Multivariate copula procedure for electric vehicle charging event simulation

Johannes Einolander*, Risto Lahdelma

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

31 Lataukset (Pure)

Abstrakti

This paper introduces a novel application area for multivariate copulas in electric vehicle charging event simulation and dependency analysis. We propose a multivariate copula procedure that can be used to generate new synthetic charging events, which retain the complex dependency and correlation structures present in real-world charging events. The paper compares the most popular multivariate copula functions to discover the most reliable one to be used with electric vehicle charging event data. Accurate EV charging event simulation and analysis is crucial in multiple theoretical and practical applications such as charging load and demand response aggregation modelling. Based on multiple goodness-of-fit tests and charging load profiles of simulated charging events, the Student-t copula was found to be the most reliable multivariate copula to be used with EV charging data. Overall, the multivariate copula procedure is effective in analysis and simulation of EV charging events as it retains the inherent variability and complex dependencies of real charging events.

AlkuperäiskieliEnglanti
Artikkeli121718
Sivumäärä11
JulkaisuEnergy
Vuosikerta238
Varhainen verkossa julkaisun päivämäärä11 elokuuta 2021
DOI - pysyväislinkit
TilaJulkaistu - 1 tammikuuta 2022
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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