Probabilistic harmonic impact assessment of multiple electric vehicle fast charging

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Senol, Murat and Bayram, I. Safak and Galloway, Stuart; (2024) Probabilistic harmonic impact assessment of multiple electric vehicle fast charging. In: 2024 IEEE Transportation Electrification Conference and Expo (ITEC). 2024 IEEE Transportation Electrification Conference and Expo (ITEC) . IEEE, USA. ISBN 979-8-3503-1766-4 (https://doi.org/10.1109/ITEC60657.2024.10598987)

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Abstract

The fast-charging infrastructure for electric vehicles (EVs) is rapidly expanding to support increasing EV penetration levels. These fast-charging nodes serve large electrical loads through power converters, which could lead to power quality issues such as harmonic distortion. This paper proposes a Monte Carlo-based probabilistic methodology to assess the impacts of simultaneous fast charging on total harmonic distortion (THD) using real-world data. It also examines the THD of multiple EV charging instances against power quality industry standards. The inputs of the Monte Carlo simulation include the harmonic content of four EV charging data based on different state of charge (SoC) levels. The initial and final SoC levels are assumed to be random to mimic real-world operations. Moreover, two case studies are carried out by varying the number of vehicles charging simultaneously, ranging from 1 to 20. The vehicles undergo full charging in the former, whereas EVs are charged up to 80\% SoC in the latter. For both cases, average THD and the probability of exceeding harmonic levels are calculated after one million iterations. The results indicate that allowing EVs to charge fully significantly increases harmonic content and limits the number of EVs that can be charged at the same time. On the other hand, limiting the maximum SoC level to 80% reduces the probability of exceeding the harmonic limits set by power quality standards.

ORCID iDs

Senol, Murat, Bayram, I. Safak ORCID logoORCID: https://orcid.org/0000-0001-8130-5583 and Galloway, Stuart ORCID logoORCID: https://orcid.org/0000-0003-1978-993X;
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