{"title":"使用鲸鱼优化算法的经济和排放联合调度","authors":"C. K. Faseela, H. Vennila","doi":"10.1504/IJENM.2019.10019585","DOIUrl":null,"url":null,"abstract":"This paper highlight the use of latest whale optimisation meta heuristic algorithm for solving economic dispatch problem efficiently. This is used to solve the combined economic and emission dispatch problems for standard three generators system and 30 bus IEEE system. The whale optimisation algorithm was found to provide optimum results with easy convergence in comparison with other algorithms like PSO algorithm. Fuel cost and emission costs are combined to derive better result for economic dispatch. For checking the effectiveness of the algorithm, the results obtained using the same are compared with the results of particle swarm optimisation (PSO) and analysed the same against minimum generation cost and easy convergence. The results are found to be excellent for the systems considered.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Combined economic and emission dispatch using whale optimisation algorithm\",\"authors\":\"C. K. Faseela, H. Vennila\",\"doi\":\"10.1504/IJENM.2019.10019585\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper highlight the use of latest whale optimisation meta heuristic algorithm for solving economic dispatch problem efficiently. This is used to solve the combined economic and emission dispatch problems for standard three generators system and 30 bus IEEE system. The whale optimisation algorithm was found to provide optimum results with easy convergence in comparison with other algorithms like PSO algorithm. Fuel cost and emission costs are combined to derive better result for economic dispatch. For checking the effectiveness of the algorithm, the results obtained using the same are compared with the results of particle swarm optimisation (PSO) and analysed the same against minimum generation cost and easy convergence. The results are found to be excellent for the systems considered.\",\"PeriodicalId\":39284,\"journal\":{\"name\":\"International Journal of Enterprise Network Management\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Enterprise Network Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJENM.2019.10019585\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Business, Management and Accounting\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Enterprise Network Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJENM.2019.10019585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
Combined economic and emission dispatch using whale optimisation algorithm
This paper highlight the use of latest whale optimisation meta heuristic algorithm for solving economic dispatch problem efficiently. This is used to solve the combined economic and emission dispatch problems for standard three generators system and 30 bus IEEE system. The whale optimisation algorithm was found to provide optimum results with easy convergence in comparison with other algorithms like PSO algorithm. Fuel cost and emission costs are combined to derive better result for economic dispatch. For checking the effectiveness of the algorithm, the results obtained using the same are compared with the results of particle swarm optimisation (PSO) and analysed the same against minimum generation cost and easy convergence. The results are found to be excellent for the systems considered.