Comparative Analysis of Fuzzy Inference System (FIS) And Adaptive Neuro-Fuzzy Inference System (ANFIS) Methods in the Classification and Location of High Impedance Faults on Distribution System


  •   Nseobong I. Okpura

  •   E. N. C. Okafor

  •   Kufre M. Udofia


Unlike low impedance faults, which involve relatively large magnitude of fault currents and are easily detected by conventional over-current protection devices, high impedance faults pose a serious challenge to protection engineers because they can remain on the system without the protective relays being able to detect them. This paper presents an improved method for detection and location of high impedance fault using ANFIS model. The study was conducted on the 33 kV Uyo-Ikot Ekpene power distribution line. The case study power distribution system was modeled using MATLAB software. HIFs were introduced at various locations along the distribution line. The data obtained from the MATLAB/Simulink simulated fault using discrete wavelet transform (DWT) were used to train the ANFIS for the location of HIF points along the distribution system as well as for prediction of the distance of the fault location to the nearest injection substation. The results show that ANFIS model gives 52.5 percentage reduction in error compared with FIS in the location of fault points on the case study power distribution system.

Keywords: Classification, High Impedance Faults, Distribution System, 33 kV Line


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How to Cite
Okpura, N., Okafor, E. and Udofia, K. 2020. Comparative Analysis of Fuzzy Inference System (FIS) And Adaptive Neuro-Fuzzy Inference System (ANFIS) Methods in the Classification and Location of High Impedance Faults on Distribution System. European Journal of Engineering and Technology Research. 5, 8 (Aug. 2020), 966-969. DOI: