B. Zeng, Houqi Dong, Xuan Wei, Fuqiang Xu, R. Sioshansi, Min Zhang
{"title":"A Bi-Level Programming Approach for Optimal Design of EV Charging Station","authors":"B. Zeng, Houqi Dong, Xuan Wei, Fuqiang Xu, R. Sioshansi, Min Zhang","doi":"10.1109/IAS.2019.8912461","DOIUrl":null,"url":null,"abstract":"This paper proposes a methodology to decide optimal design of grid-connected electric vehicle (EV) charging systems with renewable energy resources (RCS) in the future smart-grid. Distinct from existing studies, the proposed planning model is intended for a fully liberalized market environment and the potential strategic nature of EV users in their charging actions are explicitly considered. To formulate such problem, a bi-level programming framework with equilibrium constraints has been introduced. In this formulation, the optimal configuration plan of RCS and its operation/pricing schemes are determined simultaneously to maximize the total profits of RCS owner, while accounting for the interaction of EV users during the planning horizon; moreover, the potential uncertainties associated with RCS due to the volatility of market prices, renewable availability, and traffic flows are also considered in our planning problem, by using robust optimization approach. The bi-level robust optimization model is transformed into an equivalent single-level linear program, by replacing the lower-level problem with KKT conditions to solve. The simulation results from case studies demonstrate the effectiveness of the proposed approach.","PeriodicalId":376719,"journal":{"name":"2019 IEEE Industry Applications Society Annual Meeting","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Industry Applications Society Annual Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAS.2019.8912461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a methodology to decide optimal design of grid-connected electric vehicle (EV) charging systems with renewable energy resources (RCS) in the future smart-grid. Distinct from existing studies, the proposed planning model is intended for a fully liberalized market environment and the potential strategic nature of EV users in their charging actions are explicitly considered. To formulate such problem, a bi-level programming framework with equilibrium constraints has been introduced. In this formulation, the optimal configuration plan of RCS and its operation/pricing schemes are determined simultaneously to maximize the total profits of RCS owner, while accounting for the interaction of EV users during the planning horizon; moreover, the potential uncertainties associated with RCS due to the volatility of market prices, renewable availability, and traffic flows are also considered in our planning problem, by using robust optimization approach. The bi-level robust optimization model is transformed into an equivalent single-level linear program, by replacing the lower-level problem with KKT conditions to solve. The simulation results from case studies demonstrate the effectiveness of the proposed approach.