{"title":"利用蚁狮优化器优化分布式能源分配,减少电力损耗","authors":"Hany S. E. Mansour, A. Abdelsalam, A. Sallam","doi":"10.1109/SEGE.2017.8052823","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel optimization algorithm called ant-lion optimizer (ALO) for optimal distributed energy resources (DERs) allocation in various radial distribution networks. The objective function is to maximize the percentage of power losses reduction. The proposed algorithm is executed on IEEE 34 and 118-bus radial distribution networks with different number of installed DERs. The simulation results using Matlab programming environment show that the effectiveness of the proposed methodology to minimize the losses and to enhance the system voltage profile. A comparison between the results of proposed ALO and those of other optimization methods such as cuckoo search, grid search, oppositional gravitational search, simulated annealing, quasi-oppositional teaching learning based optimization, and chaotic symbiotic organisms search is introduced to verify the superiority of ALO.","PeriodicalId":404327,"journal":{"name":"2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Optimal distributed energy resources allocation using ant-lion optimizer for power losses reduction\",\"authors\":\"Hany S. E. Mansour, A. Abdelsalam, A. Sallam\",\"doi\":\"10.1109/SEGE.2017.8052823\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel optimization algorithm called ant-lion optimizer (ALO) for optimal distributed energy resources (DERs) allocation in various radial distribution networks. The objective function is to maximize the percentage of power losses reduction. The proposed algorithm is executed on IEEE 34 and 118-bus radial distribution networks with different number of installed DERs. The simulation results using Matlab programming environment show that the effectiveness of the proposed methodology to minimize the losses and to enhance the system voltage profile. A comparison between the results of proposed ALO and those of other optimization methods such as cuckoo search, grid search, oppositional gravitational search, simulated annealing, quasi-oppositional teaching learning based optimization, and chaotic symbiotic organisms search is introduced to verify the superiority of ALO.\",\"PeriodicalId\":404327,\"journal\":{\"name\":\"2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SEGE.2017.8052823\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEGE.2017.8052823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal distributed energy resources allocation using ant-lion optimizer for power losses reduction
This paper proposes a novel optimization algorithm called ant-lion optimizer (ALO) for optimal distributed energy resources (DERs) allocation in various radial distribution networks. The objective function is to maximize the percentage of power losses reduction. The proposed algorithm is executed on IEEE 34 and 118-bus radial distribution networks with different number of installed DERs. The simulation results using Matlab programming environment show that the effectiveness of the proposed methodology to minimize the losses and to enhance the system voltage profile. A comparison between the results of proposed ALO and those of other optimization methods such as cuckoo search, grid search, oppositional gravitational search, simulated annealing, quasi-oppositional teaching learning based optimization, and chaotic symbiotic organisms search is introduced to verify the superiority of ALO.