{"title":"基于Stackelberg博弈的零售商、充电站和电动汽车的最优能源交易","authors":"Muhammad Adil, M. P. Mahmud, A. Kouzani, S. Khoo","doi":"10.1109/GlobConHT56829.2023.10087684","DOIUrl":null,"url":null,"abstract":"Integration of electric vehicles (EVs) to address environmental concerns in recent years has motivated system operators to introduce EV s energy trading platforms. In these platforms, different stakeholders participate in energy trade to maximize their utilities. However, it can be challenging to find optimal strategies for EV s' energy demand, charging station (CS) operation, and retailer profit at the same time without impacting the social welfare of the energy trading platform. This article proposes a multilevel energy trading platform for EV s interaction with CS, and a retailer, which is integrated with distributed energy resources. This platform is modeled using a non-cooperative Stackelberg game, with the retailer acting as a leader at the upper level to maximize profit”. However, the CS and EV s act as followers at the lower level trying to minimize their energy costs. We introduced a penalty function to enhance the platform's social welfare. Our price distribution at various ends of the day will motivate more EVs and CS energy trading interactions. The proposed model is a constrained nonlinear optimization problem, programmed in MATLAB R2022a and solved using FMINCON solver.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimal Energy Trade in Retailer, Charging Station, and Electric Vehicles using a Stackelberg Game\",\"authors\":\"Muhammad Adil, M. P. Mahmud, A. Kouzani, S. Khoo\",\"doi\":\"10.1109/GlobConHT56829.2023.10087684\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Integration of electric vehicles (EVs) to address environmental concerns in recent years has motivated system operators to introduce EV s energy trading platforms. In these platforms, different stakeholders participate in energy trade to maximize their utilities. However, it can be challenging to find optimal strategies for EV s' energy demand, charging station (CS) operation, and retailer profit at the same time without impacting the social welfare of the energy trading platform. This article proposes a multilevel energy trading platform for EV s interaction with CS, and a retailer, which is integrated with distributed energy resources. This platform is modeled using a non-cooperative Stackelberg game, with the retailer acting as a leader at the upper level to maximize profit”. However, the CS and EV s act as followers at the lower level trying to minimize their energy costs. We introduced a penalty function to enhance the platform's social welfare. Our price distribution at various ends of the day will motivate more EVs and CS energy trading interactions. The proposed model is a constrained nonlinear optimization problem, programmed in MATLAB R2022a and solved using FMINCON solver.\",\"PeriodicalId\":355921,\"journal\":{\"name\":\"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GlobConHT56829.2023.10087684\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobConHT56829.2023.10087684","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Energy Trade in Retailer, Charging Station, and Electric Vehicles using a Stackelberg Game
Integration of electric vehicles (EVs) to address environmental concerns in recent years has motivated system operators to introduce EV s energy trading platforms. In these platforms, different stakeholders participate in energy trade to maximize their utilities. However, it can be challenging to find optimal strategies for EV s' energy demand, charging station (CS) operation, and retailer profit at the same time without impacting the social welfare of the energy trading platform. This article proposes a multilevel energy trading platform for EV s interaction with CS, and a retailer, which is integrated with distributed energy resources. This platform is modeled using a non-cooperative Stackelberg game, with the retailer acting as a leader at the upper level to maximize profit”. However, the CS and EV s act as followers at the lower level trying to minimize their energy costs. We introduced a penalty function to enhance the platform's social welfare. Our price distribution at various ends of the day will motivate more EVs and CS energy trading interactions. The proposed model is a constrained nonlinear optimization problem, programmed in MATLAB R2022a and solved using FMINCON solver.