{"title":"基于模拟退火的ieee33总线径向系统多代分布式优化配置","authors":"K. Dharageshwari, C. Nayanatara","doi":"10.1109/ICCPCT.2015.7159428","DOIUrl":null,"url":null,"abstract":"This paper presents the application of simulated annealing algorithm for the optimal placement of multiple distributed generations in IEEE 33 bus radial distribution system. In this paper multiobjective like power losses, and voltage profile improvement are considered. Expenditure of losses and savings are also estimated. Optimal placements are found using simulated annealing optimization technique. Voltage and Power Losses are calculated using Load flow analysis. Load flow analysis is done in IEEE 33 bus radial distributed network using Forward-Backward sweep method. Using Matlab software the performance of simulated annealing is illustrated. The feasibility of the proposed system is proved with Five Distributed Generations (DGs) which may be the combinations of Solar, Wind, Fuel cell, Geothermal, Biomass, reciprocating engines, and micro turbines. Using multiple DGs the improved results are discussed in this paper.","PeriodicalId":6650,"journal":{"name":"2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015]","volume":"30 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":"{\"title\":\"Multiobjective optimal placement of multiple distributed generations in IEEE 33 bus radial system using simulated annealing\",\"authors\":\"K. Dharageshwari, C. Nayanatara\",\"doi\":\"10.1109/ICCPCT.2015.7159428\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the application of simulated annealing algorithm for the optimal placement of multiple distributed generations in IEEE 33 bus radial distribution system. In this paper multiobjective like power losses, and voltage profile improvement are considered. Expenditure of losses and savings are also estimated. Optimal placements are found using simulated annealing optimization technique. Voltage and Power Losses are calculated using Load flow analysis. Load flow analysis is done in IEEE 33 bus radial distributed network using Forward-Backward sweep method. Using Matlab software the performance of simulated annealing is illustrated. The feasibility of the proposed system is proved with Five Distributed Generations (DGs) which may be the combinations of Solar, Wind, Fuel cell, Geothermal, Biomass, reciprocating engines, and micro turbines. Using multiple DGs the improved results are discussed in this paper.\",\"PeriodicalId\":6650,\"journal\":{\"name\":\"2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015]\",\"volume\":\"30 1\",\"pages\":\"1-7\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"34\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015]\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPCT.2015.7159428\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPCT.2015.7159428","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiobjective optimal placement of multiple distributed generations in IEEE 33 bus radial system using simulated annealing
This paper presents the application of simulated annealing algorithm for the optimal placement of multiple distributed generations in IEEE 33 bus radial distribution system. In this paper multiobjective like power losses, and voltage profile improvement are considered. Expenditure of losses and savings are also estimated. Optimal placements are found using simulated annealing optimization technique. Voltage and Power Losses are calculated using Load flow analysis. Load flow analysis is done in IEEE 33 bus radial distributed network using Forward-Backward sweep method. Using Matlab software the performance of simulated annealing is illustrated. The feasibility of the proposed system is proved with Five Distributed Generations (DGs) which may be the combinations of Solar, Wind, Fuel cell, Geothermal, Biomass, reciprocating engines, and micro turbines. Using multiple DGs the improved results are discussed in this paper.