{"title":"Risk Stabilization and Market Bidding Strategy of Virtual Power Plant Alliance Based on Multi-stage Robust Optimization","authors":"Yan Liang, Qingqing Zhou, Yushu Pan, Li Liu","doi":"10.1109/ACPEE53904.2022.9783960","DOIUrl":null,"url":null,"abstract":"In view of the challenges of renewable energy output and the uncertainty of electricity prices to the operation of virtual power plants, a multi-stage robust optimization based on the risk-control model of virtual power plant alliances and market bidding strategies are proposed .In view of the wind power output and market price fluctuations under the box-type uncertain set, consider multiple adjustable resources such as electric vehicles and energy storage, establish a single virtual power plant adjustable resource and a multi-stage robust collaborative control model of the wide-area virtual power plant alliance, and enhance The ability to withstand uncertain risks and improve market efficiency. A robust dual dynamic programming algorithm is proposed to solve the proposed model, and an improved lower bound of the hyperplane is proposed to solve the problem that the traditional benders lower bound cannot approximate the saddle value function surface. The simulation results show that the proposed model can provide an important basis for virtual power plant operators’ market participation strategies, and promote the promotion and application of virtual power plants in the future power market.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPEE53904.2022.9783960","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
In view of the challenges of renewable energy output and the uncertainty of electricity prices to the operation of virtual power plants, a multi-stage robust optimization based on the risk-control model of virtual power plant alliances and market bidding strategies are proposed .In view of the wind power output and market price fluctuations under the box-type uncertain set, consider multiple adjustable resources such as electric vehicles and energy storage, establish a single virtual power plant adjustable resource and a multi-stage robust collaborative control model of the wide-area virtual power plant alliance, and enhance The ability to withstand uncertain risks and improve market efficiency. A robust dual dynamic programming algorithm is proposed to solve the proposed model, and an improved lower bound of the hyperplane is proposed to solve the problem that the traditional benders lower bound cannot approximate the saddle value function surface. The simulation results show that the proposed model can provide an important basis for virtual power plant operators’ market participation strategies, and promote the promotion and application of virtual power plants in the future power market.