Open AccessFault Type Classification of 150 kV Transmission Line using Wavelet Multi-Resolution Analysis Method
Author(s) -
Novizon Novizon,
Nurfi Syahri,
Silvia Wulandari,
Tesya Uldira Septiyeni,
Rahadian Asneli Putri
Publication year - 2021
Publication title -
andalas journal of electrical and electronic engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2777-0079
DOI - 10.25077/ajeeet.v1i2.15
Subject(s) - wavelet , fault (geology) , transmission line , electric power transmission , computer science , resolution (logic) , matlab , transmission (telecommunications) , artificial intelligence , electronic engineering , pattern recognition (psychology) , engineering , telecommunications , electrical engineering , seismology , geology , operating system
To identify the fault, wavelet method is used in solving complex protection problems. This study uses a new approach, namely the wavelet multi resolution analysis method with its application where multi resolution analysis works to analyze signals at different frequencies with the same resolution. In this study, the classification of fault types that occur in the 150 kV transmission line quickly and accurately is carried out using the wavelet multi resolution analysis method. This research is included in applied research and was designed using computer simulation software, namely ATP and MATLAB. The data transmission system used is the Maninjau Hydroelectric Power Plant transmission line to Pauh Limo Substation. The modeled transmission system is given 1-phase to ground, 2-phase to ground, 2- phase, 3-phase and lightning faults. To determine the accuracy of this classification, the fault is varied according to the distance and impedance of the disturbance. From the analysis of the simulation results and calculations, based on the wavelet multi resolution analysis method used in fault classifying, the average value of the approximation coefficient used to classify the type of fault is obtained. Based on the results of the study, it can be said that all types of fault analyzed in this study have met the classification requirements using the wavelet multi resolution analysis method