Pre-built V2G Sector-coupled Euro-Calliope Model

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Authors: Francesco Davide Sanvito
Cited by: 1

Abstract

Overview The Pre-built V2G Sector-coupled Euro-Calliope Model is derived from a previous version of the Calliope pre-built models. The model is pre-packaged and ready to be loaded in Calliope. The model includes 35 European countries modelled at NUT0 spatial resolution. The model is extended with the following main features: explicit charging infrastructure (uncontrolled, V1G, and V2G) hourly road transport profiles split into motorcycles (two and three-wheelers), passenger cars, light-duty vehicles, heavy-duty vehicles, and buses. CO2 capture and storage EV and fuel cell powertrain modelling Addition of vehicle costs Detailed installation instructions, a guide to running the model, and a description of the configuration settings are provided in the README.md file. Installation You need a Gurobi license installed on your computer. You may as well choose another solver other than Gurobi. See Calliope’s documentation to understand how to switch to another solver. You need to have Calliope and Gurobi installed in your environment. The easiest way to do so is using conda. Using conda, you can create a conda environment from within which you can build the model (recommended): conda env create -f requirements.yml conda activate calliope-v2g Due to pip and conda conflicts, we advise running these commands once you have created the environment. pip uninstall netcdf4 conda install -c conda-forge netcdf4=1.6.2 hdf5=1.12.2 --strict-channel-priority conda install netcdf4=1.6.2 --force-reinstall Running the model 1. Configure the scenario parameters in `run-example.py`. 2. Run the model using: python run-example.py Model outputs are written to the directory specified in the run script. ⚠️ Warning This model is memory- and computational-time intensive. We strongly recommend first running the model at a lower time resolution. The time resolution can be adjusted in the scenario settings. Make sure the corresponding overrides are added to the `model.yaml` file.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
1 January 2026
Language
EN
Document type
Dataset