Electric vehicle charging station load forecasting for companies based on travel characteristics

Hengke Ma; Tianyu Liu

doi:10.1117/12.3004275

25 September 2023 Electric vehicle charging station load forecasting for companies based on travel characteristics

Hengke Ma, Tianyu Liu

Proceedings Volume 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023); 127884W (2023) https://doi.org/10.1117/12.3004275
Event: Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 2023, Kuala Lumpur, Malaysia

Abstract

The popularity of electric vehicles has led to an increase in the use of electric vehicles for commuting to work, requiring company charging stations to predict electric vehicle charging loads to aid advance planning. This paper takes into account the method of predicting EV load influenced by the travel characteristics of various types of EVs in a company. A probabilistic model of travel characteristics based on different types of EVs is established and a Monte Carlo simulation method is used to propose a company EV charging load prediction model. Taking a city as an example, the load of electric vehicles of a company in that place is predicted to provide more reliable data support for the planning of electric vehicle charging stations of the company.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hengke Ma and Tianyu Liu "Electric vehicle charging station load forecasting for companies based on travel characteristics", Proc. SPIE 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 127884W (25 September 2023); https://doi.org/10.1117/12.3004275

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