{"title":"考虑传输损耗降低的差分进化算法在统一潮流控制器中的最优定位","authors":"G. I. Rashed, Yuanzhan Sun, K. Rashed, H. Shaheen","doi":"10.1109/POWERCON.2012.6401297","DOIUrl":null,"url":null,"abstract":"This paper presents a Differential Evolutionary (DE) algorithm for finding the optimal location and the best parameter setting of Unified Power Flow Controller (UPFC) for minimizing the active and reactive power losses in the power system. UPFC is one of the most important Flexible Alternating Current Transmission Systems (FACTS) devices that can simultaneously control the voltage magnitude at the sending end and the active and reactive power flows at the receiving end bus. By re-dispatching the power flows in power systems, the minimization of power losses can be obtained through optimal allocation of UPFC. However, the cost of installing UPFC in the power system is too high. Therefore the objective function developed in this paper in such a way to find a compromise solution to this problem. Simulations have been implemented in MATLAB and the IEEE 14-bus and IEEE 30-bus systems have been used as a case study. Also for the purpose of comparison the proposed technique was compared with another optimization technique namely Particle Swarm Optimization (PSO). The results we have obtained indicate that DE is an easy to use, robust, and powerful optimization technique compared with particle swarm optimization (PSO). Installing UPFC in the optimal location determined by DE can significantly minimize the active and reactive power loss in the network.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Optimal location of unified power flow controller by differential evolution algorithm considering transmission loss reduction\",\"authors\":\"G. I. Rashed, Yuanzhan Sun, K. Rashed, H. Shaheen\",\"doi\":\"10.1109/POWERCON.2012.6401297\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a Differential Evolutionary (DE) algorithm for finding the optimal location and the best parameter setting of Unified Power Flow Controller (UPFC) for minimizing the active and reactive power losses in the power system. UPFC is one of the most important Flexible Alternating Current Transmission Systems (FACTS) devices that can simultaneously control the voltage magnitude at the sending end and the active and reactive power flows at the receiving end bus. By re-dispatching the power flows in power systems, the minimization of power losses can be obtained through optimal allocation of UPFC. However, the cost of installing UPFC in the power system is too high. Therefore the objective function developed in this paper in such a way to find a compromise solution to this problem. Simulations have been implemented in MATLAB and the IEEE 14-bus and IEEE 30-bus systems have been used as a case study. Also for the purpose of comparison the proposed technique was compared with another optimization technique namely Particle Swarm Optimization (PSO). The results we have obtained indicate that DE is an easy to use, robust, and powerful optimization technique compared with particle swarm optimization (PSO). Installing UPFC in the optimal location determined by DE can significantly minimize the active and reactive power loss in the network.\",\"PeriodicalId\":176214,\"journal\":{\"name\":\"2012 IEEE International Conference on Power System Technology (POWERCON)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Power System Technology (POWERCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/POWERCON.2012.6401297\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Power System Technology (POWERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERCON.2012.6401297","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal location of unified power flow controller by differential evolution algorithm considering transmission loss reduction
This paper presents a Differential Evolutionary (DE) algorithm for finding the optimal location and the best parameter setting of Unified Power Flow Controller (UPFC) for minimizing the active and reactive power losses in the power system. UPFC is one of the most important Flexible Alternating Current Transmission Systems (FACTS) devices that can simultaneously control the voltage magnitude at the sending end and the active and reactive power flows at the receiving end bus. By re-dispatching the power flows in power systems, the minimization of power losses can be obtained through optimal allocation of UPFC. However, the cost of installing UPFC in the power system is too high. Therefore the objective function developed in this paper in such a way to find a compromise solution to this problem. Simulations have been implemented in MATLAB and the IEEE 14-bus and IEEE 30-bus systems have been used as a case study. Also for the purpose of comparison the proposed technique was compared with another optimization technique namely Particle Swarm Optimization (PSO). The results we have obtained indicate that DE is an easy to use, robust, and powerful optimization technique compared with particle swarm optimization (PSO). Installing UPFC in the optimal location determined by DE can significantly minimize the active and reactive power loss in the network.