{"title":"Resilience enhancement for power distribution networks in coordination with electric vehicle fleets","authors":"Qianyu Dong , Guanyu Zhou , Qilin Huang , Zhaoyang Dong , Youwei Jia","doi":"10.1016/j.apenergy.2025.125756","DOIUrl":null,"url":null,"abstract":"<div><div>With the global shift towards decarbonized transportation, the adoption of company-owned electric vehicle (EV) fleets is rapidly increasing worldwide. This paper explores the potential of these EV fleets to enhance resilience in power distribution networks through strategic charging station planning and effective post-disaster restoration. Towards this end, a tri-level optimization model is proposed to tackle i) the optimal location problem for charging stations considering grid resilience, and ii) the post-disaster restoration challenge by incentivizing EV fleets for backup power provision. Specifically, multiple performance indices are proposed within the coupled network to facilitate optimal charging station deployment. In addition, an advanced choice model is constructed to analyze the behavioral tendencies of fleet operators. To resolve the proposed model, an accelerated nested column-and-constraint generation (A-NC&CG) algorithm is presented. Numerical case studies performed on two illustrative coupled networks demonstrate that the proposed model can incentivize EV fleets to enhance grid resilience cost-effectively.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":"Article 125756"},"PeriodicalIF":10.1000,"publicationDate":"2025-04-01","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/S0306261925004866","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}
引用次数: 0
Abstract
With the global shift towards decarbonized transportation, the adoption of company-owned electric vehicle (EV) fleets is rapidly increasing worldwide. This paper explores the potential of these EV fleets to enhance resilience in power distribution networks through strategic charging station planning and effective post-disaster restoration. Towards this end, a tri-level optimization model is proposed to tackle i) the optimal location problem for charging stations considering grid resilience, and ii) the post-disaster restoration challenge by incentivizing EV fleets for backup power provision. Specifically, multiple performance indices are proposed within the coupled network to facilitate optimal charging station deployment. In addition, an advanced choice model is constructed to analyze the behavioral tendencies of fleet operators. To resolve the proposed model, an accelerated nested column-and-constraint generation (A-NC&CG) algorithm is presented. Numerical case studies performed on two illustrative coupled networks demonstrate that the proposed model can incentivize EV fleets to enhance grid resilience cost-effectively.
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.