Load forecasting of electric vehicle charging station based on grey theory and neural network

The rapid development of electric vehicles (EVs) makes the load of electric vehicle charging stations (EVCSs) affect the power grid. Aiming at the low accuracy of charging station load forecasting caused by the number of EVs, temperature and electricity price, and other factors, this paper proposes...

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Autores principales:	Jiawei Feng, Junyou Yang, Yunlu Li, Haixin Wang, Huichao Ji, Wanying Yang, Kang Wang
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Load forecasting Charging station Grey theory Neural network Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/2cfe7b31942a420c83bf5d8e43a3f52e
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spelling	oai:doaj.org-article:2cfe7b31942a420c83bf5d8e43a3f52e2021-11-26T04:32:28ZLoad forecasting of electric vehicle charging station based on grey theory and neural network2352-484710.1016/j.egyr.2021.08.015https://doaj.org/article/2cfe7b31942a420c83bf5d8e43a3f52e2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S235248472100617Xhttps://doaj.org/toc/2352-4847The rapid development of electric vehicles (EVs) makes the load of electric vehicle charging stations (EVCSs) affect the power grid. Aiming at the low accuracy of charging station load forecasting caused by the number of EVs, temperature and electricity price, and other factors, this paper proposes a load forecasting method of EVCSs based on a combination of multivariable residual correction grey model (EMGM) and long short-term memory (LSTM) network. Firstly, load influencing factors are analysed, and the grey theory is introduced into the load forecast of EVCSs. The role of EMGM in taking into account the effects of multiple factors and eliminating cumulative errors is analysed. Then, the EMGM and LSTM networks are combined to establish a mapping from the influencing factor data to the forecast, reducing the load forecast error of EVCs. Simulation and experimental results show that the accuracy of EVCSs’ load forecasting can be improved by this method.Jiawei FengJunyou YangYunlu LiHaixin WangHuichao JiWanying YangKang WangElsevierarticleLoad forecastingCharging stationGrey theoryNeural networkElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENEnergy Reports, Vol 7, Iss , Pp 487-492 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Load forecasting Charging station Grey theory Neural network Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Load forecasting Charging station Grey theory Neural network Electrical engineering. Electronics. Nuclear engineering TK1-9971 Jiawei Feng Junyou Yang Yunlu Li Haixin Wang Huichao Ji Wanying Yang Kang Wang Load forecasting of electric vehicle charging station based on grey theory and neural network
description	The rapid development of electric vehicles (EVs) makes the load of electric vehicle charging stations (EVCSs) affect the power grid. Aiming at the low accuracy of charging station load forecasting caused by the number of EVs, temperature and electricity price, and other factors, this paper proposes a load forecasting method of EVCSs based on a combination of multivariable residual correction grey model (EMGM) and long short-term memory (LSTM) network. Firstly, load influencing factors are analysed, and the grey theory is introduced into the load forecast of EVCSs. The role of EMGM in taking into account the effects of multiple factors and eliminating cumulative errors is analysed. Then, the EMGM and LSTM networks are combined to establish a mapping from the influencing factor data to the forecast, reducing the load forecast error of EVCs. Simulation and experimental results show that the accuracy of EVCSs’ load forecasting can be improved by this method.
format	article
author	Jiawei Feng Junyou Yang Yunlu Li Haixin Wang Huichao Ji Wanying Yang Kang Wang
author_facet	Jiawei Feng Junyou Yang Yunlu Li Haixin Wang Huichao Ji Wanying Yang Kang Wang
author_sort	Jiawei Feng
title	Load forecasting of electric vehicle charging station based on grey theory and neural network
title_short	Load forecasting of electric vehicle charging station based on grey theory and neural network
title_full	Load forecasting of electric vehicle charging station based on grey theory and neural network
title_fullStr	Load forecasting of electric vehicle charging station based on grey theory and neural network
title_full_unstemmed	Load forecasting of electric vehicle charging station based on grey theory and neural network
title_sort	load forecasting of electric vehicle charging station based on grey theory and neural network
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/2cfe7b31942a420c83bf5d8e43a3f52e
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_version_	1718409831246725120

Load forecasting of electric vehicle charging station based on grey theory and neural network

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