{"title":"应用鲸鱼优化算法确定电网最大负荷极限","authors":"Suvabrata Mukherjee, P. Roy","doi":"10.1109/ICCECE48148.2020.9223071","DOIUrl":null,"url":null,"abstract":"Whale optimization algorithm (WOA), is an uncomplicated and efficient metaheuristic algorithm which provides exceptional execution in case of comprehensive optimization. WOA employs bubble-net hunting approach and it mimics the social nature of humpback whales to get the best candidate solution. In the present article the proposed algorithm has been implied for determining the maximum loadability limit (also commonly referred to as voltage stability) of power network. To assess the robustness and efficient performance in attaining the desired output, the algorithm is implied on MATPOWER 30-bus and IEEE 118-bus test systems. For further evaluation, the results obtained by the implication of WOA has been compared with alternative algorithms such as differential evolution algorithm (DE), multi agent hybrid PSO (MAHPSO) and hybridized DE and PSO (DEPSO). The results, been considered over 20 independent trials, clearly highlights that WOA provides higher efficiency in solving the maximum loadability problem by providing large loading point in much lesser time.","PeriodicalId":129001,"journal":{"name":"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Determination of maximum loadability limit of power networks applying whale optimization algorithm\",\"authors\":\"Suvabrata Mukherjee, P. Roy\",\"doi\":\"10.1109/ICCECE48148.2020.9223071\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Whale optimization algorithm (WOA), is an uncomplicated and efficient metaheuristic algorithm which provides exceptional execution in case of comprehensive optimization. WOA employs bubble-net hunting approach and it mimics the social nature of humpback whales to get the best candidate solution. In the present article the proposed algorithm has been implied for determining the maximum loadability limit (also commonly referred to as voltage stability) of power network. To assess the robustness and efficient performance in attaining the desired output, the algorithm is implied on MATPOWER 30-bus and IEEE 118-bus test systems. For further evaluation, the results obtained by the implication of WOA has been compared with alternative algorithms such as differential evolution algorithm (DE), multi agent hybrid PSO (MAHPSO) and hybridized DE and PSO (DEPSO). The results, been considered over 20 independent trials, clearly highlights that WOA provides higher efficiency in solving the maximum loadability problem by providing large loading point in much lesser time.\",\"PeriodicalId\":129001,\"journal\":{\"name\":\"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCECE48148.2020.9223071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE48148.2020.9223071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Determination of maximum loadability limit of power networks applying whale optimization algorithm
Whale optimization algorithm (WOA), is an uncomplicated and efficient metaheuristic algorithm which provides exceptional execution in case of comprehensive optimization. WOA employs bubble-net hunting approach and it mimics the social nature of humpback whales to get the best candidate solution. In the present article the proposed algorithm has been implied for determining the maximum loadability limit (also commonly referred to as voltage stability) of power network. To assess the robustness and efficient performance in attaining the desired output, the algorithm is implied on MATPOWER 30-bus and IEEE 118-bus test systems. For further evaluation, the results obtained by the implication of WOA has been compared with alternative algorithms such as differential evolution algorithm (DE), multi agent hybrid PSO (MAHPSO) and hybridized DE and PSO (DEPSO). The results, been considered over 20 independent trials, clearly highlights that WOA provides higher efficiency in solving the maximum loadability problem by providing large loading point in much lesser time.