Short-Term Load Forecasting of Electric Vehicle Charging Stations Accounting for Multifactor IDBO Hybrid Models

The charging behavior of electric vehicle users is highly stochastic, which makes the short-term prediction of charging load at electric vehicle charging stations difficult. In this paper, a data-driven hybrid model optimized by the improved dung beetle optimization algorithm (IDBO) is proposed to a...

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主要な著者:	Minan Tang, Changyou Wang, Jiandong Qiu, Hanting Li, Xi Guo, Wenxin Sheng
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2024-06-01
シリーズ:	Energies
主題:	data driven electric vehicle charging load convolutional neural network gated recurrent neural network dung beetle optimization algorithm
オンライン･アクセス:	https://www.mdpi.com/1996-1073/17/12/2831
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