An approach based on neural networks for identification of fault sections in radial distribution systems

Ziolkowski, ValmirDa Silva, Ivan NunesFlauzino, Rogerio Andrade [UNESP]2014-05-272014-05-272006-12-01Proceedings of the IEEE International Conference on Industrial Technology, p. 25-30.http://hdl.handle.net/11449/69237The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.25-30engArtificial intelligenceAutomationClassification (of information)Computer networksElectric fault locationElectric load distributionElectric power systemsElectric power transmissionElectric toolsElectronic data interchangeFeedingAutomatic identificationIndustrial technologiesInternational conferencesNeural networksAn approach based on neural networks for identification of fault sections in radial distribution systemsTrabalho apresentado em evento10.1109/ICIT.2006.372351Acesso aberto2-s2.0-51349143502