UrbanHeatPro

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

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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 to simulate should be included in the input (csv) file.
• By default, the model operates on an hourly time steps. However, the temporal resolution is configurable.

Requirements & Installation

System requirements

The project uses POSIX paths as is standard in UNIX systems such as Linux or macOS. On Windows machines using the WSL is might mitigate possible issues.

Python requirements & dependencies

Python 3.9 or higher (installation with Anaconda recommended).

The latest version was tested with Python 3.10.

Use the provided requirements.txt or the setup.py to install the dependencies via pip.

Installation

There are two ways to install UrbanHeatPro:

1. As a package:

Ideally install the project as an editable package. Inside the root directory of the repository for UrbanHeatPro run:

$ pip install -e .

All dependencies are installed and UrbanHeatPro can be used as the package UrbanHeatPro. This allows to use the folder structure expected by UrbanHeatPro and use it from other packages.

2. As a standalone project with an entry script

To install only the dependencies via pip, run inside the root directory of the repository for UrbanHeatPro:

$ pip install -r requirements.txt

Folder structure & settings

The expects the input files in the input/ directory. Per default the results are written to the results/ directory. A different result directory can be defined in the settings file or as a parameter of run_uhp().

The example and default settings files are in the settings/ directory. Settings are provided to the module as a configuration file in the yaml format. An example of the expected structure can be seen in the example settings file settings/uhp_settings_example.yaml. All possible settings are also shortly described in this file.

Note: Do not move or modify the default settings file settings/uhp_default_settings.yaml. This file is needed in case no other settings are given.

Input files (csv)

An example for the expected input data is given for the region Unterhaching.

Buildings

Each building is described with the following information:

1. Area (required)
   Building ground floor area in m²

2. Use (required)
   Building use as integer:

   • 0 Commercial
   • 1 Industrial
   • 2 Public
   • 3 Residential

3. Bid (optional)
   Building identification number as integer

4. Free_walls (required)
   Number of walls in contact with ambient temperature. The building is assumed to be a rectangular box with four walls.

5. 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
   • 10 >2009

6. 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)

7. Refurbishment level (optional)
   Refurfishment level for all building elements from TABULA Typology as integer:

   • 1 No refurbishment (Existing state)
   • 2 Usual refurbishment
   • 3 Advanced refurbishment

8. Number of occupants (optional)
   Number of occupants living in the building

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.

Regional Data

In addition to the buildings to be modeled, regional data is needed. This data should be placed in the folder input/Regional Data. Each region has its own directory of regional data, e.g. input/Regional Data/Unterhaching.

Using UrbanHeatPro

From the entry script

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

$ python runme.py

As a library or package

Alternatively the model can be used as a library or package. Note: This requires UrbanHeatPro to be installed as a package (see Installation 1). The run_uhp function in the run_uhp.py module is the entrypoint for running the model.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Copyright

Copyright (C) 2018-2021 Anahi Molar-Cruz

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details: http://www.gnu.org/licenses/.