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Accurate and scalable representation of electric vehicles in energy system models: A virtual storage-based aggregation approach

Urheber*innen
/persons/resource/jarusch.muessel

Müßel,  Jarusch
Potsdam Institute for Climate Impact Research;

Ruhnau,  Oliver
External Organizations;

Madlener,  Reinhard
External Organizations;

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Volltexte (frei zugänglich)

PIIS258900422301893X.pdf
(Verlagsversion), 3MB

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Zitation

Müßel, J., Ruhnau, O., Madlener, R. (2023): Accurate and scalable representation of electric vehicles in energy system models: A virtual storage-based aggregation approach. - iScience, 26, 10, 107816.
https://doi.org/10.1016/j.isci.2023.107816


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_29309
Zusammenfassung
The growing number of electric vehicles (EVs) will challenge the power system, but EVs may also support system balancing via smart charging. Modeling EVs’ system-level impact while respecting computational constraints requires the aggregation of individual profiles. We show that studies typically rely on too few profiles to accurately model EVs’ system-level impact and that a naïve aggregation of individual profiles leads to an overestimation of the fleet’s flexibility potential. To overcome this problem, we introduce a scalable and accurate aggregation approach based on the idea of modeling deviations from an uncontrolled charging strategy as virtual energy storage. We apply this to a German case study and estimate an average flexibility potential of 6.2 kWh/EV, only 10% of the result of a naïve aggregation. We conclude that our approach allows for a more realistic representation of EVs in energy system models and suggest applying it to other flexible assets.