District Energy Model (DEM) Input Data for Switzerland

This repository provides input data for Switzerland used in the District Energy Model (DEM). The datasets were collected from various publicly available sources, pre-processed, and formatted for direct use within the DEM environment. Documentation of the model is available on Read The Docs. The source code of DEM is published on GitHub and can be used under the Apache-2.0 license. A detailed overview of the data sources, compilation procedures, metadata structure, and instructions for incorporating the datasets into the model can be found in the model documentation. Selected datasets that serve as inputs to DEM are listed below together with their relevant publications.The referenced datasets retain their original licences as stated by the publishers; users must comply with these conditions when using the data. Compatible with DEM versions: 0.1.0 Referenced datasets included in this package: Time-series data for wind power Dujardin, J., Lehning, M. (2022). Wind-Topo_model. EnviDat. https://www.doi.org/10.16904/envidat.301. Dujardin, J., & Lehning, M. (2022). Wind‐Topo: Downscaling near‐surface wind fields to high‐resolution topography in highly complex terrain with deep learning. Quarterly Journal of the Royal Meteorological Society, 148(744), 1368-1388. https://doi.org/10.1002/qj.4265 Time-series data for electric vehicle charging demand Parajeles Herrera, M., & Hug, G. (2025). Charging Demand and Flexibility Bounds for Large-Scale BEV Fleets - The Case Study of Switzerland [Data set]. Zenodo. https://doi.org/10.5281/zenodo.16597426 Parajeles Herrera, M & Hug, G. (2025). Modeling Charging Demand and Quantifying Flexibility Bounds for Large-Scale BEV Fleets. 2025 IEEE Kiel PowerTech, Kiel, Germany, 2025, pp. 1-6. DOI: 10.1109/PowerTech59965.2025.11180551