Whei-Min Lin, Tung-Sheng Zhan, M. Tsay, Wen-Cha Hung
{"title":"在放松管制的环境下,电力公司的发电扩张计划","authors":"Whei-Min Lin, Tung-Sheng Zhan, M. Tsay, Wen-Cha Hung","doi":"10.1109/DRPT.2004.1338074","DOIUrl":null,"url":null,"abstract":"In this paper, an improved genetic algorithm (IGA) is presented to determine the generation expansion planning of the utility in a deregulated market. The utility has to take both the IPPs' participation and environment impact into account when a new generation is expanded. The CO/sub 2/emission also took into account, while satisfying all electrical constraints simultaneously. IGA was conducted by an improved crossover and mutation mechanism with a competition and autoadjust scheme to avoid prematurity. Tabu lists with heuristic rules were also employed in the searching process to enhance the performance. Testing results shows that IGA can offer an efficient way in determining the generation expansion planning. Results can offer utilities for determining the optimal expansion planning.","PeriodicalId":427228,"journal":{"name":"2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"The generation expansion planning of the utility in a deregulated environment\",\"authors\":\"Whei-Min Lin, Tung-Sheng Zhan, M. Tsay, Wen-Cha Hung\",\"doi\":\"10.1109/DRPT.2004.1338074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an improved genetic algorithm (IGA) is presented to determine the generation expansion planning of the utility in a deregulated market. The utility has to take both the IPPs' participation and environment impact into account when a new generation is expanded. The CO/sub 2/emission also took into account, while satisfying all electrical constraints simultaneously. IGA was conducted by an improved crossover and mutation mechanism with a competition and autoadjust scheme to avoid prematurity. Tabu lists with heuristic rules were also employed in the searching process to enhance the performance. Testing results shows that IGA can offer an efficient way in determining the generation expansion planning. Results can offer utilities for determining the optimal expansion planning.\",\"PeriodicalId\":427228,\"journal\":{\"name\":\"2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DRPT.2004.1338074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DRPT.2004.1338074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The generation expansion planning of the utility in a deregulated environment
In this paper, an improved genetic algorithm (IGA) is presented to determine the generation expansion planning of the utility in a deregulated market. The utility has to take both the IPPs' participation and environment impact into account when a new generation is expanded. The CO/sub 2/emission also took into account, while satisfying all electrical constraints simultaneously. IGA was conducted by an improved crossover and mutation mechanism with a competition and autoadjust scheme to avoid prematurity. Tabu lists with heuristic rules were also employed in the searching process to enhance the performance. Testing results shows that IGA can offer an efficient way in determining the generation expansion planning. Results can offer utilities for determining the optimal expansion planning.