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EV Energy Consumption Patterns and Their Correlation With Renewable Power Generation

Starosta, Anna ORCID iD icon 1; Saflekos, Phil 1; Stein, Alexander ORCID iD icon 1; Munzke, Nina ORCID iD icon 1; Hiller, Marc 1
1 Elektrotechnisches Institut (ETI), Karlsruher Institut für Technologie (KIT)

Abstract:

Europe’s biggest electric vehicle (EV) market Germany has set ambitious targets to reduce transport sector emissions by more than 40% by 2030. Electric mobility fueled by renewable energy (RE) is crucial to reaching these goals. However, the rapid proliferation of EVs as well as RE will significantly impact the grid. Especially a negative correlation between EV demand and RE would have adverse effects on grid stability, energy prices as well as security of supply. Taking into account above facts, this paper analyses real-world charging behavior regarding energy demand and parking duration at EV charging stations (EVCS) and correlates the EV load with the fluctuating RE in the German electricity grid over three years. Using the data of more than 9700 public EVCS and K-means clustering as well as the Pearson correlation coefficient, this paper shows several key insights. Firstly, public EVCS demand and solar power match well, with both peaks occuring during noon. Secondly, EVCS demand and wind power show little to negative correlation. Thirdly, 80% of EVCS were still occupied less than 4 hours a day in 2022. Finally, DC charging points are not a surefire success. ... mehr


Originalveröffentlichung
DOI: 10.1109/ITEC60657.2024.10598880
Zugehörige Institution(en) am KIT Elektrotechnisches Institut (ETI)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 19.06.2024
Sprache Englisch
Identifikator ISBN: 979-83-503-1766-4
ISSN: 2473-7631
KITopen-ID: 1000173309
HGF-Programm 37.12.02 (POF IV, LK 01) Design,Operation & Digitalization of the Future Energy Grids
Erschienen in 2024 IEEE Transportation Electrification Conference and Expo (ITEC)
Veranstaltung IEEE Transportation Electrification Conference & Expo (ITEC 2024), Chicago, IL, USA, 19.06.2024 – 21.06.2024
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 1–6
Projektinformation SKALE (BMWK, 01MV19004D)
Schlagwörter electric vehicle, charging, user behavior, clustering, correlation, renewable
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