Two-Step Intelligent Control for a Green Flexible EV Energy Supply Station Oriented to Dual Carbon Targets

As China proposes to achieve carbon peak by 2030 and carbon neutrality by 2060, as well as the huge pressure on the power grid caused by the load demand of the energy supply stations of electric vehicles (EVs), there is an urgent need to carry out comprehensive energy management and coordinated cont...

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Autores principales:	Shanshan Shi, Chen Fang, Haojing Wang, Jianfang Li, Yuekai Li, Daogang Peng, Huirong Zhao
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	electric vehicle intelligent control integrated energy system dual carbon target Chemical technology TP1-1185 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/85d093050140418daa1c2c5a9db864da
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spelling	oai:doaj.org-article:85d093050140418daa1c2c5a9db864da2021-11-25T18:50:25ZTwo-Step Intelligent Control for a Green Flexible EV Energy Supply Station Oriented to Dual Carbon Targets10.3390/pr91119182227-9717https://doaj.org/article/85d093050140418daa1c2c5a9db864da2021-10-01T00:00:00Zhttps://www.mdpi.com/2227-9717/9/11/1918https://doaj.org/toc/2227-9717As China proposes to achieve carbon peak by 2030 and carbon neutrality by 2060, as well as the huge pressure on the power grid caused by the load demand of the energy supply stations of electric vehicles (EVs), there is an urgent need to carry out comprehensive energy management and coordinated control for EVs’ energy supply stations. Therefore, this paper proposed a two-step intelligent control method known as ISOM-SAIA to solve the problem of the 24 h control and regulation of green/flexible EV energy supply stations, including four subsystems such as a photovoltaic subsystem, an energy storage subsystem, an EV charging subsystem and an EV battery changing subsystem. The proposed control method has two main innovations and contributions. One is that it reduces the computational burden by dividing the multi-dimensional mixed-integer programming problem of simultaneously optimizing the 24 h operation modes and outputs of four subsystems into two sequential tasks: the classification of data-driven operation modes and the rolling optimization of operational outputs. The other is that proper carbon transaction costs and carbon emission constraints are considered to help save costs and reduce carbon emissions. The simulation analysis conducted in this paper indicates that the proposed two-step intelligent control method can help green/flexible EV energy supply stations to optimally allocate energy flows between four subsystems, effectively respond to peak shaving and valley filling of power grid, save energy costs and reduce carbon emissions.Shanshan ShiChen FangHaojing WangJianfang LiYuekai LiDaogang PengHuirong ZhaoMDPI AGarticleelectric vehicleintelligent controlintegrated energy systemdual carbon targetChemical technologyTP1-1185ChemistryQD1-999ENProcesses, Vol 9, Iss 1918, p 1918 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	electric vehicle intelligent control integrated energy system dual carbon target Chemical technology TP1-1185 Chemistry QD1-999
spellingShingle	electric vehicle intelligent control integrated energy system dual carbon target Chemical technology TP1-1185 Chemistry QD1-999 Shanshan Shi Chen Fang Haojing Wang Jianfang Li Yuekai Li Daogang Peng Huirong Zhao Two-Step Intelligent Control for a Green Flexible EV Energy Supply Station Oriented to Dual Carbon Targets
description	As China proposes to achieve carbon peak by 2030 and carbon neutrality by 2060, as well as the huge pressure on the power grid caused by the load demand of the energy supply stations of electric vehicles (EVs), there is an urgent need to carry out comprehensive energy management and coordinated control for EVs’ energy supply stations. Therefore, this paper proposed a two-step intelligent control method known as ISOM-SAIA to solve the problem of the 24 h control and regulation of green/flexible EV energy supply stations, including four subsystems such as a photovoltaic subsystem, an energy storage subsystem, an EV charging subsystem and an EV battery changing subsystem. The proposed control method has two main innovations and contributions. One is that it reduces the computational burden by dividing the multi-dimensional mixed-integer programming problem of simultaneously optimizing the 24 h operation modes and outputs of four subsystems into two sequential tasks: the classification of data-driven operation modes and the rolling optimization of operational outputs. The other is that proper carbon transaction costs and carbon emission constraints are considered to help save costs and reduce carbon emissions. The simulation analysis conducted in this paper indicates that the proposed two-step intelligent control method can help green/flexible EV energy supply stations to optimally allocate energy flows between four subsystems, effectively respond to peak shaving and valley filling of power grid, save energy costs and reduce carbon emissions.
format	article
author	Shanshan Shi Chen Fang Haojing Wang Jianfang Li Yuekai Li Daogang Peng Huirong Zhao
author_facet	Shanshan Shi Chen Fang Haojing Wang Jianfang Li Yuekai Li Daogang Peng Huirong Zhao
author_sort	Shanshan Shi
title	Two-Step Intelligent Control for a Green Flexible EV Energy Supply Station Oriented to Dual Carbon Targets
title_short	Two-Step Intelligent Control for a Green Flexible EV Energy Supply Station Oriented to Dual Carbon Targets
title_full	Two-Step Intelligent Control for a Green Flexible EV Energy Supply Station Oriented to Dual Carbon Targets
title_fullStr	Two-Step Intelligent Control for a Green Flexible EV Energy Supply Station Oriented to Dual Carbon Targets
title_full_unstemmed	Two-Step Intelligent Control for a Green Flexible EV Energy Supply Station Oriented to Dual Carbon Targets
title_sort	two-step intelligent control for a green flexible ev energy supply station oriented to dual carbon targets
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/85d093050140418daa1c2c5a9db864da
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Two-Step Intelligent Control for a Green Flexible EV Energy Supply Station Oriented to Dual Carbon Targets

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