{"title":"A Power Portfolio Method using DR- CVaR in Renewable Power Systems","authors":"Feifei Zhao, Xingning Han, Qinxin Huang, Yiqing Xu, Zhuyi Peng","doi":"10.1109/POWERCON53785.2021.9697515","DOIUrl":null,"url":null,"abstract":"A great uncertainty exists in the operation of power market, but the stable operation of the market is of extreme importantance. Considering the uncertainty of probability distribution of electricity price in multi-energy markets as well as the premise of guaranteeing distributional robust conditional value-at-risk constraint is satisfied, this paper establishes an optimal power purchasing portfolio method. In the proposed framework, power purchasing in real-time electricity market, day-ahead electricity market, and mid-long term contract market is transformed into a semi-definite programming problem. The numerical analysis shows the efficiency of the proposed model, which paves a new way for power supply companies to determine the optimal purchasing strategies considering the risk, especially in the new type power system with strong uncertainty dominated by renewable energy.","PeriodicalId":216155,"journal":{"name":"2021 International Conference on Power System Technology (POWERCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Power System Technology (POWERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERCON53785.2021.9697515","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A great uncertainty exists in the operation of power market, but the stable operation of the market is of extreme importantance. Considering the uncertainty of probability distribution of electricity price in multi-energy markets as well as the premise of guaranteeing distributional robust conditional value-at-risk constraint is satisfied, this paper establishes an optimal power purchasing portfolio method. In the proposed framework, power purchasing in real-time electricity market, day-ahead electricity market, and mid-long term contract market is transformed into a semi-definite programming problem. The numerical analysis shows the efficiency of the proposed model, which paves a new way for power supply companies to determine the optimal purchasing strategies considering the risk, especially in the new type power system with strong uncertainty dominated by renewable energy.