{"title":"储存还是出售?具有现场存储的风电场收益最大化的阈值价格政策","authors":"Zamiyad Dar, K. Kar, J. Chow","doi":"10.1109/CISS.2016.7460491","DOIUrl":null,"url":null,"abstract":"We consider the problem of maximizing the revenue of a windfarm with on-site storage, and propose and analyze a scheme for a windfarm to store or sell energy based on a threshold price. The threshold price is calculated based on long-term distributions of the electricity price and wind power generation processes, and is chosen so as to balance the energy flows in and out of the storage-equipped windfarm. We apply our method on real time data from a windfarm in New York, along with real time electricity prices from NYISO for the same region and time period. Comparing it with the optimal policy that has knowledge of the future, we observe that the revenue obtained by our threshold policy increases as the storage capacity is increased, and is approximately 90% of the maximum attainable revenue at a storage capacity of 10-15 times the power rating.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Store or sell? A threshold price policy for revenue maximization in windfarms with on-site storage\",\"authors\":\"Zamiyad Dar, K. Kar, J. Chow\",\"doi\":\"10.1109/CISS.2016.7460491\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider the problem of maximizing the revenue of a windfarm with on-site storage, and propose and analyze a scheme for a windfarm to store or sell energy based on a threshold price. The threshold price is calculated based on long-term distributions of the electricity price and wind power generation processes, and is chosen so as to balance the energy flows in and out of the storage-equipped windfarm. We apply our method on real time data from a windfarm in New York, along with real time electricity prices from NYISO for the same region and time period. Comparing it with the optimal policy that has knowledge of the future, we observe that the revenue obtained by our threshold policy increases as the storage capacity is increased, and is approximately 90% of the maximum attainable revenue at a storage capacity of 10-15 times the power rating.\",\"PeriodicalId\":346776,\"journal\":{\"name\":\"2016 Annual Conference on Information Science and Systems (CISS)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Annual Conference on Information Science and Systems (CISS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISS.2016.7460491\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Annual Conference on Information Science and Systems (CISS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISS.2016.7460491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Store or sell? A threshold price policy for revenue maximization in windfarms with on-site storage
We consider the problem of maximizing the revenue of a windfarm with on-site storage, and propose and analyze a scheme for a windfarm to store or sell energy based on a threshold price. The threshold price is calculated based on long-term distributions of the electricity price and wind power generation processes, and is chosen so as to balance the energy flows in and out of the storage-equipped windfarm. We apply our method on real time data from a windfarm in New York, along with real time electricity prices from NYISO for the same region and time period. Comparing it with the optimal policy that has knowledge of the future, we observe that the revenue obtained by our threshold policy increases as the storage capacity is increased, and is approximately 90% of the maximum attainable revenue at a storage capacity of 10-15 times the power rating.