{"title":"基于改进细菌觅食算法的固定头水热调度","authors":"I. Farhat, M. El-Hawary","doi":"10.1109/EPEC.2010.5697200","DOIUrl":null,"url":null,"abstract":"In this paper the short-term hydro-thermal scheduling problem is solved using a modified bacterial foraging algorithm (MBFA). The integrated hydro-thermal systems considered include fixed-head hydro reservoirs. The short-term hydro-thermal scheduling (STHTS) problem is a dynamic large-scale nonlinear optimization problem which requires solving unit commitment and economic power load dispatch problems. The bacterial foraging algorithm (BFA) is a recently developed evolutionary optimization technique based on the foraging behavior of the E. coli bacteria. The BFA has been successfully employed to solve various optimization problems; however, for large-scale problems such as this problem, it shows poor convergence properties. To overcome this problem considering its high-dimension search space, critical modifications are introduced to the basic BFA. The algorithm presented is validated using two fixed-head test systems. Results show that the proposed algorithm is capable of solving the problem with good performance.","PeriodicalId":393869,"journal":{"name":"2010 IEEE Electrical Power & Energy Conference","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Fixed-head hydro-thermal scheduling using a modified bacterial foraging algorithm\",\"authors\":\"I. Farhat, M. El-Hawary\",\"doi\":\"10.1109/EPEC.2010.5697200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper the short-term hydro-thermal scheduling problem is solved using a modified bacterial foraging algorithm (MBFA). The integrated hydro-thermal systems considered include fixed-head hydro reservoirs. The short-term hydro-thermal scheduling (STHTS) problem is a dynamic large-scale nonlinear optimization problem which requires solving unit commitment and economic power load dispatch problems. The bacterial foraging algorithm (BFA) is a recently developed evolutionary optimization technique based on the foraging behavior of the E. coli bacteria. The BFA has been successfully employed to solve various optimization problems; however, for large-scale problems such as this problem, it shows poor convergence properties. To overcome this problem considering its high-dimension search space, critical modifications are introduced to the basic BFA. The algorithm presented is validated using two fixed-head test systems. Results show that the proposed algorithm is capable of solving the problem with good performance.\",\"PeriodicalId\":393869,\"journal\":{\"name\":\"2010 IEEE Electrical Power & Energy Conference\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Electrical Power & Energy Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EPEC.2010.5697200\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Electrical Power & Energy Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEC.2010.5697200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fixed-head hydro-thermal scheduling using a modified bacterial foraging algorithm
In this paper the short-term hydro-thermal scheduling problem is solved using a modified bacterial foraging algorithm (MBFA). The integrated hydro-thermal systems considered include fixed-head hydro reservoirs. The short-term hydro-thermal scheduling (STHTS) problem is a dynamic large-scale nonlinear optimization problem which requires solving unit commitment and economic power load dispatch problems. The bacterial foraging algorithm (BFA) is a recently developed evolutionary optimization technique based on the foraging behavior of the E. coli bacteria. The BFA has been successfully employed to solve various optimization problems; however, for large-scale problems such as this problem, it shows poor convergence properties. To overcome this problem considering its high-dimension search space, critical modifications are introduced to the basic BFA. The algorithm presented is validated using two fixed-head test systems. Results show that the proposed algorithm is capable of solving the problem with good performance.