CH-RPV300: Hourly Rooftop-PV Potential Profiles in Switzerland

DOI

Hourly rooftop photovoltaic (RPV) power generation profiles for Switzerland, covering 12 weather years (2008--2019) and spatially aggregated to the nodes of the Swiss electricity transmission grid. The dataset resolves 48 orientation and tilt combinations, five installation size classes, and three flat roof design scenarios per grid node, providing approximately 8,550 distinct candidate RPV generators nationwide.

What is in this dataset

  • Hourly generation profiles (power, in Wh) for each grid node, roof orientation, and tilt bin
  • Installed capacity (Wp, in Wp) broken down by size class (1--10, 10--30, 30--100, 100--300, 300--1000 kWp)
  • Normalized capacity factor profiles (specificPower, in Wh/Wp) enabling scaling to arbitrary deployment levels
  • Voronoi grid shapefiles defining the spatial aggregation zones around each transmission node.

Flat roof scenarios

Flat roofs (~23% of Swiss roof area) allow different module configurations. Three scenarios are included: - Winter — South-facing, 35° tilt, GCR 0.45 — optimizes winter yield (Oct–Mar) - Annual — South-facing, 15° tilt, GCR 0.70 — optimizes annual yield - Flat-EW — East-West alternating, 15° tilt, GCR 1.04 — maximizes total installed capacity

Tilted roofs (tilt > 0) are identical in all three scenarios.

Methodology

Generation profiles are derived from satellite-based hourly surface solar radiation data (HelioMont), downscaled to 300 m resolution using the NASADEM digital elevation model with terrain-scale shading and ground reflection (CH-POA300). The national roof inventory Sonnendach (v1.5) provides orientation, tilt, and area for over 10 million roof surfaces. A simplified PV system model (module efficiency 20%, performance ratio 0.8, roof cover factor 0.7) converts irradiance to AC power output. Only roofs with an installed capacity >= 1 kWp are included.

Two grid versions

  • v1 — 135 nodes, CRS EPSG:21781
  • v2 — 126 nodes, CRS EPSG:21781

File format

NetCDF-4 files, one per year and scenario. See DATA_DESCRIPTION.md included in the dataset for the full data model, coordinate definitions, and usage examples.

Identifier
DOI https://doi.org/10.16904/envidat.733
Metadata Access https://www.envidat.ch/api/action/package_show?id=73f6cac8-6a0e-469b-8eed-a9e7fcd75bb8
Provenance
Creator Yael, Frischholz, 0009-0001-2643-9260; Samuel, Renggli,; Ali, Darudi, 0000-0001-7164-6587; Jonas, Savelsberg, call_made external page: ORCID ID:0000-0003-2425-6214
Publisher EnviDat
Publication Year 2026
Funding Reference Innosuisse, 47985.1 IP-EE; Speed2Zero,
Rights cc-by-sa; Creative Commons Attribution Share-Alike (CC-BY-SA)
OpenAccess true
Contact envidat(at)wsl.ch
Representation
Resource Type Dataset
Discipline Environmental Sciences
Spatial Coverage (5.956W, 45.818S, 10.492E, 47.808N)
Temporal Coverage Begin 2025-10-01T00:00:00Z
Temporal Coverage End 2026-02-28T00:00:00Z