{"title":"考虑市场交易的机组承诺问题的求解方法","authors":"Hiroto Ishimori, Ryusei Mikami, Tetsuya Sato, Takayuki Shiina","doi":"10.52731/ijskm.v7.i2.721","DOIUrl":null,"url":null,"abstract":"In Japan, the electric power market has been fully deregulated since April 2016, and many Independent Power Producers have entered the market. Companies participating in the market conduct transactions between market participants to maximize their profits. When companies consider maximization of their profit, it is necessary to optimize the operation of generators in consideration of market transactions.However, it is not easy to consider trading in the market because it contains many complex and uncertain factors. The number of participating companies continues to increase, and research on the operation of generators in consideration of market transactions is an important field. The power market comprises various markets such as the day-ahead and adjustment markets, and various transactions are performed between participants. We discuss the day-ahead market trading. In such a market, electricity prices and demands vary greatly depending on the trends in electricity sell and purchase bidding. It is necessary for business operators to set operational schedules that take fluctuations in electricity prices and demand into account. We consider an optimization model of generator operation considering market transactions and apply stochastic programming to solve the problem. In addition, we demonstrate that scheduling based on the stochastic programming method is better than conventional deterministic planning.","PeriodicalId":487422,"journal":{"name":"International journal of service and knowledge management","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Solution methods for unit commitment problem considering market transactions\",\"authors\":\"Hiroto Ishimori, Ryusei Mikami, Tetsuya Sato, Takayuki Shiina\",\"doi\":\"10.52731/ijskm.v7.i2.721\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Japan, the electric power market has been fully deregulated since April 2016, and many Independent Power Producers have entered the market. Companies participating in the market conduct transactions between market participants to maximize their profits. When companies consider maximization of their profit, it is necessary to optimize the operation of generators in consideration of market transactions.However, it is not easy to consider trading in the market because it contains many complex and uncertain factors. The number of participating companies continues to increase, and research on the operation of generators in consideration of market transactions is an important field. The power market comprises various markets such as the day-ahead and adjustment markets, and various transactions are performed between participants. We discuss the day-ahead market trading. In such a market, electricity prices and demands vary greatly depending on the trends in electricity sell and purchase bidding. It is necessary for business operators to set operational schedules that take fluctuations in electricity prices and demand into account. We consider an optimization model of generator operation considering market transactions and apply stochastic programming to solve the problem. In addition, we demonstrate that scheduling based on the stochastic programming method is better than conventional deterministic planning.\",\"PeriodicalId\":487422,\"journal\":{\"name\":\"International journal of service and knowledge management\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of service and knowledge management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52731/ijskm.v7.i2.721\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of service and knowledge management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52731/ijskm.v7.i2.721","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solution methods for unit commitment problem considering market transactions
In Japan, the electric power market has been fully deregulated since April 2016, and many Independent Power Producers have entered the market. Companies participating in the market conduct transactions between market participants to maximize their profits. When companies consider maximization of their profit, it is necessary to optimize the operation of generators in consideration of market transactions.However, it is not easy to consider trading in the market because it contains many complex and uncertain factors. The number of participating companies continues to increase, and research on the operation of generators in consideration of market transactions is an important field. The power market comprises various markets such as the day-ahead and adjustment markets, and various transactions are performed between participants. We discuss the day-ahead market trading. In such a market, electricity prices and demands vary greatly depending on the trends in electricity sell and purchase bidding. It is necessary for business operators to set operational schedules that take fluctuations in electricity prices and demand into account. We consider an optimization model of generator operation considering market transactions and apply stochastic programming to solve the problem. In addition, we demonstrate that scheduling based on the stochastic programming method is better than conventional deterministic planning.