Travel activity based stochastic modelling of load and charging state of electric vehicles

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dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorIqbal, Muhammad Naveeden_US
dc.contributor.authorKütt, Laurien_US
dc.contributor.authorLehtonen, Mattien_US
dc.contributor.authorMillar, Robert Johnen_US
dc.contributor.authorPüvi, Verneren_US
dc.contributor.authorRassõlkin, Antonen_US
dc.contributor.authorDemidova, Galina L.en_US
dc.contributor.departmentDepartment of Electrical Engineering and Automationen
dc.contributor.groupauthorPower Systems and High Voltage Engineeringen
dc.contributor.organizationTallinn University of Technologyen_US
dc.contributor.organizationSt. Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO)en_US
dc.date.accessioned2021-02-26T07:12:33Z
dc.date.available2021-02-26T07:12:33Z
dc.date.issued2021-02-02en_US
dc.description.abstractThe uptake of electric vehicles (EV) is increasing every year and will eventually replace the traditional transport system in the near future. This imminent increase is urging stakeholders to plan up-gradation in the electric power system infrastructure. However, for efficient planning to support an additional load, an accurate assessment of the electric vehicle load and power quality indices is required. Although several EV models to estimate the charging profile and additional electrical load are available, but they are not capable of providing a high-resolution evaluation of charging current, especially at a higher frequency. This paper presents a probabilistic approach capable of estimating the time-dependent charging and harmonic currents for the future EV load. The model is based on the detailed travel activities of the existing car owners reported in the travel survey. The probability distribution functions of departure time, distance, arrival time, and time span are calculated. The charging profiles are based on the measurements of several EVs.en
dc.description.versionPeer revieweden
dc.format.extent14
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationIqbal, M N, Kütt, L, Lehtonen, M, Millar, R J, Püvi, V, Rassõlkin, A & Demidova, G L 2021, ' Travel activity based stochastic modelling of load and charging state of electric vehicles ', Sustainability (Switzerland), vol. 13, no. 3, 1550 . https://doi.org/10.3390/su13031550en
dc.identifier.doi10.3390/su13031550en_US
dc.identifier.issn2071-1050
dc.identifier.otherPURE UUID: 5e67f1c6-ca25-4ed9-9c8b-e87ffd25a45cen_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/5e67f1c6-ca25-4ed9-9c8b-e87ffd25a45cen_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85100655150&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/56292522/ELEC_Iqbal_etal_Travel_Activity_Based_Sustainability_13_3_2021_finalpublishedversion.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/102771
dc.identifier.urnURN:NBN:fi:aalto-202102262060
dc.language.isoenen
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.relation.ispartofseriesSustainability (Switzerland)en
dc.relation.ispartofseriesVolume 13, issue 3en
dc.rightsopenAccessen
dc.subject.keywordActivity based modellingen_US
dc.subject.keywordEV charging currenten_US
dc.subject.keywordEV load modelen_US
dc.subject.keywordManaged chargingen_US
dc.subject.keywordSOCen_US
dc.subject.keywordUnmanaged chargingen_US
dc.titleTravel activity based stochastic modelling of load and charging state of electric vehiclesen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion
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