Electric Vehicle Charging Load Forecasting based on Monte Carlo

Konferenz: ISCTT 2021 - 6th International Conference on Information Science, Computer Technology and Transportation
26.11.2021 - 28.11.2021 in Xishuangbanna, China

Tagungsband: ISCTT 2021

Seiten: 4Sprache: EnglischTyp: PDF

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Wang, Peiwen; Shen, Jin (Business School, Shanghai Dian Ji University, Shanghai, China)

Based on the comparison of the characteristics of conventional electric load forecasting methods, the prediction model of electric vehicle charging load is established by using the four influencing factors of electric vehicle operation law, daily mileage, ownership and charging law. The steps of solving the model by Monte Carlo simulation are introduced in detail. In the example, the electric vehicles are divided into private cars, taxis and buses. According to their characteristics, load forecasting is carried out respectively. Finally, the total electric vehicle charging load of Xuzhou in 2022 is obtained. Finally, the adjustment strategy to reduce the charging load is proposed.