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dc.contributor.authorNatvig, Marit Kjøsnes
dc.contributor.authorJiang, Shanshan
dc.contributor.authorHallsteinsen, Svein Olav
dc.contributor.authorVenticinque, Salvatore
dc.contributor.authorSard, Regina Enrich
dc.date.accessioned2022-04-08T19:10:53Z
dc.date.available2022-04-08T19:10:53Z
dc.date.created2022-01-27T12:23:34Z
dc.date.issued2021
dc.identifier.citationProceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 1nb_NO
dc.identifier.isbn978-3-030-75077-0
dc.identifier.urihttps://hdl.handle.net/11250/2990826
dc.description.abstractAccess to charging is a prerequisite for the transition to electric mobility. There are however challenges related to charging and charging infrastructures, e.g., charging availability, grid capacity during peak hours, and the CO2 intensity of the energy mix provided. This paper suggests measures to be taken in a smart charging ecosystem to mitigate the challenges. The impact of the measures must however be evaluated. The objective of the paper is to suggest an evaluation approach, with focus on quantitative aspects. The measures of relevance, the associated indicators for the impact evaluation, and an overview of the research data needed is provided. In addition, data content examples and calculation details are described for two indicators – the charging flexibility provided by the EV users and the peak to average ratio characterising the load balancing. Scenarios to be evaluated and how simulations are used to complement the evaluation of the demonstrators are addressed.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.ispartofAdvanced Information Networking and Applications: Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 3
dc.relation.ispartofseriesLecture Notes in Networks and Systems;
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleEvaluation Approach for Smart Charging Ecosystem – with Focus on Automated Data Collection and Indicator Calculationsen_US
dc.typeChapteren_US
dc.typePeer revieweden_US
dc.description.versionsubmittedVersionen_US
dc.rights.holder© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AGen_US
dc.source.pagenumber13en_US
dc.identifier.doi10.1007/978-3-030-75078-7_65
dc.identifier.cristin1991260
dc.relation.projectEC/H2020/769016en_US
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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