dc.contributor.author | Muessel, Jarusch | |
dc.contributor.author | Ruhnau, Oliver | |
dc.contributor.author | Madlener, Reinhard | |
dc.date.accessioned | 2024-01-04T12:17:17Z | |
dc.date.available | 2024-01-04T12:17:17Z | |
dc.date.created | 2023-10-03T10:28:45Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | iScience. 2023, 26 (10), . | en_US |
dc.identifier.issn | 2589-0042 | |
dc.identifier.uri | https://hdl.handle.net/11250/3109830 | |
dc.description.abstract | 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. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier B. V. | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Accurate and scalable representation of electric vehicles in energy system models: A virtual storage-based aggregation approach | en_US |
dc.title.alternative | Accurate and scalable representation of electric vehicles in energy system models: A virtual storage-based aggregation approach | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.volume | 26 | en_US |
dc.source.journal | iScience | en_US |
dc.source.issue | 10 | en_US |
dc.identifier.doi | 10.1016/j.isci.2023.107816 | |
dc.identifier.cristin | 2181221 | |
dc.source.articlenumber | 107816 | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |