Evaluation of Spatial Clustering Algorithms for Analysis and Division of Hydrogen Ecosystems

Geospatial 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.