The ongoing advances in the electromobility sector, together with increased research efforts in alternative fuel technologies and growing environmental concerns, highlight the necessity and inevitability of shifting away from internal combustion engines and toward electric cars (EVs). However, in order to facilitate and accelerate the broad adoption of EVs, the apprehension of depleting battery power before reaching the next available charging station must be overcome. The present increase in electric vehicle adoption worldwide needs the creation of a well-developed charging infrastructure comprised of a significant number of charging stations. Hence, this study aims to contribute to the research community by creating an open source dataset designed to aid the experiments of researchers in the community related to the optimal placement of electric vehicle charging stations. Furthermore, we also assess and compare several prominent artificial intelligence algorithms on the dataset that we curated for Germany. Our code: https://gitlHib.coni/akaiish12/data-science-Optimal-EV-station-placement
Spatial-Economic Analysis for Optimal Electric Vehicle Charging Station Placement
23.02.2024
762296 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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