{"title":"基于遗传算法的变压器暂态优化建模","authors":"M. Bigdeli, E. Rahimpour","doi":"10.5923/J.IJEE.20120203.08","DOIUrl":null,"url":null,"abstract":"In this paper a straightforward model is proposed for transient analysis of transformers. The model is capable of representing the impedance or admittance characteristics of the transformer measured from the terminals under different terminal connections up to approximately 200 kHz. The model is simple, so that the simulation with this model is easy and fast. It is feasible to use the model as a two port element by network analysing. To estimation of model parameters genetic algorithm is used. Outset of all, the required measurements are carried out on the 2500 KVA, 6300/420 V transformer. Thereafter, the model parameters are estimated using genetic algorithm toolbox in MATLAB. The comparison between calculated and measured quantities confirms that the accuracy of the proposed method in the middle transient frequency domain is satisfactory. Finally, one of important application of proposed model in transformers fault detection is discussed.","PeriodicalId":14041,"journal":{"name":"International journal of energy engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimized Modeling of Transformer in Transient State with Genetic Algorithm\",\"authors\":\"M. Bigdeli, E. Rahimpour\",\"doi\":\"10.5923/J.IJEE.20120203.08\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a straightforward model is proposed for transient analysis of transformers. The model is capable of representing the impedance or admittance characteristics of the transformer measured from the terminals under different terminal connections up to approximately 200 kHz. The model is simple, so that the simulation with this model is easy and fast. It is feasible to use the model as a two port element by network analysing. To estimation of model parameters genetic algorithm is used. Outset of all, the required measurements are carried out on the 2500 KVA, 6300/420 V transformer. Thereafter, the model parameters are estimated using genetic algorithm toolbox in MATLAB. The comparison between calculated and measured quantities confirms that the accuracy of the proposed method in the middle transient frequency domain is satisfactory. Finally, one of important application of proposed model in transformers fault detection is discussed.\",\"PeriodicalId\":14041,\"journal\":{\"name\":\"International journal of energy engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of energy engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5923/J.IJEE.20120203.08\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of energy engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5923/J.IJEE.20120203.08","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimized Modeling of Transformer in Transient State with Genetic Algorithm
In this paper a straightforward model is proposed for transient analysis of transformers. The model is capable of representing the impedance or admittance characteristics of the transformer measured from the terminals under different terminal connections up to approximately 200 kHz. The model is simple, so that the simulation with this model is easy and fast. It is feasible to use the model as a two port element by network analysing. To estimation of model parameters genetic algorithm is used. Outset of all, the required measurements are carried out on the 2500 KVA, 6300/420 V transformer. Thereafter, the model parameters are estimated using genetic algorithm toolbox in MATLAB. The comparison between calculated and measured quantities confirms that the accuracy of the proposed method in the middle transient frequency domain is satisfactory. Finally, one of important application of proposed model in transformers fault detection is discussed.