{"title":"基于差分演化的常规与非常规成本特征的OPF","authors":"K. Vaisakh, L. Srinivas","doi":"10.1109/ICPST.2008.4745376","DOIUrl":null,"url":null,"abstract":"An efficient evolutionary-based approach, termed as differential evolution (DE), is presented for the solution of optimal power flow (OPF) with the continuous variables. The continuous control variables are unit-active power outputs and generator-bus voltage magnitudes, transformer tap settings and switchable shunt devices. The differential evolution is illustrated for two case studies of IEEE-30 bus system. Both conventional and non-conventional cost characteristics are considered for the optimal power flow solution. The feasibility of the proposed method is compared with a simple evolutionary programming algorithm. The algorithm is computationally faster, in terms of the number of load flows executed, and provides better results than other heuristic techniques.","PeriodicalId":107016,"journal":{"name":"2008 Joint International Conference on Power System Technology and IEEE Power India Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Differential Evolution based OPF with Conventional and Non-Conventional Cost Characteristics\",\"authors\":\"K. Vaisakh, L. Srinivas\",\"doi\":\"10.1109/ICPST.2008.4745376\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An efficient evolutionary-based approach, termed as differential evolution (DE), is presented for the solution of optimal power flow (OPF) with the continuous variables. The continuous control variables are unit-active power outputs and generator-bus voltage magnitudes, transformer tap settings and switchable shunt devices. The differential evolution is illustrated for two case studies of IEEE-30 bus system. Both conventional and non-conventional cost characteristics are considered for the optimal power flow solution. The feasibility of the proposed method is compared with a simple evolutionary programming algorithm. The algorithm is computationally faster, in terms of the number of load flows executed, and provides better results than other heuristic techniques.\",\"PeriodicalId\":107016,\"journal\":{\"name\":\"2008 Joint International Conference on Power System Technology and IEEE Power India Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Joint International Conference on Power System Technology and IEEE Power India Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPST.2008.4745376\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Joint International Conference on Power System Technology and IEEE Power India Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPST.2008.4745376","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Differential Evolution based OPF with Conventional and Non-Conventional Cost Characteristics
An efficient evolutionary-based approach, termed as differential evolution (DE), is presented for the solution of optimal power flow (OPF) with the continuous variables. The continuous control variables are unit-active power outputs and generator-bus voltage magnitudes, transformer tap settings and switchable shunt devices. The differential evolution is illustrated for two case studies of IEEE-30 bus system. Both conventional and non-conventional cost characteristics are considered for the optimal power flow solution. The feasibility of the proposed method is compared with a simple evolutionary programming algorithm. The algorithm is computationally faster, in terms of the number of load flows executed, and provides better results than other heuristic techniques.