{"title":"智能电网中的纳什均衡电力组合:一种遗传退火解决方案","authors":"G. Longoria, Lei Shi","doi":"10.1109/SGCF.2017.7947601","DOIUrl":null,"url":null,"abstract":"To leverage the potential of bilateral contracts in the smart grid, we address the conflict-of-interest problem of designing energy portfolios. From the viewpoint of competing Utility companies, we present a game theoretical formulation for contract offering with integration of wind energy. We propose a heuristic algorithm, the Recursive Genetic Annealing algorithm (RGAn), to find the Nash-Equilibrium solution, that is, the best trade-off between cost and uncertainty. To hedge the portfolios, we model the decision making process as a non-cooperative game. Expected Utility theory is used to define the minimum cost energy mix. We show the RGAn outperforms the genetic algorithm.","PeriodicalId":207857,"journal":{"name":"2017 5th International Istanbul Smart Grid and Cities Congress and Fair (ICSG)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Nash-equilibrium electricity portfolios in the smart grid: A genetic annealing solution\",\"authors\":\"G. Longoria, Lei Shi\",\"doi\":\"10.1109/SGCF.2017.7947601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To leverage the potential of bilateral contracts in the smart grid, we address the conflict-of-interest problem of designing energy portfolios. From the viewpoint of competing Utility companies, we present a game theoretical formulation for contract offering with integration of wind energy. We propose a heuristic algorithm, the Recursive Genetic Annealing algorithm (RGAn), to find the Nash-Equilibrium solution, that is, the best trade-off between cost and uncertainty. To hedge the portfolios, we model the decision making process as a non-cooperative game. Expected Utility theory is used to define the minimum cost energy mix. We show the RGAn outperforms the genetic algorithm.\",\"PeriodicalId\":207857,\"journal\":{\"name\":\"2017 5th International Istanbul Smart Grid and Cities Congress and Fair (ICSG)\",\"volume\":\"83 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 5th International Istanbul Smart Grid and Cities Congress and Fair (ICSG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SGCF.2017.7947601\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Istanbul Smart Grid and Cities Congress and Fair (ICSG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SGCF.2017.7947601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Nash-equilibrium electricity portfolios in the smart grid: A genetic annealing solution
To leverage the potential of bilateral contracts in the smart grid, we address the conflict-of-interest problem of designing energy portfolios. From the viewpoint of competing Utility companies, we present a game theoretical formulation for contract offering with integration of wind energy. We propose a heuristic algorithm, the Recursive Genetic Annealing algorithm (RGAn), to find the Nash-Equilibrium solution, that is, the best trade-off between cost and uncertainty. To hedge the portfolios, we model the decision making process as a non-cooperative game. Expected Utility theory is used to define the minimum cost energy mix. We show the RGAn outperforms the genetic algorithm.