Modeling electric vehicle charging patterns: A review

Rémi Lauvergne (), Yannick Perez () and Alberto Tejeda
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Rémi Lauvergne: LGI - Laboratoire Génie Industriel - CentraleSupélec - Université Paris-Saclay, RTE - Réseau de Transport d'Electricité [Paris]
Alberto Tejeda: RTE - Réseau de Transport d'Electricité [Paris]

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Abstract: Electric vehicles (EVs) offer an opportunity to move towards greenhouse gas emission reduction targets by decarbonizing the transport sector as well as reduce local air pollution. However, uncontrolled and simultaneous charging of a significant number of EVs could pose a challenge to electricity grids and generation-load adequacy. Studying these impacts requires a predictive model of EV fleet recharging. Here we review techniques for EV charging pattern modeling and the types of studies they are used for. The paper also introduces the wide range of parameters (vehicle types, charging points, plug-in behavior, etc.) that modeling studies can factor in, and the EV smart charging simulation approaches available. We conclude by proposing a framework for future research on EV load prediction models.

Date: 2022-09-01
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Published in Revue d'économie industrielle , 2022, 178-179, pp.247-286. ⟨10.4000/rei.11816⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04297535

DOI: 10.4000/rei.11816

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