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A bottom-up model for the simulation of heat demand profiles of urban areas

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UrbanHeatPro

Bottom-up model for the simulation of heat demand profiles of urban areas A. Molar-Cruz @ TUM ENS

Features

  • UrbanHeatPro is a python-based bottom-up model for the simulation of heat demand profiles of urban areas.
  • It considers both the space heating demand and hot water demand. So far, the hot water demand is calculated only for residential buildings.
  • Characteristic values for the building stock, building thermal properties, building set-temperature and annual hot water consumption are based on statistics for Germany.
  • DSM strategies for the reduction of heat demand such as building renovation, heat load reduction, night-set back operation, etc, are easily implemented.
  • The size of the study area can start from one building. Buildings can be input as a shapefile or as an excel table.
  • By default, the model operates on an hourly time steps. However, the temporal resolution is configurable.

Requirements

Python 3.6 if multiprocessing is used (installation with Anaconda recommended) Python 2.7 (installation with Anaconda recommended)

Input file (csv)

Each building is described with the following information: A. Area (required) Building ground floor area in m² B. Use (required) Building use as integer: 0 Commercial 1 Industrial 2 Public 3 Residential C. Bid (optional) Building identification number as integer D. Free_walls (required) Number of walls in contact with ambient temperature. The building is assumed to be a rectangular box with four walls. E. Construction year class (optional) Construction year class from TABULA Typology as integer: 0 <1859 1 1860 - 1918 2 1919 - 1948 3 1949 - 1957 4 1958 - 1968 5 1969 - 1978 6 1979 - 1983 7 1984 - 1994 8 1995 - 2001 9 2002 - 2009 F. Building type (optional) Building type from TABULA Typology as integer: 0 Single-Family House (SFH) 1 Terraced House (TH) 2 Multi-family House (MFH) 3 Apartment Block (AB) All columns are required, if no information is given, the cell value is taken as NaN. This input file should be located in the corresponding folder input/buildings

Using UrbanHeatPro

To run the model with the given input data, change the desired information in the runme.py file and run this file in the command line:

python runme.py

For more details please refer to the documentation file

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A bottom-up model for the simulation of heat demand profiles of urban areas

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