Xiao Xiong, Ge Zaihui, C. Zhiming, Sun Siyang, Meng Wenchuan
{"title":"电现货市场与调控市场下的风热发电机组协调交易模式","authors":"Xiao Xiong, Ge Zaihui, C. Zhiming, Sun Siyang, Meng Wenchuan","doi":"10.1109/ACPEE56931.2023.10135895","DOIUrl":null,"url":null,"abstract":"In the process clean and low-carbon power systems construction, an increasing proportion of wind turbines participate in the power market, but the randomness of its output will bring great market risks. To reduce the risks, wind power, thermal power, pumped storage units, and other regulatory facilities would jointly participate in the power market. How these participants obtain more benefits under coordination has become a research focus. This paper proposes a stochastic optimization model for wind-thermal-pumped storage units cooperatively participate in day-ahead power market and frequency modulation(FM) market. In both markets, these participants are required to declare the next-day generation outputs, bidding prices, and the available generation capacity that can be used for frequency modulation. The model considers the statistical characteristics and correlations of wind power outputs between different periods and proposes a scenario reduction method. In addition, the model also introduces a CVaR risk control method for market electricity price, wind generation output, FM mileage and other uncertainties. In addition, the model also introduces the CVaR risk control method for market electricity price, wind power output, FM mileage and other uncertain factors, and simulates the situation of different participants in the market under different risk appetites. The experimental results show that the stochastic optimal bidding strategy with risk control is effective under uncertain conditions.","PeriodicalId":403002,"journal":{"name":"2023 8th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Coordinated Trading Mode of Wind-Thermal-Pumped Storage Units In Electricity Spot Market and Regulation Market\",\"authors\":\"Xiao Xiong, Ge Zaihui, C. Zhiming, Sun Siyang, Meng Wenchuan\",\"doi\":\"10.1109/ACPEE56931.2023.10135895\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the process clean and low-carbon power systems construction, an increasing proportion of wind turbines participate in the power market, but the randomness of its output will bring great market risks. To reduce the risks, wind power, thermal power, pumped storage units, and other regulatory facilities would jointly participate in the power market. How these participants obtain more benefits under coordination has become a research focus. This paper proposes a stochastic optimization model for wind-thermal-pumped storage units cooperatively participate in day-ahead power market and frequency modulation(FM) market. In both markets, these participants are required to declare the next-day generation outputs, bidding prices, and the available generation capacity that can be used for frequency modulation. The model considers the statistical characteristics and correlations of wind power outputs between different periods and proposes a scenario reduction method. In addition, the model also introduces a CVaR risk control method for market electricity price, wind generation output, FM mileage and other uncertainties. In addition, the model also introduces the CVaR risk control method for market electricity price, wind power output, FM mileage and other uncertain factors, and simulates the situation of different participants in the market under different risk appetites. The experimental results show that the stochastic optimal bidding strategy with risk control is effective under uncertain conditions.\",\"PeriodicalId\":403002,\"journal\":{\"name\":\"2023 8th Asia Conference on Power and Electrical Engineering (ACPEE)\",\"volume\":\"94 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 8th Asia Conference on Power and Electrical Engineering (ACPEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACPEE56931.2023.10135895\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 8th Asia Conference on Power and Electrical Engineering (ACPEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPEE56931.2023.10135895","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Coordinated Trading Mode of Wind-Thermal-Pumped Storage Units In Electricity Spot Market and Regulation Market
In the process clean and low-carbon power systems construction, an increasing proportion of wind turbines participate in the power market, but the randomness of its output will bring great market risks. To reduce the risks, wind power, thermal power, pumped storage units, and other regulatory facilities would jointly participate in the power market. How these participants obtain more benefits under coordination has become a research focus. This paper proposes a stochastic optimization model for wind-thermal-pumped storage units cooperatively participate in day-ahead power market and frequency modulation(FM) market. In both markets, these participants are required to declare the next-day generation outputs, bidding prices, and the available generation capacity that can be used for frequency modulation. The model considers the statistical characteristics and correlations of wind power outputs between different periods and proposes a scenario reduction method. In addition, the model also introduces a CVaR risk control method for market electricity price, wind generation output, FM mileage and other uncertainties. In addition, the model also introduces the CVaR risk control method for market electricity price, wind power output, FM mileage and other uncertain factors, and simulates the situation of different participants in the market under different risk appetites. The experimental results show that the stochastic optimal bidding strategy with risk control is effective under uncertain conditions.