Fengyuan Jin;Chengcheng Shao;Ke Li;Xin Jin;Mohammad Shahidehpour;Xifan Wang
{"title":"需求响应中聚合博弈的用户均衡分析","authors":"Fengyuan Jin;Chengcheng Shao;Ke Li;Xin Jin;Mohammad Shahidehpour;Xifan Wang","doi":"10.1109/TPWRS.2024.3438540","DOIUrl":null,"url":null,"abstract":"Demand response (DR) enables numerous small-scale users, as independent decision-makers, to minimize their costs while representing the real-time electricity consumption as an aggregative game. Consequently, the optimal power system operation would be determined by the equilibrium of small users. This paper leverages the user equilibrium (UE) concept based on the real-time electricity price to analyze the DR game for determining the grid load profile. First, the UE condition is introduced based on the aggregative DR game formulation, where no user can profit more by adjusting its consumption. Second, the UE state is proven to be the optimal solution of a convex programming problem, where an efficient solution is provided by the branch and price method. Finally, the properties and potential UE applications are discussed and illustrated by several numerical examples. Compared with the conventional Nash Equilibrium (NE) method, the proposed UE method can model flexible loads in terms of their types, where the proposed solution offers an advantage in terms of its fast computation and shows great potentials in large-scale DR analysis.","PeriodicalId":13373,"journal":{"name":"IEEE Transactions on Power Systems","volume":"40 2","pages":"1903-1915"},"PeriodicalIF":7.2000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"User Equilibrium Analysis of Aggregative Game in Demand Response\",\"authors\":\"Fengyuan Jin;Chengcheng Shao;Ke Li;Xin Jin;Mohammad Shahidehpour;Xifan Wang\",\"doi\":\"10.1109/TPWRS.2024.3438540\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Demand response (DR) enables numerous small-scale users, as independent decision-makers, to minimize their costs while representing the real-time electricity consumption as an aggregative game. Consequently, the optimal power system operation would be determined by the equilibrium of small users. This paper leverages the user equilibrium (UE) concept based on the real-time electricity price to analyze the DR game for determining the grid load profile. First, the UE condition is introduced based on the aggregative DR game formulation, where no user can profit more by adjusting its consumption. Second, the UE state is proven to be the optimal solution of a convex programming problem, where an efficient solution is provided by the branch and price method. Finally, the properties and potential UE applications are discussed and illustrated by several numerical examples. Compared with the conventional Nash Equilibrium (NE) method, the proposed UE method can model flexible loads in terms of their types, where the proposed solution offers an advantage in terms of its fast computation and shows great potentials in large-scale DR analysis.\",\"PeriodicalId\":13373,\"journal\":{\"name\":\"IEEE Transactions on Power Systems\",\"volume\":\"40 2\",\"pages\":\"1903-1915\"},\"PeriodicalIF\":7.2000,\"publicationDate\":\"2024-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Power Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10623334/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Power Systems","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10623334/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
User Equilibrium Analysis of Aggregative Game in Demand Response
Demand response (DR) enables numerous small-scale users, as independent decision-makers, to minimize their costs while representing the real-time electricity consumption as an aggregative game. Consequently, the optimal power system operation would be determined by the equilibrium of small users. This paper leverages the user equilibrium (UE) concept based on the real-time electricity price to analyze the DR game for determining the grid load profile. First, the UE condition is introduced based on the aggregative DR game formulation, where no user can profit more by adjusting its consumption. Second, the UE state is proven to be the optimal solution of a convex programming problem, where an efficient solution is provided by the branch and price method. Finally, the properties and potential UE applications are discussed and illustrated by several numerical examples. Compared with the conventional Nash Equilibrium (NE) method, the proposed UE method can model flexible loads in terms of their types, where the proposed solution offers an advantage in terms of its fast computation and shows great potentials in large-scale DR analysis.
期刊介绍:
The scope of IEEE Transactions on Power Systems covers the education, analysis, operation, planning, and economics of electric generation, transmission, and distribution systems for general industrial, commercial, public, and domestic consumption, including the interaction with multi-energy carriers. The focus of this transactions is the power system from a systems viewpoint instead of components of the system. It has five (5) key areas within its scope with several technical topics within each area. These areas are: (1) Power Engineering Education, (2) Power System Analysis, Computing, and Economics, (3) Power System Dynamic Performance, (4) Power System Operations, and (5) Power System Planning and Implementation.