{"title":"供需一体化管理下区间需求下基于需求的投标策略","authors":"Zixu Liu, Xiao-Jun Zeng, Zhihua Yang","doi":"10.1109/CEC.2018.8477941","DOIUrl":null,"url":null,"abstract":"The penetration of renewable resources in the wholesale electricity market and the demand response in the retail market cause the demand and the supply to become more unpredictable. The ISO is hard to efficiently schedule the production and dispatch the demand. Furthermore, strategic bidding in a more competitive environment is an important problem for the generator. Forecasting the hourly market clearing price (MCP) in the day-ahead electricity market is one of essential task for any bidding decision making. But only a single predicted value of MCP cannot offer enough help for the generator to select the optimal bidding strategies. Aiming at challenge these tasks, we design a new wholesale mechanism in which the ISO declares an interval demand to the wholesale market. The interval demand is more robust than a single demand figure and enables the ISO to handle unpredictable demand under the DR programs. We also developed a forecasting model to forecast a MCP function under the interval demand and introduce the notion of confidence interval to the forecasting model. The confidence interval predicts the exact range of hourly MCP. Based on these work, the optimal bidding strategies for the generator under an interval demand is also illustrated.","PeriodicalId":212677,"journal":{"name":"2018 IEEE Congress on Evolutionary Computation (CEC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Demand Based Bidding Strategies Under Interval Demand for Integrated Demand and Supply Management\",\"authors\":\"Zixu Liu, Xiao-Jun Zeng, Zhihua Yang\",\"doi\":\"10.1109/CEC.2018.8477941\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The penetration of renewable resources in the wholesale electricity market and the demand response in the retail market cause the demand and the supply to become more unpredictable. The ISO is hard to efficiently schedule the production and dispatch the demand. Furthermore, strategic bidding in a more competitive environment is an important problem for the generator. Forecasting the hourly market clearing price (MCP) in the day-ahead electricity market is one of essential task for any bidding decision making. But only a single predicted value of MCP cannot offer enough help for the generator to select the optimal bidding strategies. Aiming at challenge these tasks, we design a new wholesale mechanism in which the ISO declares an interval demand to the wholesale market. The interval demand is more robust than a single demand figure and enables the ISO to handle unpredictable demand under the DR programs. We also developed a forecasting model to forecast a MCP function under the interval demand and introduce the notion of confidence interval to the forecasting model. The confidence interval predicts the exact range of hourly MCP. Based on these work, the optimal bidding strategies for the generator under an interval demand is also illustrated.\",\"PeriodicalId\":212677,\"journal\":{\"name\":\"2018 IEEE Congress on Evolutionary Computation (CEC)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Congress on Evolutionary Computation (CEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEC.2018.8477941\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Congress on Evolutionary Computation (CEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2018.8477941","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Demand Based Bidding Strategies Under Interval Demand for Integrated Demand and Supply Management
The penetration of renewable resources in the wholesale electricity market and the demand response in the retail market cause the demand and the supply to become more unpredictable. The ISO is hard to efficiently schedule the production and dispatch the demand. Furthermore, strategic bidding in a more competitive environment is an important problem for the generator. Forecasting the hourly market clearing price (MCP) in the day-ahead electricity market is one of essential task for any bidding decision making. But only a single predicted value of MCP cannot offer enough help for the generator to select the optimal bidding strategies. Aiming at challenge these tasks, we design a new wholesale mechanism in which the ISO declares an interval demand to the wholesale market. The interval demand is more robust than a single demand figure and enables the ISO to handle unpredictable demand under the DR programs. We also developed a forecasting model to forecast a MCP function under the interval demand and introduce the notion of confidence interval to the forecasting model. The confidence interval predicts the exact range of hourly MCP. Based on these work, the optimal bidding strategies for the generator under an interval demand is also illustrated.