Published December 3, 2020 | Version v1
Dataset Open

Clim2Power Austria-Germany Case Study

  • 1. University of Natural Resources and Life Sciences, Vienna

Description

This archive contains neural-network-based forecasts of electricity generation and electricity market variables for a Germany-Austria case study conducted within the project Clim2Power. Depending on the selected variable (some time series are shorter), the folder named “C2P Hindcasts” contains forecast time series from 2010 to 2017 for 30 (February, May, August forecasts) respectively 10 (November forecasts) climate model ensemble members. The folder named “C2P Forecasts” contains forecast time series starting from February 2018 to May 2020 for 50 (February, May, August forecasts) respectively 10 (November forecasts) climate model ensemble members.

Both folders are structured as follows:

Subfolder names contain the respective variable name (Wind Electricity Generation, PV Electricity Generation, Electricity Load and Electricity Price/Climate Impact on Electricity Prices) and the short code “AT” for Austria, “DE” for Germany or “ATDE” for both. Within the subfolders, forecast time series are available in CSV, Feather and NetCDF file format. The digits in the single file names within the folder named “C2P Forecasts” denote the forecast start month and year.

Files

C2P Forecasts.zip

Files (12.0 MB)

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