{"title":"FAULT LOCATION SCHEME IN DISTRIBUTION SYSTEMS WITH DISTRIBUTED GENERATORS USING NEURAL NETWORKS","authors":"Shahgholian Ghazanfar, M. Rezaei","doi":"10.1234/MJEE.V4I2.333","DOIUrl":null,"url":null,"abstract":"Nowadays using DG (distributed generation) in vast variety of cases has been more considerable due to its beneficial advantages, but interconnecting DG to radial distribution systems has some impact on the coordination of protection devices. The main point in the protection scheme is the diagnosis of fault locations, so producing a new method to identify fault location with high accuracy is necessary. This paper presents a novel approach to fault location identification with DG in distributed systems by the means of neural networks. According to this method using a distributed system as intentional islanding in necessary conditions is possible and reduces the ENS (Energy Not Supplied) of the net. Using separate NNs (neural networks) for each island (zone) will increase the accuracy of this method. Implementation results of this scheme on actual distributed systems has been simulated and reported.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"4 1","pages":"57-62"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Majlesi Journal of Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1234/MJEE.V4I2.333","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 1
Abstract
Nowadays using DG (distributed generation) in vast variety of cases has been more considerable due to its beneficial advantages, but interconnecting DG to radial distribution systems has some impact on the coordination of protection devices. The main point in the protection scheme is the diagnosis of fault locations, so producing a new method to identify fault location with high accuracy is necessary. This paper presents a novel approach to fault location identification with DG in distributed systems by the means of neural networks. According to this method using a distributed system as intentional islanding in necessary conditions is possible and reduces the ENS (Energy Not Supplied) of the net. Using separate NNs (neural networks) for each island (zone) will increase the accuracy of this method. Implementation results of this scheme on actual distributed systems has been simulated and reported.
期刊介绍:
The scope of Majlesi Journal of Electrcial Engineering (MJEE) is ranging from mathematical foundation to practical engineering design in all areas of electrical engineering. The editorial board is international and original unpublished papers are welcome from throughout the world. The journal is devoted primarily to research papers, but very high quality survey and tutorial papers are also published. There is no publication charge for the authors.