Comparative evaluation of KBANN networks and ANFIS systems for fault location in electrical power distribution networks
Main Article Content
Current regulation on electrical power quality emphasizes the requirements related to service continuity, thereby increasing the importance of the fault location problem in electrical power distribution networks. The opportune location of faults accelerates the procedure for distribution network supply restoration. This paper presents an evaluative comparison of two approaches to solve the fault location problem. These approaches combine fuzzy logic with artificial neural networks and expert's rules, and use records of the fundamental frecuency components of current and voltage measured at the power substation. Tests carried out in a power distribution network show average errors lower than 5% in fault location, validating the approaches proposed in this work.
- René A. Barrera, Juan J. Mora, Sandra M. Pérez, neural estimator of the rotor angle of synchronous generators from measurement of voltage and current at terminals , Ingeniería y Competitividad: Vol. 11 No. 1 (2009)
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