{"title":"不平衡磁场条件下原位感应电动机效率的比较","authors":"G. S. Grewal, B. Rajpurohit","doi":"10.1109/ICPACE.2015.7274919","DOIUrl":null,"url":null,"abstract":"There has been a tremendous pressure to assess the in situ efficiency of Induction Machine (IM) with bounded level of intrusion and restricted measurements so as to enhance IMs enforcement. Very few researchers have carried out work to make IM efficiency evaluation methods compatible to unbalanced supply and varying load conditions. This paper recommends a novel approach using cuckoo algorithm to obtain efficiency assessment of an IM operating as a motor working with unbalanced supply having different phase voltages and different currents respectively. The cuckoo algorithm improves the searching ability and has competence to accommodate to complex optimization obstacles. Here, cuckoo algorithm optimizes the IM positive sequence parameters at various loading levels. The parameters optimization is done with the use of positive sequence input currents and electrical powers which have been obtained earlier at various load points of operation. Using the optimized parameters, the evaluation of negative sequence parameters can be made. So, the efficiency of IM can be estimated at different loading levels. Comparison of efficiencies at varying load points with unbalanced power supplies is carried out. The proposed approach is materialized on the MATLAB/SIMULINK platform. The effectiveness, validation and accuracy of the proposed strategy are established by comparing the results obtained with genetic algorithm.","PeriodicalId":6644,"journal":{"name":"2015 International Conference on Power and Advanced Control Engineering (ICPACE)","volume":"519 1","pages":"70-74"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Comparison of efficiencies of in situ induction motor in unbalanced field conditions\",\"authors\":\"G. S. Grewal, B. Rajpurohit\",\"doi\":\"10.1109/ICPACE.2015.7274919\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There has been a tremendous pressure to assess the in situ efficiency of Induction Machine (IM) with bounded level of intrusion and restricted measurements so as to enhance IMs enforcement. Very few researchers have carried out work to make IM efficiency evaluation methods compatible to unbalanced supply and varying load conditions. This paper recommends a novel approach using cuckoo algorithm to obtain efficiency assessment of an IM operating as a motor working with unbalanced supply having different phase voltages and different currents respectively. The cuckoo algorithm improves the searching ability and has competence to accommodate to complex optimization obstacles. Here, cuckoo algorithm optimizes the IM positive sequence parameters at various loading levels. The parameters optimization is done with the use of positive sequence input currents and electrical powers which have been obtained earlier at various load points of operation. Using the optimized parameters, the evaluation of negative sequence parameters can be made. So, the efficiency of IM can be estimated at different loading levels. Comparison of efficiencies at varying load points with unbalanced power supplies is carried out. The proposed approach is materialized on the MATLAB/SIMULINK platform. The effectiveness, validation and accuracy of the proposed strategy are established by comparing the results obtained with genetic algorithm.\",\"PeriodicalId\":6644,\"journal\":{\"name\":\"2015 International Conference on Power and Advanced Control Engineering (ICPACE)\",\"volume\":\"519 1\",\"pages\":\"70-74\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Power and Advanced Control Engineering (ICPACE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPACE.2015.7274919\",\"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 Power and Advanced Control Engineering (ICPACE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPACE.2015.7274919","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of efficiencies of in situ induction motor in unbalanced field conditions
There has been a tremendous pressure to assess the in situ efficiency of Induction Machine (IM) with bounded level of intrusion and restricted measurements so as to enhance IMs enforcement. Very few researchers have carried out work to make IM efficiency evaluation methods compatible to unbalanced supply and varying load conditions. This paper recommends a novel approach using cuckoo algorithm to obtain efficiency assessment of an IM operating as a motor working with unbalanced supply having different phase voltages and different currents respectively. The cuckoo algorithm improves the searching ability and has competence to accommodate to complex optimization obstacles. Here, cuckoo algorithm optimizes the IM positive sequence parameters at various loading levels. The parameters optimization is done with the use of positive sequence input currents and electrical powers which have been obtained earlier at various load points of operation. Using the optimized parameters, the evaluation of negative sequence parameters can be made. So, the efficiency of IM can be estimated at different loading levels. Comparison of efficiencies at varying load points with unbalanced power supplies is carried out. The proposed approach is materialized on the MATLAB/SIMULINK platform. The effectiveness, validation and accuracy of the proposed strategy are established by comparing the results obtained with genetic algorithm.