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 and Kufre M. Udofia
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Nseobong I. Okpura: Department of Electrical/Electronic & Computer Engineering, University of Uyo, Nigeria
E. N. C. Okafor: Department of Elect/Elect Engineering, Federal University of Technology, Owerri, Nigeria
Kufre M. Udofia: Department of Electrical/Electronic & Computer Engineering, University of Uyo, Nigeria

European Journal of Engineering and Technology Research, 2020, vol. 5, issue 8, 966-969

Abstract: 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 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:5:y:2020:i:8:id:61690

DOI: 10.24018/ejeng.2020.5.8.1690

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