Mid- and long-term strategy based on electric vehicle charging unpredictability and ownership estimation

• Main Authors: Hui, Hwang Goh, Lian Zong, Dongdong Zhang, Hui Liu, Wei Dai, Chee, Shen Lim, Tonni Agustiono Kurniawan, Tze, Kenneth Kin Teo, Kai, Chen Goh
• Format: Article
• Language: English; English
• Published: Elsevier Ltd. 2022
• Subjects: TL1-484 Motor vehicles. Cycles
• Online Access: https://eprints.ums.edu.my/id/eprint/33430/1/Mid-%20and%20long-term%20strategy%20based%20on%20electric%20vehicle%20charging%20unpredictability%20and%20ownership%20estimation.pdf; https://eprints.ums.edu.my/id/eprint/33430/2/Mid-%20and%20long-term%20strategy%20based%20on%20electric%20vehicle%20charging%20unpredictability%20and%20ownership%20estimation1.pdf; https://eprints.ums.edu.my/id/eprint/33430/; https://www.sciencedirect.com/science/article/pii/S0142061522002691?casa_token=ghjLXZKH2E8AAAAA:CH0Rpoc6NzM-gCqaAsAfe7CjtpO8mkKZi8qNW41l9j02ne0P0lbjVO8vXxZGqPs_hiiR9va7zg; https://doi.org/10.1016/j.ijepes.2022.108240

Predicting the charging load of electric vehicles (EVs) is critical for the safe and reliable operation of the distribution network. Analyzing an EV’s random charging characteristics and the uncertainty associated with its development scale are important to accurate prediction of its charging load....