Paper
10 October 2023 Research on load forecasting method for electric vehicle cluster charging in distribution network
Shenghao Jin, Yi Zhang, Feng Zhang, Yutao Qiu, Jianguo Mo, Xiahui Xie, Jiaying Miao, Jiayi Zhu
Author Affiliations +
Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279944 (2023) https://doi.org/10.1117/12.3005931
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia
Abstract
With the implementation of China's green and low-carbon development strategy, electric vehicles have increasingly become a means of transportation and a priority choice for people's consumption. Their centralized charging behavior will have a significant impact on the safe operation of the power grid and the overall energy conservation of society. This article delves into the consumption behavior of electric vehicle users through preliminary research, with the goal of optimizing and improving the charging prediction level of electric vehicle clusters. Through the prediction of electric vehicle charging behavior, modeling of electric vehicle loads, and post evaluation of prediction effects, a suitable optimization method for predicting the charging load of electric vehicle clusters in distribution stations is proposed, In order to serve the rapidly growing demand for electric vehicle charging and limit the safe operating capacity of low-voltage distribution stations. The research results have significant socio-economic benefits and have good promotion and demonstration value.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Shenghao Jin, Yi Zhang, Feng Zhang, Yutao Qiu, Jianguo Mo, Xiahui Xie, Jiaying Miao, and Jiayi Zhu "Research on load forecasting method for electric vehicle cluster charging in distribution network", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279944 (10 October 2023); https://doi.org/10.1117/12.3005931
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KEYWORDS
Power grids

Data modeling

Fuzzy logic

Fuzzy systems

Error analysis

Batteries

Neural networks

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