Renken, VolkerVolkerRenkenSorg, MichaelMichaelSorgMarschner, VolkerVolkerMarschnerGerdes, LewinLewinGerdesGerdes, GerhardGerhardGerdesFischer, AndreasAndreasFischer2024-09-132024-09-132018-101879-0682https://media.suub.uni-bremen.de/handle/elib/8277https://doi.org/10.26092/elib/3311The rising penetration of renewable energies became an important issue in the German electricity sector within the past years. In order to plan the required infrastructure for the energy distribution, a detailed knowledge about the complete geographical and temporal power generation compared to the demand is crucial. However, the available data for the renewable power generation in Germany is insufficient due to the complexity of the energy system. For this reason, a comparison between the renewable power generation and the electricity demand is presented for 95 German zip code regions based on real input data with a sample time of 15 min from renewable energy generators. For enhancing the incomplete data, different model-based data filling methods using the data of neighboured regions or additional meteorological data are introduced and compared. As a result, a number of modelling methods, based either on a heuristic model, a wind speed model or a combination of both, has been investigated, leading to similar correlation coefficients of above 80%. Finally, the obtained data set is applied for an analysis with a high spatiotemporal resolution. For three use cases the resulting optimal flow of the inter-regional power transfers is calculated.enCC BY-NC-ND 4.0 (Attribution-NonCommercial-NoDerivatives)https://creativecommons.org/licenses/by-nc-nd/4.0/Renewable energyGeographical distributionSolarWindData-based analysisModel-based data filling600 Technik, Medizin, angewandte Wissenschaften::600 Technik::600 Technik, TechnologieText::Zeitschrift::Wissenschaftlicher Artikel10.26092/elib/3311urn:nbn:de:gbv:46-elib82770