This library provides a tool to simulate the operation and maintenance phase (O&M) of distributed, land-based, and offshore windfarms using a discrete event simultaion framework.

WOMBAT is written around the SimPy discrete event simulation framework. Additionally, this is supported using a flexible and modular object-oriented code base, which enables the modeling of arbitrarily large (or small) windfarms with as many or as few failure and maintenance tasks that can be encoded.

Please note that this is still heavily under development, so you may find some functionality to be incomplete at the current moment, but rest assured the functionality is expanding. With that said, it would be greatly appreciated for issues or PRs to be submitted for any improvements at all, from fixing typos (guaranteed to be a few) to features to testing.

If you use this library please cite our NREL Technical Report:

   @techreport{hammond2022wombat,
      title = {Windfarm Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT)},
      author = {Hammond, Rob and Cooperman, Aubryn},
      abstractNote = {This report provides technical documentation and background on the newly-developed Wind Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT) software. WOMBAT is an open-source model that can be used to obtain cost estimates for operations and maintenance of land-based or offshore wind power plants. The software was designed to be flexible and modular to allow for implementation of new strategies and technological innovations for wind plant maintenance. WOMBAT uses a process-based simulation approach to model day-to-day operations, repairs, and weather conditions. High-level outputs from WOMBAT, including time-based availability and annual operating costs, are found to agree with published results from other models.},
      doi = {10.2172/1894867},
      url = {https://www.osti.gov/biblio/1894867},
      place = {United States},
      year = {2022},
      month = {10},
      institution = {National Renewable Energy Lab. (NREL)},
   }

There a few Jupyter notebooks to get users up and running with WOMBAT in the examples/ folder, but here are a few highlights:

Note In v0.6 the results will diverge significantly under certain modeling conditions from past versions due to substantial model upgrades on the backend and new/updated features to better specify how repairs are managed.

• Dinwoodie, et al. replication for wombat can be found in the examples folder <https://github.com/WISDEM/WOMBAT/blob/main/examples/dinwoodie_validation.ipynb>_.
• IEA Task 26 validation exercise <https://github.com/WISDEM/WOMBAT/blob/main/examples/iea_26_validation.ipynb>_.
• Presentations: slides <https://github.com/WISDEM/WOMBAT/blob/main/presentation_material/>_.

• Python 3.9 through 3.12

Download the latest version of Miniconda for the appropriate OS. Follow the remaining steps for the appropriate OS version.

Using conda, create a new virtual environment:

conda create -n <environment_name> python=3.11
conda activate <environment_name>
conda install -c anaconda pip

# activate the environment
conda activate <environment_name>

# to deactivate
conda deactivate

Once in your desired environment, WOMBAT can be installed from PyPI via pip install or from source.

This option is best for those working with the latest release, or including WOMBAT as a tool in a workflow without the desire to modify the source code.

pip install wombat

This option is ideal for users that wish to work with the examples, modify the source code, and/or contribute back to the project.

Install it directly into an activated virtual environment:

git clone https://github.com/WISDEM/WOMBAT.git
cd wombat
python setup.py install

# Alternatively:
pip install .

After installation, the package can imported:

python
import wombat
wombat.__version__

For further usage, please see the documentation site at https://wisdem.github.io/WOMBAT.

Code contributors should note that there is both an additional dependency suite for running the tests and enabling the pre-commit workflow to automatically standardize the core code formatting principles. In short, the following steps should be taken, but be sure to read the contributor's guide

git clone https://github.com/WISDEM/WOMBAT.git
cd wombat

# Install the additional dependencies for running the tests and automatic code formatting
pip install -e '.[dev]'

# Enable the pre-commit workflow for automatic code formatting
pre-commit install

# ... contributions and commits ...

# Run the tests and ensure they all pass
pytest tests

Basic pre-commit issues that users might encounter and their remedies:

• For any failed run, changes may have been either automatically applied or require further edits from the contributor. In either case, after changes have been made, contributors will have to rerun git add <the changed files> and git commit -m <the commit message> to restart the pre-commit workflow with the applied changes. Once all checks pass, the commit is safe to be pushed.
• isort, black, or simple file checks failed, but made changes
  • rerun the add and commit processes as needed until the changes satisfy the checks
• ruff failed:
  • Address the errors and rerun the add and commit processes
• mypy has type errors that seem incorrect
  • Double check the typing is in fact as correct as it seems it should be and rerun the add and commit processes
  • If mypy simply seems confused with seemingly correct types, the following statement can be added above the mypy error: assert isinstance(<variable of concern>, <the type you think mypy should be registering>)
  • If that's still not working, but you are definitely sure the types are correct, simply add a # type ignore comment at the end of the line. Sometimes mypy struggles with complex scenarios, or especially with certain attrs conventions.

git clone https://github.com/WISDEM/WOMBAT.git
cd wombat
pip install -e '.[docs]'

Build the site

Note You may want to change the "execute_notebooks" parameter in the docs/_config.yaml file to "off" unless you're updating the coded examples, or they will be run every time you build the site.

jupyter-book build docs

View the results: docs/_build/html/index.html

git clone https://github.com/WISDEM/WOMBAT.git
cd wombat
pip install -e '.[all]'

Standard dependencies:

• attrs>=21
• numpy>=1.21
• scipy>=1.8
• pandas>=2
• polars>=0.17
• pyarrow>=10
• jupyterlab>=3
• simpy>=4.0.1
• pyyaml>=6
• geopy>=2.3
• networkx>=2.7
• matplotlib>=3.3
• types-attrs>=19
• types-typed-ast>=1.5
• types-PyYAML>=6
• types-python-dateutil>=2.8

Optional "dev" dependencies:

• pre-commit>=2.20
• isort>=5.10
• pytest>=7
• pytest-cov>=4
• mypy==0.991
• ruff>=0.2
• pyupgrade

Optional "docs" dependencies:

• jupyter-book>=0.15
• myst-nb>=0.16
• myst-parser>=0.17
• linkify-it-py>=2
• sphinx-autodoc-typehints
• sphinxcontrib-autoyaml
• sphinxcontrib-bibtex>=2.4
• sphinxcontrib-spelling>=7