{"title":"考虑市场动态和电网交互的电动汽车充电站运行研究综述","authors":"Saheb Ghanbari Motlagh, Jamiu Oladigbolu, Li Li","doi":"10.1016/j.apenergy.2025.126058","DOIUrl":null,"url":null,"abstract":"<div><div>The growing adoption of Electric Vehicles (EVs) presents pressing challenges and opportunities for power systems and market dynamics. This paper comprehensively reviews state-of-the-art operational optimization techniques for EV charging, including model predictive control, reinforcement learning, and distributed approaches. The study examines strategies to address uncertainties in renewable generation, market pricing, and EV charging behavior. Advanced pricing schemes like distribution locational marginal pricing and game-based methods are explored to align profitability with system stability. The significance of bidirectional charging in reducing peak loads, supporting ancillary services, and balancing battery degradation with user satisfaction is also discussed. Finally, emerging challenges in privacy, multi-energy coupling, and regulation are presented, emphasizing research directions to enhance grid resilience, economic viability, and sustainability. This review offers valuable insights for policymakers, energy utilities, and EV stakeholders to facilitate a smooth and cost-effective transition toward an electrified and decarbonized transportation and power sector.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"392 ","pages":"Article 126058"},"PeriodicalIF":11.0000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A review on electric vehicle charging station operation considering market dynamics and grid interaction\",\"authors\":\"Saheb Ghanbari Motlagh, Jamiu Oladigbolu, Li Li\",\"doi\":\"10.1016/j.apenergy.2025.126058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The growing adoption of Electric Vehicles (EVs) presents pressing challenges and opportunities for power systems and market dynamics. This paper comprehensively reviews state-of-the-art operational optimization techniques for EV charging, including model predictive control, reinforcement learning, and distributed approaches. The study examines strategies to address uncertainties in renewable generation, market pricing, and EV charging behavior. Advanced pricing schemes like distribution locational marginal pricing and game-based methods are explored to align profitability with system stability. The significance of bidirectional charging in reducing peak loads, supporting ancillary services, and balancing battery degradation with user satisfaction is also discussed. Finally, emerging challenges in privacy, multi-energy coupling, and regulation are presented, emphasizing research directions to enhance grid resilience, economic viability, and sustainability. This review offers valuable insights for policymakers, energy utilities, and EV stakeholders to facilitate a smooth and cost-effective transition toward an electrified and decarbonized transportation and power sector.</div></div>\",\"PeriodicalId\":246,\"journal\":{\"name\":\"Applied Energy\",\"volume\":\"392 \",\"pages\":\"Article 126058\"},\"PeriodicalIF\":11.0000,\"publicationDate\":\"2025-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0306261925007883\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306261925007883","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
A review on electric vehicle charging station operation considering market dynamics and grid interaction
The growing adoption of Electric Vehicles (EVs) presents pressing challenges and opportunities for power systems and market dynamics. This paper comprehensively reviews state-of-the-art operational optimization techniques for EV charging, including model predictive control, reinforcement learning, and distributed approaches. The study examines strategies to address uncertainties in renewable generation, market pricing, and EV charging behavior. Advanced pricing schemes like distribution locational marginal pricing and game-based methods are explored to align profitability with system stability. The significance of bidirectional charging in reducing peak loads, supporting ancillary services, and balancing battery degradation with user satisfaction is also discussed. Finally, emerging challenges in privacy, multi-energy coupling, and regulation are presented, emphasizing research directions to enhance grid resilience, economic viability, and sustainability. This review offers valuable insights for policymakers, energy utilities, and EV stakeholders to facilitate a smooth and cost-effective transition toward an electrified and decarbonized transportation and power sector.
期刊介绍:
Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.