Basic usage

After installation, you can run the EVPV model in command-line mode. This is ideal for users who are not familiar with Python or who want to quickly conduct a simple case study.

First, create a configuration file by copying an existing example such as the AddisAbaba_Simple example case study. Update the configuration file with your own parameters and ensure that all required geospatial input data is available (see the config file and input/ folder for guidance).

Note

We recommend starting by running the Addis Ababa simple example to get familiar with the workflow. The easiest way to access all necessary files is to download the GitHub repository containing the examples as a ZIP file, extract it and copy the contents of the Addis Ababa example folder into the directory of your choice.

Once your config file and geospatial input data are ready, open a terminal, activate your virtual environment (optional), and run:

evpv

You’ll be prompted to enter the path to your config file:

Enter the path to the python configuration file: C:\Users\(...)\config.py

Warning

Use absolute paths in both in the terminal and in the config file, or start the terminal in the same directory as the config file to use relative paths.

Model input parameters and required data

All input parameters are defined and explained in the configuration file you copied.

In addition to numerical and model-specific parameters, you’ll need to provide paths to the following four geospatial data files:

  • Region of interest: A GeoJSON file defining the boundary of your study area. For most administrative regions, you can download this from the GADM dataset.

  • Residential population: A .tif raster file showing population density, in the WGS84 coordinate system. We recommend using the GHS POP dataset at the highest resolution.

  • List of workplaces: A CSV file with the following columns: name, latitude, longitude, and weight. You can generate this manually using you own data or automatically extract it from OpenStreetMap using the helper script in evpv.tools.

  • List of POIs (Points of Interest): Same format and process as for workplaces. Use the same script but with modified inputs.

Note

Need help in gathering the needed geospatial data for your own case study? See the evpv.tools.

Model Outputs

After running the simulation, the model generates output files organized into three main subfolders:

  • Mobility/: Data and interactive maps related to the mobility demand simulation. Includes vehicle flows, travel distances, and aggregated data for the region of interest.

  • ChargingDemand/: Charging demand outputs, including spatial and temporal demand per vehicle and per traffic zone. Also includes HTML maps for visualization.

  • EVPV/: PV production curves and EV–PV complementarity indicators.