{"title":"双结算电力市场中虚拟竞价和风险管理下的风电和太阳能发电联合发售策略","authors":"Josue Campos do Prado, W. Qiao, Dongliang Xiao","doi":"10.1109/EIT51626.2021.9491892","DOIUrl":null,"url":null,"abstract":"This paper presents a stochastic-optimization-based decision-making model to generate the optional bidding strategies for wind and solar energy facilities with virtual bidding and risk management in two-settlement electricity markets. The proposed model generates day-ahead optimal bidding curves while considering the balancing actions in the real-time market. The uncertainties related to wind and solar power productions and day-ahead and real-time market locational marginal prices are modeled by using a prediction-based scenario generation method. Case studies are performed for an electric utility participating in the Southwest Power Pool electricity market to demonstrate the effectiveness of the proposed model for different risk aversion levels.","PeriodicalId":162816,"journal":{"name":"2021 IEEE International Conference on Electro Information Technology (EIT)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Combined Wind and Solar Power Offering Strategy with Virtual Bidding and Risk Management in Two-Settlement Electricity Markets\",\"authors\":\"Josue Campos do Prado, W. Qiao, Dongliang Xiao\",\"doi\":\"10.1109/EIT51626.2021.9491892\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a stochastic-optimization-based decision-making model to generate the optional bidding strategies for wind and solar energy facilities with virtual bidding and risk management in two-settlement electricity markets. The proposed model generates day-ahead optimal bidding curves while considering the balancing actions in the real-time market. The uncertainties related to wind and solar power productions and day-ahead and real-time market locational marginal prices are modeled by using a prediction-based scenario generation method. Case studies are performed for an electric utility participating in the Southwest Power Pool electricity market to demonstrate the effectiveness of the proposed model for different risk aversion levels.\",\"PeriodicalId\":162816,\"journal\":{\"name\":\"2021 IEEE International Conference on Electro Information Technology (EIT)\",\"volume\":\"114 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Electro Information Technology (EIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIT51626.2021.9491892\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Electro Information Technology (EIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIT51626.2021.9491892","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combined Wind and Solar Power Offering Strategy with Virtual Bidding and Risk Management in Two-Settlement Electricity Markets
This paper presents a stochastic-optimization-based decision-making model to generate the optional bidding strategies for wind and solar energy facilities with virtual bidding and risk management in two-settlement electricity markets. The proposed model generates day-ahead optimal bidding curves while considering the balancing actions in the real-time market. The uncertainties related to wind and solar power productions and day-ahead and real-time market locational marginal prices are modeled by using a prediction-based scenario generation method. Case studies are performed for an electric utility participating in the Southwest Power Pool electricity market to demonstrate the effectiveness of the proposed model for different risk aversion levels.