Positive Energy Districts in Switzerland : Analysis from a Technical, Social and Business Point of View - Data and Python code for the technical approach.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides open-source data and Python code for building-level energy balance modeling and optimization, useful for replicating PED studies.

🏢実務担当者:Offers a technical framework for assessing solar PV potential and energy exchange in districts, aiding in energy planning.

Data files description :  Car_Canton_Somme_Model1.parquet : Contains the first model used to calculate the energy consumption per household of the Swiss vehicle fleet.  Car_Canton_Somme_Model1_V2.parquet : Contains the optimised version of the first model selected to calculate the energy consumption per household of the Swiss vehicle fleet.  regions_DMorais.parquet : A file containing geographical coordinates used to link the PEDSET Regions defined in the project to physical coordinates. df_bilan_bati.parquet  : Contains the calculation of the energy balance per building used exclusively for residential purposes. This dataset enables the calculation of the Positive Energy Ratio per dwelling, which serves as an input value for the energy network model. df_bil_reg1.parquet : Contains the calculation of the aggregated energy balance by PEDSET Regions ( regions_DMorais.parquet ) df_bil_dis2.parquet : Contains the calculation of the aggregated energy balance by District. df_bil_comm2.parquet  : Contains the calculation of the aggregated energy balance by Municipality. Description of Python codes: Bat_clustering_V9.py : This calculation script uses energy and geographical data on dwellings sourced from various organisations * to construct a dataset containing energy balances at different spatial scales (buildings, municipalities, districts, regions). This dataset is used by Bat_clustering_V9_Plot.py as an input file. Bat_clustering_V9_Plot.py : A calculation and analysis script that displays and compares various energy-related results, such as rooftop solar generation in relation to solar generation on building façades. The output files from this script are primarily figures.  Bat_clustering_10.py : A calculation script similar to Bat_clustering_V9.py and operating on the same principle. It differs from its predecessor in that it compiles the Positive Energy Ratio by building and includes a model to quantify the difficulty of deploying rooftop PV panel technology by calculating a return on investment. Bat_clustering_V10_Plot.py : A calculation and analysis script that displays and compares various energy results generated by Bat_clustering_10.py .  ConvexOptim_graph_v3.py : Computational code using a convex optimisation problem based on the Positive Energy Ratio, enabling the simulation of potential energy exchange between energy-surplus buildings and energy-deficit buildings, thereby creating a quasi-energy network.   * The balance sheet is calculated using existing databases from the Federal Statistical Office, the Federal Office of Energy, the Federal Office for Housing and the Federal Office for Spatial Planning. It is supplemented by annual figures from Swissolar, VESE.ch, Suisse-eole and the SIA Standards. All geographical data are referenced to the CH1903+ / LV95 model (crs: EPSG:2056) This project was funded by the Swiss National Science Foundation (SNSF) under contract 205'436, as part of the COST ACTION CA 19126 PED-EU-NET-Positive Energy Districts European Network, whose support made this project possible.

• Zenodo https://zenodo.org/records/21239499first seen 2026-07-12 04:15:03 · last seen 2026-07-12 04:17:06