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@ARTICLE{Hecht:1024904,
author = {Hecht, Christopher and Figgener, Jan and Li, Xiaohui and
Zhang, Lei and Sauer, Dirk Uwe},
title = {{S}tandard {L}oad {P}rofiles for {E}lectric {V}ehicle
{C}harging {S}tations in {G}ermany {B}ased on
{R}epresentative, {E}mpirical {D}ata},
journal = {Energies},
volume = {16},
number = {6},
issn = {1996-1073},
address = {Basel},
publisher = {MDPI},
reportid = {FZJ-2024-02554},
pages = {2619 -},
year = {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.},
cin = {IEK-12},
ddc = {620},
cid = {I:(DE-Juel1)IEK-12-20141217},
pnm = {1223 - Batteries in Application (POF4-122)},
pid = {G:(DE-HGF)POF4-1223},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000968401500001},
doi = {10.3390/en16062619},
url = {https://juser.fz-juelich.de/record/1024904},
}