Under CopyrightWeise, FriedrichFriedrichWeise2023-06-152023-06-152022Note-ID: 00006006https://publica.fraunhofer.de/handle/publica/442604https://doi.org/10.24406/publica-143910.24406/publica-1439Geospatial data is of high relevance in modeling of hydrogen ecosystems, for instance to evaluate available areas, transport distances or existing infrastructure. Spatial clustering can play a key role to group this data in spatial entities depending on geo-technical conditions rather than administrative boundaries. Therefore, I evaluated multiple clustering algorithms with various variables and parameters to find the best spatial resolution fitting to our techno economic modeling done at Fraunhofer ISE. During the talk I will give insights to our applications, the selected data and methodology, my results, and indicators I developed to compare the clustering algorithms beyond the classic sum of squares.enclusteringenergy system modelingHydrogenTechno-economic analysispresentation