LAPSE:2023.31155v1
Published Article
LAPSE:2023.31155v1
Standard Load Profiles for Electric Vehicle Charging Stations in Germany Based on Representative, Empirical Data
April 18, 2023
Abstract
Electric vehicles are becoming dominant in the global automobile market due to their better environmental friendliness compared to internal combustion vehicles. An adequate network of public charging stations is required to fulfil the fast charging demands of EV users. Knowing the shape and amplitude of their power curves is essential for power purchase planning and grid capacity sizing. Based on a large-scale empirical and representative dataset, this paper creates standard load profiles for various power levels, station sizes, and operating environments. It is found that the average power per charge point increases with rated station power, particularly for a rated power above 100 kW, and decreases with the number of charge points per station for AC chargers. For AC chargers, it is revealed how the shape of the power curve largely depends on the environment of a station, with urban settings experiencing the highest average power of 0.71 kW on average leading to an annual energy sale of 6.2 MWh. These findings show that the rated grid capacity can be well below the sum of the rated power of each charge point.
Keywords
electric vehicles, empirical data analysis, power curve, public charging station, standard load profile
Suggested Citation
Hecht C, Figgener J, Li X, Zhang L, Sauer DU. Standard Load Profiles for Electric Vehicle Charging Stations in Germany Based on Representative, Empirical Data. (2023). LAPSE:2023.31155v1
Author Affiliations
Hecht C: Grid Integration and Storage System Analysis, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, 52074 Aachen, Germany; Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, 52074 Aa [ORCID]
Figgener J: Grid Integration and Storage System Analysis, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, 52074 Aachen, Germany; Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, 52074 Aa [ORCID]
Li X: National Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China [ORCID]
Zhang L: National Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China [ORCID]
Sauer DU: Grid Integration and Storage System Analysis, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, 52074 Aachen, Germany; Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, 52074 Aa [ORCID]
Journal Name
Energies
Volume
16
Issue
6
First Page
2619
Year
2023
Publication Date
2023-03-10
ISSN
1996-1073
Version Comments
Original Submission
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PII: en16062619, Publication Type: Journal Article
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LAPSE:2023.31155v1
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https://doi.org/10.3390/en16062619
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Apr 18, 2023
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