{"title":"基于孤立电力系统风力发电和抽水蓄能水电站考虑的经济调度规划","authors":"Ming-Tse Kuo, Shiue‐Der Lu, Ming-Chang Tsou","doi":"10.1109/ICPS.2015.7266405","DOIUrl":null,"url":null,"abstract":"Taiwan possesses rich wind power. In addition, by using mature hydroelectric power generation technology, system costs and thermal power generation unit loads can be reduced. Regarding simulating wind velocity for wind power generation, this study forecast wind velocity based on the Weibull distribution. According to wind power generation data, predicted wind velocity was converted into the amount of generated electricity. Because of the unpredictability of wind power generation, dispatch cannot be instantly performed. Therefore, pumped storage hydroelectric power generation was used to supplement wind power generation during off-peak periods by storing wind energy in the form of potential energy; thus, hydroelectric power generation supplemented thermal power generation during peak periods. Regarding thermal power generation, this study used the priority list method to calculate unit commitments and used the particle swarm optimization method to calculate economic dispatch. This study performed simulations by using thermal power generation unit, wind power generation unit, and hydraulic power data. The simulation results were compared with the results obtained from existing algorithms. The results showed that the algorithms used in this study yielded accurate results in a short time and reduced the loads of thermal power generation units in a Taiwan Power Company case.","PeriodicalId":107232,"journal":{"name":"2015 IEEE/IAS 51st Industrial & Commercial Power Systems Technical Conference (I&CPS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Economic dispatch planning based on considerations of wind power generation and pumped storage hydroelectric plants for isolated power systems\",\"authors\":\"Ming-Tse Kuo, Shiue‐Der Lu, Ming-Chang Tsou\",\"doi\":\"10.1109/ICPS.2015.7266405\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Taiwan possesses rich wind power. In addition, by using mature hydroelectric power generation technology, system costs and thermal power generation unit loads can be reduced. Regarding simulating wind velocity for wind power generation, this study forecast wind velocity based on the Weibull distribution. According to wind power generation data, predicted wind velocity was converted into the amount of generated electricity. Because of the unpredictability of wind power generation, dispatch cannot be instantly performed. Therefore, pumped storage hydroelectric power generation was used to supplement wind power generation during off-peak periods by storing wind energy in the form of potential energy; thus, hydroelectric power generation supplemented thermal power generation during peak periods. Regarding thermal power generation, this study used the priority list method to calculate unit commitments and used the particle swarm optimization method to calculate economic dispatch. This study performed simulations by using thermal power generation unit, wind power generation unit, and hydraulic power data. The simulation results were compared with the results obtained from existing algorithms. The results showed that the algorithms used in this study yielded accurate results in a short time and reduced the loads of thermal power generation units in a Taiwan Power Company case.\",\"PeriodicalId\":107232,\"journal\":{\"name\":\"2015 IEEE/IAS 51st Industrial & Commercial Power Systems Technical Conference (I&CPS)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE/IAS 51st Industrial & Commercial Power Systems Technical Conference (I&CPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPS.2015.7266405\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE/IAS 51st Industrial & Commercial Power Systems Technical Conference (I&CPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPS.2015.7266405","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Economic dispatch planning based on considerations of wind power generation and pumped storage hydroelectric plants for isolated power systems
Taiwan possesses rich wind power. In addition, by using mature hydroelectric power generation technology, system costs and thermal power generation unit loads can be reduced. Regarding simulating wind velocity for wind power generation, this study forecast wind velocity based on the Weibull distribution. According to wind power generation data, predicted wind velocity was converted into the amount of generated electricity. Because of the unpredictability of wind power generation, dispatch cannot be instantly performed. Therefore, pumped storage hydroelectric power generation was used to supplement wind power generation during off-peak periods by storing wind energy in the form of potential energy; thus, hydroelectric power generation supplemented thermal power generation during peak periods. Regarding thermal power generation, this study used the priority list method to calculate unit commitments and used the particle swarm optimization method to calculate economic dispatch. This study performed simulations by using thermal power generation unit, wind power generation unit, and hydraulic power data. The simulation results were compared with the results obtained from existing algorithms. The results showed that the algorithms used in this study yielded accurate results in a short time and reduced the loads of thermal power generation units in a Taiwan Power Company case.