set=np.inf, p_nom_max_set=np.inf): if "Co2L" in o: m = re.findall("[0-9]*\.?[0-9]+$", o) if len(m) > 0: - co2limit = float(m[0]) * snakemake.config["electricity"]["co2base"] + co2limit = float(m[0]) * snakemake.params.co2base add_co2limit(n, co2limit, Nyears) logger.info("Setting CO2 limit according to wildcard value.") else: - add_co2limit(n, snakemake.config["electricity"]["co2limit"], Nyears) + add_co2limit(n, snakemake.params.co2limit, Nyears) logger.info("Setting CO2 limit according to config value.") break @@ -293,11 +308,13 @@ def set_line_nom_max(n, s_nom_max_set=np.inf, p_nom_max_set=np.inf): add_gaslimit(n, limit, Nyears) logger.info("Setting gas usage limit according to wildcard value.") else: - add_gaslimit(n, snakemake.config["electricity"].get("gaslimit"), Nyears) + add_gaslimit(n, snakemake.params.gaslimit, Nyears) logger.info("Setting gas usage limit according to config value.") break for o in opts: + if "+" not in o: + continue oo = o.split("+") suptechs = map(lambda c: c.split("-", 2)[0], n.carriers.index) if oo[0].startswith(tuple(suptechs)): @@ -322,7 +339,7 @@ def set_line_nom_max(n, s_nom_max_set=np.inf, p_nom_max_set=np.inf): add_emission_prices(n, dict(co2=float(m[0]))) else: logger.info("Setting emission prices according to config value.") - add_emission_prices(n, snakemake.config["costs"]["emission_prices"]) + add_emission_prices(n, snakemake.params.costs["emission_prices"]) break ll_type, factor = snakemake.wildcards.ll[0], snakemake.wildcards.ll[1:] @@ -330,8 +347,10 @@ def set_line_nom_max(n, s_nom_max_set=np.inf, p_nom_max_set=np.inf): set_line_nom_max( n, - s_nom_max_set=snakemake.config["lines"].get("s_nom_max,", np.inf), - p_nom_max_set=snakemake.config["links"].get("p_nom_max,", np.inf), + s_nom_max_set=snakemake.params.lines.get("s_nom_max", np.inf), + p_nom_max_set=snakemake.params.links.get("p_nom_max", np.inf), + s_nom_max_ext=snakemake.params.lines.get("max_extension", np.inf), + p_nom_max_ext=snakemake.params.links.get("max_extension", np.inf), ) if "ATK" in opts: diff --git a/scripts/prepare_sector_network.py b/scripts/prepare_sector_network.py index da6eab726..e0afbcd8c 100644 --- a/scripts/prepare_sector_network.py +++ b/scripts/prepare_sector_network.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Adds all sector-coupling components to the network, including demand and supply technologies for the buildings, transport and industry sectors. @@ -18,18 +17,14 @@ import pandas as pd import pypsa import xarray as xr -from _helpers import ( - generate_periodic_profiles, - override_component_attrs, - update_config_with_sector_opts, -) +from _helpers import generate_periodic_profiles, update_config_with_sector_opts +from add_electricity import calculate_annuity, sanitize_carriers from build_energy_totals import build_co2_totals, build_eea_co2, build_eurostat_co2 from networkx.algorithms import complement from networkx.algorithms.connectivity.edge_augmentation import k_edge_augmentation from pypsa.geo import haversine_pts from pypsa.io import import_components_from_dataframe from scipy.stats import beta -from vresutils.costdata import annuity logger = logging.getLogger(__name__) @@ -51,7 +46,6 @@ def define_spatial(nodes, options): ---------- nodes : list-like """ - global spatial spatial.nodes = nodes @@ -202,12 +196,12 @@ def co2_emissions_year( """ Calculate CO2 emissions in one specific year (e.g. 1990 or 2018). """ - emissions_scope = snakemake.config["energy"]["emissions"] + emissions_scope = snakemake.params.energy["emissions"] eea_co2 = build_eea_co2(snakemake.input.co2, year, emissions_scope) # TODO: read Eurostat data from year > 2014 # this only affects the estimation of CO2 emissions for BA, RS, AL, ME, MK - report_year = snakemake.config["energy"]["eurostat_report_year"] + report_year = snakemake.params.energy["eurostat_report_year"] if year > 2014: eurostat_co2 = build_eurostat_co2( input_eurostat, countries, report_year, year=2014 @@ -243,7 +237,7 @@ def build_carbon_budget(o, input_eurostat, fn, emissions_scope, report_year): carbon_budget = float(o[o.find("cb") + 2 : o.find("ex")]) r = float(o[o.find("ex") + 2 :]) - countries = snakemake.config["countries"] + countries = snakemake.params.countries e_1990 = co2_emissions_year( countries, input_eurostat, opts, emissions_scope, report_year, year=1990 @@ -254,7 +248,7 @@ def build_carbon_budget(o, input_eurostat, fn, emissions_scope, report_year): countries, input_eurostat, opts, emissions_scope, report_year, year=2018 ) - planning_horizons = snakemake.config["scenario"]["planning_horizons"] + planning_horizons = snakemake.params.planning_horizons t_0 = planning_horizons[0] if "be" in o: @@ -362,7 +356,6 @@ def update_wind_solar_costs(n, costs): Update costs for wind and solar generators added with pypsa-eur to those cost in the planning year. """ - # NB: solar costs are also manipulated for rooftop # when distribution grid is inserted n.generators.loc[n.generators.carrier == "solar", "capital_cost"] = costs.at[ @@ -394,7 +387,7 @@ def update_wind_solar_costs(n, costs): with xr.open_dataset(profile) as ds: underwater_fraction = ds["underwater_fraction"].to_pandas() connection_cost = ( - snakemake.config["lines"]["length_factor"] + snakemake.params.length_factor * ds["average_distance"].to_pandas() * ( underwater_fraction @@ -440,7 +433,6 @@ def add_carrier_buses(n, carrier, nodes=None): """ Add buses to connect e.g. coal, nuclear and oil plants. """ - if nodes is None: nodes = vars(spatial)[carrier].nodes location = vars(spatial)[carrier].locations @@ -487,9 +479,8 @@ def remove_elec_base_techs(n): batteries and H2) from base electricity-only network, since they're added here differently using links. """ - - for c in n.iterate_components(snakemake.config["pypsa_eur"]): - to_keep = snakemake.config["pypsa_eur"][c.name] + for c in n.iterate_components(snakemake.params.pypsa_eur): + to_keep = snakemake.params.pypsa_eur[c.name] to_remove = pd.Index(c.df.carrier.unique()).symmetric_difference(to_keep) if to_remove.empty: continue @@ -679,7 +670,7 @@ def add_dac(n, costs): def add_co2limit(n, nyears=1.0, limit=0.0): logger.info(f"Adding CO2 budget limit as per unit of 1990 levels of {limit}") - countries = snakemake.config["countries"] + countries = snakemake.params.countries sectors = emission_sectors_from_opts(opts) @@ -732,7 +723,7 @@ def cycling_shift(df, steps=1): return df -def prepare_costs(cost_file, config, nyears): +def prepare_costs(cost_file, params, nyears): # set all asset costs and other parameters costs = pd.read_csv(cost_file, index_col=[0, 1]).sort_index() @@ -744,10 +735,10 @@ def prepare_costs(cost_file, config, nyears): costs.loc[:, "value"].unstack(level=1).groupby("technology").sum(min_count=1) ) - costs = costs.fillna(config["fill_values"]) + costs = costs.fillna(params["fill_values"]) def annuity_factor(v): - return annuity(v["lifetime"], v["discount rate"]) + v["FOM"] / 100 + return calculate_annuity(v["lifetime"], v["discount rate"]) + v["FOM"] / 100 costs["fixed"] = [ annuity_factor(v) * v["investment"] * nyears for i, v in costs.iterrows() @@ -792,7 +783,7 @@ def add_ammonia(n, costs): nodes = pop_layout.index - cf_industry = snakemake.config["industry"] + cf_industry = snakemake.params.industry n.add("Carrier", "NH3") @@ -856,7 +847,7 @@ def add_wave(n, wave_cost_factor): capacity = pd.Series({"Attenuator": 750, "F2HB": 1000, "MultiPA": 600}) # in EUR/MW - annuity_factor = annuity(25, 0.07) + 0.03 + annuity_factor = calculate_annuity(25, 0.07) + 0.03 costs = ( 1e6 * wave_cost_factor @@ -1072,23 +1063,49 @@ def add_storage_and_grids(n, costs): lifetime=costs.at["electrolysis", "lifetime"], ) - n.madd( - "Link", - nodes + " H2 Fuel Cell", - bus0=nodes + " H2", - bus1=nodes, - p_nom_extendable=True, - carrier="H2 Fuel Cell", - efficiency=costs.at["fuel cell", "efficiency"], - capital_cost=costs.at["fuel cell", "fixed"] - * costs.at["fuel cell", "efficiency"], # NB: fixed cost is per MWel - lifetime=costs.at["fuel cell", "lifetime"], - ) + if options["hydrogen_fuel_cell"]: + logger.info("Adding hydrogen fuel cell for re-electrification.") - cavern_types = snakemake.config["sector"]["hydrogen_underground_storage_locations"] + n.madd( + "Link", + nodes + " H2 Fuel Cell", + bus0=nodes + " H2", + bus1=nodes, + p_nom_extendable=True, + carrier="H2 Fuel Cell", + efficiency=costs.at["fuel cell", "efficiency"], + capital_cost=costs.at["fuel cell", "fixed"] + * costs.at["fuel cell", "efficiency"], # NB: fixed cost is per MWel + lifetime=costs.at["fuel cell", "lifetime"], + ) + + if options["hydrogen_turbine"]: + logger.info( + "Adding hydrogen turbine for re-electrification. Assuming OCGT technology costs." + ) + # TODO: perhaps replace with hydrogen-specific technology assumptions. + + n.madd( + "Link", + nodes + " H2 turbine", + bus0=nodes + " H2", + bus1=nodes, + p_nom_extendable=True, + carrier="H2 turbine", + efficiency=costs.at["OCGT", "efficiency"], + capital_cost=costs.at["OCGT", "fixed"] + * costs.at["OCGT", "efficiency"], # NB: fixed cost is per MWel + lifetime=costs.at["OCGT", "lifetime"], + ) + + cavern_types = snakemake.params.sector["hydrogen_underground_storage_locations"] h2_caverns = pd.read_csv(snakemake.input.h2_cavern, index_col=0) - if not h2_caverns.empty and options["hydrogen_underground_storage"]: + if ( + not h2_caverns.empty + and options["hydrogen_underground_storage"] + and set(cavern_types).intersection(h2_caverns.columns) + ): h2_caverns = h2_caverns[cavern_types].sum(axis=1) # only use sites with at least 2 TWh potential @@ -3035,7 +3052,6 @@ def maybe_adjust_costs_and_potentials(n, opts): logger.info(f"changing {attr} for {carrier} by factor {factor}") -# TODO this should rather be a config no wildcard def limit_individual_line_extension(n, maxext): logger.info(f"Limiting new HVAC and HVDC extensions to {maxext} MW") n.lines["s_nom_max"] = n.lines["s_nom"] + maxext @@ -3253,14 +3269,13 @@ def set_temporal_aggregation(n, opts, solver_name): update_config_with_sector_opts(snakemake.config, snakemake.wildcards.sector_opts) - options = snakemake.config["sector"] + options = snakemake.params.sector opts = snakemake.wildcards.sector_opts.split("-") investment_year = int(snakemake.wildcards.planning_horizons[-4:]) - overrides = override_component_attrs(snakemake.input.overrides) - n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides) + n = pypsa.Network(snakemake.input.network) pop_layout = pd.read_csv(snakemake.input.clustered_pop_layout, index_col=0) nhours = n.snapshot_weightings.generators.sum() @@ -3268,7 +3283,7 @@ def set_temporal_aggregation(n, opts, solver_name): costs = prepare_costs( snakemake.input.costs, - snakemake.config["costs"], + snakemake.params.costs, nyears, ) @@ -3280,10 +3295,10 @@ def set_temporal_aggregation(n, opts, solver_name): spatial = define_spatial(pop_layout.index, options) - if snakemake.config["foresight"] == "myopic": + if snakemake.params.foresight == "myopic": add_lifetime_wind_solar(n, costs) - conventional = snakemake.config["existing_capacities"]["conventional_carriers"] + conventional = snakemake.params.conventional_carriers for carrier in conventional: add_carrier_buses(n, carrier) @@ -3352,15 +3367,15 @@ def set_temporal_aggregation(n, opts, solver_name): n = set_temporal_aggregation(n, opts, solver_name) limit_type = "config" - limit = get(snakemake.config["co2_budget"], investment_year) + limit = get(snakemake.params.co2_budget, investment_year) for o in opts: if "cb" not in o: continue limit_type = "carbon budget" fn = "results/" + snakemake.params.RDIR + "/csvs/carbon_budget_distribution.csv" if not os.path.exists(fn): - emissions_scope = snakemake.config["energy"]["emissions"] - report_year = snakemake.config["energy"]["eurostat_report_year"] + emissions_scope = snakemake.params.emissions_scope + report_year = snakemake.params.eurostat_report_year build_carbon_budget( o, snakemake.input.eurostat, fn, emissions_scope, report_year ) @@ -3395,8 +3410,8 @@ def set_temporal_aggregation(n, opts, solver_name): if options["electricity_grid_connection"]: add_electricity_grid_connection(n, costs) - first_year_myopic = (snakemake.config["foresight"] == "myopic") and ( - snakemake.config["scenario"]["planning_horizons"][0] == investment_year + first_year_myopic = (snakemake.params.foresight == "myopic") and ( + snakemake.params.planning_horizons[0] == investment_year ) if options.get("cluster_heat_buses", False) and not first_year_myopic: @@ -3404,4 +3419,6 @@ def set_temporal_aggregation(n, opts, solver_name): n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards))) + sanitize_carriers(n, snakemake.config) + n.export_to_netcdf(snakemake.output[0]) diff --git a/scripts/retrieve_databundle.py b/scripts/retrieve_databundle.py index b3a6cb4e2..75d8519e1 100644 --- a/scripts/retrieve_databundle.py +++ b/scripts/retrieve_databundle.py @@ -3,7 +3,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3517935.svg :target: https://doi.org/10.5281/zenodo.3517935 @@ -24,7 +23,7 @@ tutorial: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`toplevel_cf` **Outputs** @@ -59,9 +58,8 @@ else: url = "https://zenodo.org/record/3517935/files/pypsa-eur-data-bundle.tar.xz" - # Save locations tarball_fn = Path(f"{rootpath}/bundle.tar.xz") - to_fn = Path(f"{rootpath}/data") + to_fn = Path(rootpath) / Path(snakemake.output[0]).parent.parent logger.info(f"Downloading databundle from '{url}'.") disable_progress = snakemake.config["run"].get("disable_progressbar", False) diff --git a/scripts/retrieve_gas_infrastructure_data.py b/scripts/retrieve_gas_infrastructure_data.py index dda7bd8cf..42b726dbd 100644 --- a/scripts/retrieve_gas_infrastructure_data.py +++ b/scripts/retrieve_gas_infrastructure_data.py @@ -29,7 +29,7 @@ # Save locations zip_fn = Path(f"{rootpath}/IGGIELGN.zip") - to_fn = Path(f"{rootpath}/data/gas_network/scigrid-gas") + to_fn = Path(rootpath) / Path(snakemake.output[0]).parent.parent logger.info(f"Downloading databundle from '{url}'.") disable_progress = snakemake.config["run"].get("disable_progressbar", False) diff --git a/scripts/retrieve_sector_databundle.py b/scripts/retrieve_sector_databundle.py index 97426ab21..0d172c8d1 100644 --- a/scripts/retrieve_sector_databundle.py +++ b/scripts/retrieve_sector_databundle.py @@ -10,23 +10,25 @@ logger = logging.getLogger(__name__) -import os -import sys import tarfile from pathlib import Path -# Add pypsa-eur scripts to path for import of _helpers -sys.path.insert(0, os.getcwd() + "/../pypsa-eur/scripts") - from _helpers import configure_logging, progress_retrieve if __name__ == "__main__": + if "snakemake" not in globals(): + from _helpers import mock_snakemake + + snakemake = mock_snakemake("retrieve_databundle") + rootpath = ".." + else: + rootpath = "." configure_logging(snakemake) url = "https://zenodo.org/record/5824485/files/pypsa-eur-sec-data-bundle.tar.gz" - tarball_fn = Path("sector-bundle.tar.gz") - to_fn = Path("data") + tarball_fn = Path(f"{rootpath}/sector-bundle.tar.gz") + to_fn = Path(rootpath) / Path(snakemake.output[0]).parent.parent logger.info(f"Downloading databundle from '{url}'.") disable_progress = snakemake.config["run"].get("disable_progressbar", False) diff --git a/scripts/simplify_network.py b/scripts/simplify_network.py index 5e50c4ab6..9fce8e06e 100644 --- a/scripts/simplify_network.py +++ b/scripts/simplify_network.py @@ -40,7 +40,7 @@ name: .. seealso:: - Documentation of the configuration file ``config.yaml`` at + Documentation of the configuration file ``config/config.yaml`` at :ref:`costs_cf`, :ref:`electricity_cf`, :ref:`renewable_cf`, :ref:`lines_cf`, :ref:`links_cf`, :ref:`solving_cf` @@ -86,22 +86,21 @@ """ import logging -from functools import reduce +from functools import partial, reduce import numpy as np import pandas as pd import pypsa import scipy as sp -from _helpers import configure_logging, get_aggregation_strategies, update_p_nom_max +from _helpers import configure_logging, update_p_nom_max from add_electricity import load_costs from cluster_network import cluster_regions, clustering_for_n_clusters -from pypsa.io import import_components_from_dataframe, import_series_from_dataframe -from pypsa.networkclustering import ( - aggregategenerators, +from pypsa.clustering.spatial import ( aggregateoneport, busmap_by_stubs, get_clustering_from_busmap, ) +from pypsa.io import import_components_from_dataframe, import_series_from_dataframe from scipy.sparse.csgraph import connected_components, dijkstra logger = logging.getLogger(__name__) @@ -112,15 +111,12 @@ def simplify_network_to_380(n): Fix all lines to a voltage level of 380 kV and remove all transformers. The function preserves the transmission capacity for each line while - updating - its voltage level, line type and number of parallel bundles + updating its voltage level, line type and number of parallel bundles (num_parallel). Transformers are removed and connected components are moved from - their - starting bus to their ending bus. The corresponding starting buses - are - removed as well. + their starting bus to their ending bus. The corresponding starting + buses are removed as well. """ logger.info("Mapping all network lines onto a single 380kV layer") @@ -152,17 +148,17 @@ def simplify_network_to_380(n): return n, trafo_map -def _prepare_connection_costs_per_link(n, costs, config): +def _prepare_connection_costs_per_link(n, costs, renewable_carriers, length_factor): if n.links.empty: return {} connection_costs_per_link = {} - for tech in config["renewable"]: + for tech in renewable_carriers: if tech.startswith("offwind"): connection_costs_per_link[tech] = ( n.links.length - * config["lines"]["length_factor"] + * length_factor * ( n.links.underwater_fraction * costs.at[tech + "-connection-submarine", "capital_cost"] @@ -175,10 +171,18 @@ def _prepare_connection_costs_per_link(n, costs, config): def _compute_connection_costs_to_bus( - n, busmap, costs, config, connection_costs_per_link=None, buses=None + n, + busmap, + costs, + renewable_carriers, + length_factor, + connection_costs_per_link=None, + buses=None, ): if connection_costs_per_link is None: - connection_costs_per_link = _prepare_connection_costs_per_link(n, costs, config) + connection_costs_per_link = _prepare_connection_costs_per_link( + n, costs, renewable_carriers, length_factor + ) if buses is None: buses = busmap.index[busmap.index != busmap.values] @@ -248,11 +252,15 @@ def replace_components(n, c, df, pnl): _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus, output) - _, generator_strategies = get_aggregation_strategies(aggregation_strategies) + generator_strategies = aggregation_strategies["generators"] carriers = set(n.generators.carrier) - set(exclude_carriers) - generators, generators_pnl = aggregategenerators( - n, busmap, carriers=carriers, custom_strategies=generator_strategies + generators, generators_pnl = aggregateoneport( + n, + busmap, + "Generator", + carriers=carriers, + custom_strategies=generator_strategies, ) replace_components(n, "Generator", generators, generators_pnl) @@ -268,7 +276,16 @@ def replace_components(n, c, df, pnl): n.mremove(c, df.index[df.bus0.isin(buses_to_del) | df.bus1.isin(buses_to_del)]) -def simplify_links(n, costs, config, output, aggregation_strategies=dict()): +def simplify_links( + n, + costs, + renewables, + length_factor, + p_max_pu, + exclude_carriers, + output, + aggregation_strategies=dict(), +): ## Complex multi-node links are folded into end-points logger.info("Simplifying connected link components") @@ -318,7 +335,9 @@ def split_links(nodes): busmap = n.buses.index.to_series() - connection_costs_per_link = _prepare_connection_costs_per_link(n, costs, config) + connection_costs_per_link = _prepare_connection_costs_per_link( + n, costs, renewables, length_factor + ) connection_costs_to_bus = pd.DataFrame( 0.0, index=n.buses.index, columns=list(connection_costs_per_link) ) @@ -336,12 +355,17 @@ def split_links(nodes): ) busmap.loc[buses] = b[np.r_[0, m.argmin(axis=0), 1]] connection_costs_to_bus.loc[buses] += _compute_connection_costs_to_bus( - n, busmap, costs, config, connection_costs_per_link, buses + n, + busmap, + costs, + renewables, + length_factor, + connection_costs_per_link, + buses, ) all_links = [i for _, i in sum(links, [])] - p_max_pu = config["links"].get("p_max_pu", 1.0) lengths = n.links.loc[all_links, "length"] name = lengths.idxmax() + "+{}".format(len(links) - 1) params = dict( @@ -380,10 +404,6 @@ def split_links(nodes): logger.debug("Collecting all components using the busmap") - exclude_carriers = config["clustering"]["simplify_network"].get( - "exclude_carriers", [] - ) - _aggregate_and_move_components( n, busmap, @@ -395,19 +415,23 @@ def split_links(nodes): return n, busmap -def remove_stubs(n, costs, config, output, aggregation_strategies=dict()): +def remove_stubs( + n, + costs, + renewable_carriers, + length_factor, + simplify_network, + output, + aggregation_strategies=dict(), +): logger.info("Removing stubs") - across_borders = config["clustering"]["simplify_network"].get( - "remove_stubs_across_borders", True - ) + across_borders = simplify_network["remove_stubs_across_borders"] matching_attrs = [] if across_borders else ["country"] busmap = busmap_by_stubs(n, matching_attrs) - connection_costs_to_bus = _compute_connection_costs_to_bus(n, busmap, costs, config) - - exclude_carriers = config["clustering"]["simplify_network"].get( - "exclude_carriers", [] + connection_costs_to_bus = _compute_connection_costs_to_bus( + n, busmap, costs, renewable_carriers, length_factor ) _aggregate_and_move_components( @@ -416,7 +440,7 @@ def remove_stubs(n, costs, config, output, aggregation_strategies=dict()): connection_costs_to_bus, output, aggregation_strategies=aggregation_strategies, - exclude_carriers=exclude_carriers, + exclude_carriers=simplify_network["exclude_carriers"], ) return n, busmap @@ -457,45 +481,42 @@ def aggregate_to_substations(n, aggregation_strategies=dict(), buses_i=None): busmap = n.buses.index.to_series() busmap.loc[buses_i] = dist.idxmin(1) - bus_strategies, generator_strategies = get_aggregation_strategies( - aggregation_strategies - ) + line_strategies = aggregation_strategies.get("lines", dict()) + generator_strategies = aggregation_strategies.get("generators", dict()) + one_port_strategies = aggregation_strategies.get("one_ports", dict()) clustering = get_clustering_from_busmap( n, busmap, - bus_strategies=bus_strategies, aggregate_generators_weighted=True, aggregate_generators_carriers=None, aggregate_one_ports=["Load", "StorageUnit"], line_length_factor=1.0, + line_strategies=line_strategies, generator_strategies=generator_strategies, + one_port_strategies=one_port_strategies, scale_link_capital_costs=False, ) return clustering.network, busmap def cluster( - n, n_clusters, config, algorithm="hac", feature=None, aggregation_strategies=dict() + n, + n_clusters, + focus_weights, + solver_name, + algorithm="hac", + feature=None, + aggregation_strategies=dict(), ): logger.info(f"Clustering to {n_clusters} buses") - focus_weights = config.get("focus_weights", None) - - renewable_carriers = pd.Index( - [ - tech - for tech in n.generators.carrier.unique() - if tech.split("-", 2)[0] in config["renewable"] - ] - ) - clustering = clustering_for_n_clusters( n, n_clusters, custom_busmap=False, aggregation_strategies=aggregation_strategies, - solver_name=config["solving"]["solver"]["name"], + solver_name=solver_name, algorithm=algorithm, feature=feature, focus_weights=focus_weights, @@ -511,92 +532,90 @@ def cluster( snakemake = mock_snakemake("simplify_network", simpl="") configure_logging(snakemake) - n = pypsa.Network(snakemake.input.network) + params = snakemake.params + solver_name = snakemake.config["solving"]["solver"]["name"] - aggregation_strategies = snakemake.config["clustering"].get( - "aggregation_strategies", {} - ) - # translate str entries of aggregation_strategies to pd.Series functions: - aggregation_strategies = { - p: {k: getattr(pd.Series, v) for k, v in aggregation_strategies[p].items()} - for p in aggregation_strategies.keys() - } + n = pypsa.Network(snakemake.input.network) + Nyears = n.snapshot_weightings.objective.sum() / 8760 n, trafo_map = simplify_network_to_380(n) - Nyears = n.snapshot_weightings.objective.sum() / 8760 - technology_costs = load_costs( snakemake.input.tech_costs, - snakemake.config["costs"], - snakemake.config["electricity"], + params.costs, + params.max_hours, Nyears, ) n, simplify_links_map = simplify_links( - n, technology_costs, snakemake.config, snakemake.output, aggregation_strategies + n, + technology_costs, + params.renewable_carriers, + params.length_factor, + params.p_max_pu, + params.simplify_network["exclude_carriers"], + snakemake.output, + params.aggregation_strategies, ) busmaps = [trafo_map, simplify_links_map] - cluster_config = snakemake.config["clustering"]["simplify_network"] - if cluster_config.get("remove_stubs", True): + if params.simplify_network["remove_stubs"]: n, stub_map = remove_stubs( n, technology_costs, - snakemake.config, + params.renewable_carriers, + params.length_factor, + params.simplify_network, snakemake.output, - aggregation_strategies=aggregation_strategies, + aggregation_strategies=params.aggregation_strategies, ) busmaps.append(stub_map) - if cluster_config.get("to_substations", False): - n, substation_map = aggregate_to_substations(n, aggregation_strategies) + if params.simplify_network["to_substations"]: + n, substation_map = aggregate_to_substations(n, params.aggregation_strategies) busmaps.append(substation_map) # treatment of outliers (nodes without a profile for considered carrier): # all nodes that have no profile of the given carrier are being aggregated to closest neighbor - if ( - snakemake.config.get("clustering", {}) - .get("cluster_network", {}) - .get("algorithm", "hac") - == "hac" - or cluster_config.get("algorithm", "hac") == "hac" - ): - carriers = ( - cluster_config.get("feature", "solar+onwind-time").split("-")[0].split("+") - ) + if params.simplify_network["algorithm"] == "hac": + carriers = params.simplify_network["feature"].split("-")[0].split("+") for carrier in carriers: buses_i = list( set(n.buses.index) - set(n.generators.query("carrier == @carrier").bus) ) logger.info( - f"clustering preparaton (hac): aggregating {len(buses_i)} buses of type {carrier}." + f"clustering preparation (hac): aggregating {len(buses_i)} buses of type {carrier}." + ) + n, busmap_hac = aggregate_to_substations( + n, params.aggregation_strategies, buses_i ) - n, busmap_hac = aggregate_to_substations(n, aggregation_strategies, buses_i) busmaps.append(busmap_hac) if snakemake.wildcards.simpl: n, cluster_map = cluster( n, int(snakemake.wildcards.simpl), - snakemake.config, - cluster_config.get("algorithm", "hac"), - cluster_config.get("feature", None), - aggregation_strategies, + params.focus_weights, + solver_name, + params.simplify_network["algorithm"], + params.simplify_network["feature"], + params.aggregation_strategies, ) busmaps.append(cluster_map) # some entries in n.buses are not updated in previous functions, therefore can be wrong. as they are not needed # and are lost when clustering (for example with the simpl wildcard), we remove them for consistency: - buses_c = { + remove = [ "symbol", "tags", "under_construction", "substation_lv", "substation_off", - }.intersection(n.buses.columns) - n.buses = n.buses.drop(buses_c, axis=1) + "geometry", + ] + n.buses.drop(remove, axis=1, inplace=True, errors="ignore") + n.lines.drop(remove, axis=1, errors="ignore", inplace=True) update_p_nom_max(n) diff --git a/scripts/solve_network.py b/scripts/solve_network.py index cfb95bfe6..141d8bc8c 100644 --- a/scripts/solve_network.py +++ b/scripts/solve_network.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Solves optimal operation and capacity for a network with the option to iteratively optimize while updating line reactances. @@ -34,25 +33,21 @@ import pandas as pd import pypsa import xarray as xr -from _helpers import ( - configure_logging, - override_component_attrs, - update_config_with_sector_opts, -) -from vresutils.benchmark import memory_logger +from _helpers import configure_logging, update_config_with_sector_opts logger = logging.getLogger(__name__) pypsa.pf.logger.setLevel(logging.WARNING) +from pypsa.descriptors import get_switchable_as_dense as get_as_dense -def add_land_use_constraint(n, config): +def add_land_use_constraint(n, planning_horizons, config): if "m" in snakemake.wildcards.clusters: - _add_land_use_constraint_m(n, config) + _add_land_use_constraint_m(n, planning_horizons, config) else: - _add_land_use_constraint(n, config) + _add_land_use_constraint(n) -def _add_land_use_constraint(n, config): +def _add_land_use_constraint(n): # warning: this will miss existing offwind which is not classed AC-DC and has carrier 'offwind' for carrier in ["solar", "onwind", "offwind-ac", "offwind-dc"]: @@ -81,10 +76,10 @@ def _add_land_use_constraint(n, config): n.generators.p_nom_max.clip(lower=0, inplace=True) -def _add_land_use_constraint_m(n, config): +def _add_land_use_constraint_m(n, planning_horizons, config): # if generators clustering is lower than network clustering, land_use accounting is at generators clusters - planning_horizons = config["scenario"]["planning_horizons"] + planning_horizons = param["planning_horizons"] grouping_years = config["existing_capacities"]["grouping_years"] current_horizon = snakemake.wildcards.planning_horizons @@ -142,16 +137,24 @@ def add_co2_sequestration_limit(n, limit=200): ) -def prepare_network(n, solve_opts=None, config=None): +def prepare_network( + n, + solve_opts=None, + config=None, + foresight=None, + planning_horizons=None, + co2_sequestration_potential=None, +): if "clip_p_max_pu" in solve_opts: for df in ( n.generators_t.p_max_pu, - n.generators_t.p_min_pu, # TODO: check if this can be removed + n.generators_t.p_min_pu, n.storage_units_t.inflow, ): df.where(df > solve_opts["clip_p_max_pu"], other=0.0, inplace=True) - if solve_opts.get("load_shedding"): + load_shedding = solve_opts.get("load_shedding") + if load_shedding: # intersect between macroeconomic and surveybased willingness to pay # http://journal.frontiersin.org/article/10.3389/fenrg.2015.00055/full # TODO: retrieve color and nice name from config @@ -165,7 +168,7 @@ def prepare_network(n, solve_opts=None, config=None): "Generator", buses_i, " load", - bus=n.buses.index, + bus=buses_i, carrier="load", sign=1e-3, # Adjust sign to measure p and p_nom in kW instead of MW marginal_cost=load_shedding, # Eur/kWh @@ -191,11 +194,11 @@ def prepare_network(n, solve_opts=None, config=None): n.set_snapshots(n.snapshots[:nhours]) n.snapshot_weightings[:] = 8760.0 / nhours - if config["foresight"] == "myopic": - add_land_use_constraint(n, config) + if foresight == "myopic": + add_land_use_constraint(n, planning_horizons, config) if n.stores.carrier.eq("co2 stored").any(): - limit = config["sector"].get("co2_sequestration_potential", 200) + limit = co2_sequestration_potential add_co2_sequestration_limit(n, limit=limit) return n @@ -228,8 +231,7 @@ def add_CCL_constraints(n, config): p_nom = n.model["Generator-p_nom"] gens = n.generators.query("p_nom_extendable").rename_axis(index="Generator-ext") - grouper = [gens.bus.map(n.buses.country), gens.carrier] - grouper = xr.DataArray(pd.MultiIndex.from_arrays(grouper), dims=["Generator-ext"]) + grouper = pd.concat([gens.bus.map(n.buses.country), gens.carrier]) lhs = p_nom.groupby(grouper).sum().rename(bus="country") minimum = xr.DataArray(agg_p_nom_minmax["min"].dropna()).rename(dim_0="group") @@ -274,13 +276,13 @@ def add_EQ_constraints(n, o, scaling=1e-1): float_regex = "[0-9]*\.?[0-9]+" level = float(re.findall(float_regex, o)[0]) if o[-1] == "c": - ggrouper = n.generators.bus.map(n.buses.country).to_xarray() - lgrouper = n.loads.bus.map(n.buses.country).to_xarray() - sgrouper = n.storage_units.bus.map(n.buses.country).to_xarray() + ggrouper = n.generators.bus.map(n.buses.country) + lgrouper = n.loads.bus.map(n.buses.country) + sgrouper = n.storage_units.bus.map(n.buses.country) else: - ggrouper = n.generators.bus.to_xarray() - lgrouper = n.loads.bus.to_xarray() - sgrouper = n.storage_units.bus.to_xarray() + ggrouper = n.generators.bus + lgrouper = n.loads.bus + sgrouper = n.storage_units.bus load = ( n.snapshot_weightings.generators @ n.loads_t.p_set.groupby(lgrouper, axis=1).sum() @@ -294,7 +296,7 @@ def add_EQ_constraints(n, o, scaling=1e-1): p = n.model["Generator-p"] lhs_gen = ( (p * (n.snapshot_weightings.generators * scaling)) - .groupby(ggrouper) + .groupby(ggrouper.to_xarray()) .sum() .sum("snapshot") ) @@ -303,7 +305,7 @@ def add_EQ_constraints(n, o, scaling=1e-1): spillage = n.model["StorageUnit-spill"] lhs_spill = ( (spillage * (-n.snapshot_weightings.stores * scaling)) - .groupby(sgrouper) + .groupby(sgrouper.to_xarray()) .sum() .sum("snapshot") ) @@ -372,13 +374,14 @@ def add_SAFE_constraints(n, config): peakdemand = n.loads_t.p_set.sum(axis=1).max() margin = 1.0 + config["electricity"]["SAFE_reservemargin"] reserve_margin = peakdemand * margin - # TODO: do not take this from the plotting config! - conv_techs = config["plotting"]["conv_techs"] - ext_gens_i = n.generators.query("carrier in @conv_techs & p_nom_extendable").index + conventional_carriers = config["electricity"]["conventional_carriers"] + ext_gens_i = n.generators.query( + "carrier in @conventional_carriers & p_nom_extendable" + ).index p_nom = n.model["Generator-p_nom"].loc[ext_gens_i] lhs = p_nom.sum() exist_conv_caps = n.generators.query( - "~p_nom_extendable & carrier in @conv_techs" + "~p_nom_extendable & carrier in @conventional_carriers" ).p_nom.sum() rhs = reserve_margin - exist_conv_caps n.model.add_constraints(lhs >= rhs, name="safe_mintotalcap") @@ -414,7 +417,7 @@ def add_operational_reserve_margin(n, sns, config): 0, np.inf, coords=[sns, n.generators.index], name="Generator-r" ) reserve = n.model["Generator-r"] - lhs = reserve.sum("Generator") + summed_reserve = reserve.sum("Generator") # Share of extendable renewable capacities ext_i = n.generators.query("p_nom_extendable").index @@ -426,10 +429,12 @@ def add_operational_reserve_margin(n, sns, config): .loc[vres_i.intersection(ext_i)] .rename({"Generator-ext": "Generator"}) ) - lhs = lhs + (p_nom_vres * (-EPSILON_VRES * capacity_factor)).sum() + lhs = summed_reserve + (p_nom_vres * (-EPSILON_VRES * capacity_factor)).sum( + "Generator" + ) # Total demand per t - demand = n.loads_t.p_set.sum(axis=1) + demand = get_as_dense(n, "Load", "p_set").sum(axis=1) # VRES potential of non extendable generators capacity_factor = n.generators_t.p_max_pu[vres_i.difference(ext_i)] @@ -441,17 +446,26 @@ def add_operational_reserve_margin(n, sns, config): n.model.add_constraints(lhs >= rhs, name="reserve_margin") + # additional constraint that capacity is not exceeded + gen_i = n.generators.index + ext_i = n.generators.query("p_nom_extendable").index + fix_i = n.generators.query("not p_nom_extendable").index + + dispatch = n.model["Generator-p"] reserve = n.model["Generator-r"] - lhs = n.model.constraints["Generator-fix-p-upper"].lhs - lhs = lhs + reserve.loc[:, lhs.coords["Generator-fix"]].drop("Generator") - rhs = n.model.constraints["Generator-fix-p-upper"].rhs - n.model.add_constraints(lhs <= rhs, name="Generator-fix-p-upper-reserve") + capacity_variable = n.model["Generator-p_nom"].rename( + {"Generator-ext": "Generator"} + ) + capacity_fixed = n.generators.p_nom[fix_i] + + p_max_pu = get_as_dense(n, "Generator", "p_max_pu") + + lhs = dispatch + reserve - capacity_variable * p_max_pu[ext_i] - lhs = n.model.constraints["Generator-ext-p-upper"].lhs - lhs = lhs + reserve.loc[:, lhs.coords["Generator-ext"]].drop("Generator") - rhs = n.model.constraints["Generator-ext-p-upper"].rhs - n.model.add_constraints(lhs >= rhs, name="Generator-ext-p-upper-reserve") + rhs = (p_max_pu[fix_i] * capacity_fixed).reindex(columns=gen_i, fill_value=0) + + n.model.add_constraints(lhs <= rhs, name="Generator-p-reserve-upper") def add_battery_constraints(n): @@ -579,16 +593,16 @@ def extra_functionality(n, snapshots): add_pipe_retrofit_constraint(n) -def solve_network(n, config, opts="", **kwargs): - set_of_options = config["solving"]["solver"]["options"] - solver_options = ( - config["solving"]["solver_options"][set_of_options] if set_of_options else {} - ) - solver_name = config["solving"]["solver"]["name"] - cf_solving = config["solving"]["options"] +def solve_network(n, config, solving, opts="", **kwargs): + set_of_options = solving["solver"]["options"] + solver_options = solving["solver_options"][set_of_options] if set_of_options else {} + solver_name = solving["solver"]["name"] + cf_solving = solving["options"] track_iterations = cf_solving.get("track_iterations", False) min_iterations = cf_solving.get("min_iterations", 4) max_iterations = cf_solving.get("max_iterations", 6) + transmission_losses = cf_solving.get("transmission_losses", 0) + assign_all_duals = cf_solving.get("assign_all_duals", False) # add to network for extra_functionality n.config = config @@ -602,6 +616,8 @@ def solve_network(n, config, opts="", **kwargs): if skip_iterations: status, condition = n.optimize( solver_name=solver_name, + transmission_losses=transmission_losses, + assign_all_duals=assign_all_duals, extra_functionality=extra_functionality, **solver_options, **kwargs, @@ -612,6 +628,8 @@ def solve_network(n, config, opts="", **kwargs): track_iterations=track_iterations, min_iterations=min_iterations, max_iterations=max_iterations, + transmission_losses=transmission_losses, + assign_all_duals=assign_all_duals, extra_functionality=extra_functionality, **solver_options, **kwargs, @@ -651,27 +669,28 @@ def solve_network(n, config, opts="", **kwargs): if "sector_opts" in snakemake.wildcards.keys(): opts += "-" + snakemake.wildcards.sector_opts opts = [o for o in opts.split("-") if o != ""] - solve_opts = snakemake.config["solving"]["options"] + solve_opts = snakemake.params.solving["options"] np.random.seed(solve_opts.get("seed", 123)) - fn = getattr(snakemake.log, "memory", None) - with memory_logger(filename=fn, interval=30.0) as mem: - if "overrides" in snakemake.input.keys(): - overrides = override_component_attrs(snakemake.input.overrides) - n = pypsa.Network( - snakemake.input.network, override_component_attrs=overrides - ) - else: - n = pypsa.Network(snakemake.input.network) - - n = prepare_network(n, solve_opts, config=snakemake.config) + n = pypsa.Network(snakemake.input.network) - n = solve_network( - n, config=snakemake.config, opts=opts, log_fn=snakemake.log.solver - ) + n = prepare_network( + n, + solve_opts, + config=snakemake.config, + foresight=snakemake.params.foresight, + planning_horizons=snakemake.params.planning_horizons, + co2_sequestration_potential=snakemake.params["co2_sequestration_potential"], + ) - n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards))) - n.export_to_netcdf(snakemake.output[0]) + n = solve_network( + n, + config=snakemake.config, + solving=snakemake.params.solving, + opts=opts, + log_fn=snakemake.log.solver, + ) - logger.info("Maximum memory usage: {}".format(mem.mem_usage)) + n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards))) + n.export_to_netcdf(snakemake.output[0]) diff --git a/scripts/solve_operations_network.py b/scripts/solve_operations_network.py index d16b60aa6..1a3855a93 100644 --- a/scripts/solve_operations_network.py +++ b/scripts/solve_operations_network.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT - """ Solves linear optimal dispatch in hourly resolution using the capacities of previous capacity expansion in rule :mod:`solve_network`. @@ -12,13 +11,8 @@ import numpy as np import pypsa -from _helpers import ( - configure_logging, - override_component_attrs, - update_config_with_sector_opts, -) +from _helpers import configure_logging, update_config_with_sector_opts from solve_network import prepare_network, solve_network -from vresutils.benchmark import memory_logger logger = logging.getLogger(__name__) @@ -43,27 +37,17 @@ opts = (snakemake.wildcards.opts + "-" + snakemake.wildcards.sector_opts).split("-") opts = [o for o in opts if o != ""] - solve_opts = snakemake.config["solving"]["options"] + solve_opts = snakemake.params.options np.random.seed(solve_opts.get("seed", 123)) - fn = getattr(snakemake.log, "memory", None) - with memory_logger(filename=fn, interval=30.0) as mem: - if "overrides" in snakemake.input: - overrides = override_component_attrs(snakemake.input.overrides) - n = pypsa.Network( - snakemake.input.network, override_component_attrs=overrides - ) - else: - n = pypsa.Network(snakemake.input.network) - - n.optimize.fix_optimal_capacities() - n = prepare_network(n, solve_opts, config=snakemake.config) - n = solve_network( - n, config=snakemake.config, opts=opts, log_fn=snakemake.log.solver - ) + n = pypsa.Network(snakemake.input.network) - n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards))) - n.export_to_netcdf(snakemake.output[0]) + n.optimize.fix_optimal_capacities() + n = prepare_network(n, solve_opts, config=snakemake.config) + n = solve_network( + n, config=snakemake.config, opts=opts, log_fn=snakemake.log.solver + ) - logger.info("Maximum memory usage: {}".format(mem.mem_usage)) + n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards))) + n.export_to_netcdf(snakemake.output[0])