{"title":"电动汽车充电基础设施与电网可再生能源的协同规划","authors":"Bo Wang;Payman Dehghanian;Dongbo Zhao","doi":"10.1109/OAJPE.2023.3245993","DOIUrl":null,"url":null,"abstract":"This paper proposes a new planning model to coordinate the expansion of electric vehicle charging infrastructure (EVCI) and renewables in power grids. Firstly, individual electric vehicle (EV) charging behaviours are modeled considering EV customers adopting smart charging services as the main charging method and those using fast charging, super fast charging and battery swapping services as a complementary charging approach. Next, EV aggregation and the associated system economic dispatch model are built. A novel model predictive control (MPC) learning approach is then proposed to iteratively learn the correlation between different types of EV charging loads and the EV interactions with renewables and other generating units in modern power grids of the future. The simulation results demonstrate that the proposed approach can be used to quantify the ratio of different types of charging loads in a region and strategically guide on the integration of EVs and renewables to achieve the clean energy transition goals. The proposed framework can also be used to decide charging capacity needs in a charging demand zone.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/10045673.pdf","citationCount":"2","resultStr":"{\"title\":\"Coordinated Planning of Electric Vehicle Charging Infrastructure and Renewables in Power Grids\",\"authors\":\"Bo Wang;Payman Dehghanian;Dongbo Zhao\",\"doi\":\"10.1109/OAJPE.2023.3245993\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a new planning model to coordinate the expansion of electric vehicle charging infrastructure (EVCI) and renewables in power grids. Firstly, individual electric vehicle (EV) charging behaviours are modeled considering EV customers adopting smart charging services as the main charging method and those using fast charging, super fast charging and battery swapping services as a complementary charging approach. Next, EV aggregation and the associated system economic dispatch model are built. A novel model predictive control (MPC) learning approach is then proposed to iteratively learn the correlation between different types of EV charging loads and the EV interactions with renewables and other generating units in modern power grids of the future. The simulation results demonstrate that the proposed approach can be used to quantify the ratio of different types of charging loads in a region and strategically guide on the integration of EVs and renewables to achieve the clean energy transition goals. The proposed framework can also be used to decide charging capacity needs in a charging demand zone.\",\"PeriodicalId\":56187,\"journal\":{\"name\":\"IEEE Open Access Journal of Power and Energy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/iel7/8784343/9999142/10045673.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Open Access Journal of Power and Energy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10045673/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Access Journal of Power and Energy","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10045673/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Coordinated Planning of Electric Vehicle Charging Infrastructure and Renewables in Power Grids
This paper proposes a new planning model to coordinate the expansion of electric vehicle charging infrastructure (EVCI) and renewables in power grids. Firstly, individual electric vehicle (EV) charging behaviours are modeled considering EV customers adopting smart charging services as the main charging method and those using fast charging, super fast charging and battery swapping services as a complementary charging approach. Next, EV aggregation and the associated system economic dispatch model are built. A novel model predictive control (MPC) learning approach is then proposed to iteratively learn the correlation between different types of EV charging loads and the EV interactions with renewables and other generating units in modern power grids of the future. The simulation results demonstrate that the proposed approach can be used to quantify the ratio of different types of charging loads in a region and strategically guide on the integration of EVs and renewables to achieve the clean energy transition goals. The proposed framework can also be used to decide charging capacity needs in a charging demand zone.