Ouafa Herbadji, Ketfi Nadhir, L. Slimani, T. Bouktir
{"title":"采用萤火虫算法控制最优功率流","authors":"Ouafa Herbadji, Ketfi Nadhir, L. Slimani, T. Bouktir","doi":"10.1109/ICMSAO.2013.6552559","DOIUrl":null,"url":null,"abstract":"This paper presents the use of a meta-heuristic nature-inspired algorithm, called firefly algorithm for the solution of the optimal power flow problem. The objective is to minimize the total fuel cost of generation and environmental pollution caused by fossil based thermal generating units and also maintain an acceptable system performance in terms of limits on generator real and reactive power outputs, bus voltages, shunt capacitors/reactors and power flow of transmission lines. In this work the standard IEEE 30-bus test system with six generating units has been used to test the effectiveness of the proposed method. Satisfactory results obtained from the proposed method were compared to those obtained by genetic algorithm (GA) and particle Swarm methods (PSO).","PeriodicalId":339666,"journal":{"name":"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Optimal power flow with emission controlled using firefly algorithm\",\"authors\":\"Ouafa Herbadji, Ketfi Nadhir, L. Slimani, T. Bouktir\",\"doi\":\"10.1109/ICMSAO.2013.6552559\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the use of a meta-heuristic nature-inspired algorithm, called firefly algorithm for the solution of the optimal power flow problem. The objective is to minimize the total fuel cost of generation and environmental pollution caused by fossil based thermal generating units and also maintain an acceptable system performance in terms of limits on generator real and reactive power outputs, bus voltages, shunt capacitors/reactors and power flow of transmission lines. In this work the standard IEEE 30-bus test system with six generating units has been used to test the effectiveness of the proposed method. Satisfactory results obtained from the proposed method were compared to those obtained by genetic algorithm (GA) and particle Swarm methods (PSO).\",\"PeriodicalId\":339666,\"journal\":{\"name\":\"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)\",\"volume\":\"95 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMSAO.2013.6552559\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMSAO.2013.6552559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal power flow with emission controlled using firefly algorithm
This paper presents the use of a meta-heuristic nature-inspired algorithm, called firefly algorithm for the solution of the optimal power flow problem. The objective is to minimize the total fuel cost of generation and environmental pollution caused by fossil based thermal generating units and also maintain an acceptable system performance in terms of limits on generator real and reactive power outputs, bus voltages, shunt capacitors/reactors and power flow of transmission lines. In this work the standard IEEE 30-bus test system with six generating units has been used to test the effectiveness of the proposed method. Satisfactory results obtained from the proposed method were compared to those obtained by genetic algorithm (GA) and particle Swarm methods (PSO).