Dataset Open Access

Rooftop photovoltaic (PV) potential data for the Swiss building stock

Walch, Alina

The provided dataset contains data for the PV potentials on building rooftops, evaluated for 9.6 M roof surfaces in Switzerland in an hourly temporal resolution. The methodology of the generation of the dataset is described in:

Walch, Alina, Roberto Castello, Nahid Mohajeri, and Jean-Louis Scartezzini. “Big Data Mining for the Estimation of Hourly Rooftop Photovoltaic Potential and Its Uncertainty.” Applied Energy 262 (March 15, 2020): 114404.

In the process of generating this dataset, the following aspects were included:

  • Meteorological conditions in Switzerland (solar radiation, temperature, snow cover)
  • Local shading and sky coverage from surrounding buildings and trees (based on a Digital Surface Model)
  • Obstruction of roof surface due to roof superstructures such as dormers and chimneys (estimated based on data from the canton of Geneva)
  • The panel and inverter efficiencies, as a function of the solar radiation and temperature

Several aspects were estimated and hence include some uncertainty, due to the input datasets and the modelling methodology. For details on the sources of uncertainty and the limitations, please refer to the referenced article. Estimates for these uncertainties are provided alongside the variables. A description of the metadata is provided in the document rooftop_PV_CH_metadata_V1.pdf.

Data description:

The rooftop PV potential data has been computed at monthly-mean-hourly temporal resolution (i.e. 24 hours for each of the 12 months) for each individual roof surface, based on a national roof surface dataset created by SwissTopo (see https://www.uvek-gis.admin.ch/BFE/sonnendach/). The data given in this dataset is aggregated, in order to make the data easier to use for studies inside as well as outside Switzerland, to reduce the file size and to respect license agreements. Two types of aggregation are provided:

  1. Aggregation per building, using the object ID of the SwissBuildings3D cadastre as identifier. 
  2. Aggregation per roof type, separating between 4 categories: Tilt angle, aspect angle, roof area, altitude

If a different type of aggregation or the data per individual roof surface is required, please do not hesitate to get in touch with the authors directly.

This research has been financed by the Swiss National Science Foundation (SNSF) under the National Research Program 75 (Big Data) for the HyEnergy project.
Files (13.7 GB)
Name Size
rooftop_PV_CH_annual_by_building.csv
md5:c72ffea28e46ca935eddc7f7810f3eeb
511.2 MB Download
rooftop_PV_CH_annual_by_category.csv
md5:c62fb7b8ea6e695a4b4b3934d29cf3cf
2.4 MB Download
rooftop_PV_CH_EPV_W_by_building.csv
md5:e68385d46cbb7800034901cb30266eb5
3.3 GB Download
rooftop_PV_CH_EPV_W_by_category.csv
md5:5e1c2224f3b3c66dce1b5cb940ed7bd2
26.7 MB Download
rooftop_PV_CH_EPV_W_std_by_building.csv
md5:5980574b1851bfbc0ea84539eab4ee30
3.3 GB Download
rooftop_PV_CH_EPV_W_std_by_category.csv
md5:b0abcc81faed9856f7dedf9adb8f9152
35.4 MB Download
rooftop_PV_CH_Gt_W_m2_by_building.csv
md5:dc265622cce8e060b292e2f5c35951de
3.3 GB Download
rooftop_PV_CH_Gt_W_m2_by_category.csv
md5:f5ac8841a61ea8e455c6c032d3669bc9
36.9 MB Download
rooftop_PV_CH_Gt_W_m2_std_by_building.csv
md5:6912742861f9c540d85613af80c7e124
3.2 GB Download
rooftop_PV_CH_Gt_W_m2_std_by_category.csv
md5:2cad894ec14e704ca72191fe124a5aa1
36.7 MB Download
rooftop_PV_CH_metadata_V1.pdf
md5:592db0c956bc6fb8b5cee4681a38ee99
168.5 kB Download
  • Walch, Alina, Roberto Castello, Nahid Mohajeri, and Jean-Louis Scartezzini. "Big Data Mining for the Estimation of Hourly Rooftop Photovoltaic Potential and Its Uncertainty." Applied Energy 262 (March 15, 2020): 114404.

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