M. Bakhshipour, E. Rokrok, F. Namdari, M. Sedaghat
{"title":"利用群机器人搜索和救援算法优化DG和电容器分配及网络重构","authors":"M. Bakhshipour, E. Rokrok, F. Namdari, M. Sedaghat","doi":"10.1109/KBEI.2019.8734909","DOIUrl":null,"url":null,"abstract":"In this paper, a multi objective optimization method based on the swarm robotics search and rescue (SRSR) algorithm is provided to simultaneously determination of optimal capacity and location of DG units and capacitor banks along with network reconfiguration in the distribution system. Also the load uncertainty is considered in the proposed investigation based on triangular fuzzy method. The objective function considers six performance indexes including active losses, reactive losses, voltage deviation, voltage stability index, section loadability and index of balancing current of sections. Each of these indicators is weighed based on their importance and their composition forms in the objective function of the optimization problem. The proposed method has been studied and evaluated on IEEE 33 bus system, also the convergence and efficiency of the proposed SRSR approach is compared with two well-known genetic (GA) and cuckoo search (CS) algorithms. The obtained simulation results indicate the capability of the presented SRSR algorithm in determining the optimal capacity and location of the DG sources and capacitor banks in different operating conditions, and illuminate the improvement of system performance indexes, especially the reduction of active losses in the network.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimal DG and capacitor allocation along with network reconfiguration using Swarm robotics search & rescue algorithm\",\"authors\":\"M. Bakhshipour, E. Rokrok, F. Namdari, M. Sedaghat\",\"doi\":\"10.1109/KBEI.2019.8734909\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a multi objective optimization method based on the swarm robotics search and rescue (SRSR) algorithm is provided to simultaneously determination of optimal capacity and location of DG units and capacitor banks along with network reconfiguration in the distribution system. Also the load uncertainty is considered in the proposed investigation based on triangular fuzzy method. The objective function considers six performance indexes including active losses, reactive losses, voltage deviation, voltage stability index, section loadability and index of balancing current of sections. Each of these indicators is weighed based on their importance and their composition forms in the objective function of the optimization problem. The proposed method has been studied and evaluated on IEEE 33 bus system, also the convergence and efficiency of the proposed SRSR approach is compared with two well-known genetic (GA) and cuckoo search (CS) algorithms. The obtained simulation results indicate the capability of the presented SRSR algorithm in determining the optimal capacity and location of the DG sources and capacitor banks in different operating conditions, and illuminate the improvement of system performance indexes, especially the reduction of active losses in the network.\",\"PeriodicalId\":339990,\"journal\":{\"name\":\"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KBEI.2019.8734909\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KBEI.2019.8734909","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal DG and capacitor allocation along with network reconfiguration using Swarm robotics search & rescue algorithm
In this paper, a multi objective optimization method based on the swarm robotics search and rescue (SRSR) algorithm is provided to simultaneously determination of optimal capacity and location of DG units and capacitor banks along with network reconfiguration in the distribution system. Also the load uncertainty is considered in the proposed investigation based on triangular fuzzy method. The objective function considers six performance indexes including active losses, reactive losses, voltage deviation, voltage stability index, section loadability and index of balancing current of sections. Each of these indicators is weighed based on their importance and their composition forms in the objective function of the optimization problem. The proposed method has been studied and evaluated on IEEE 33 bus system, also the convergence and efficiency of the proposed SRSR approach is compared with two well-known genetic (GA) and cuckoo search (CS) algorithms. The obtained simulation results indicate the capability of the presented SRSR algorithm in determining the optimal capacity and location of the DG sources and capacitor banks in different operating conditions, and illuminate the improvement of system performance indexes, especially the reduction of active losses in the network.