Klasifikasi Dan Estimasi Lokasi Gangguan Pada Saluran Transmisi Tenaga Listrik 150 Kv Menggunakan Metode Hibrid

Sandy Ahmad, Azriyenni Azhari Zakri


This research proposes a hybrid method for classifying and estimating the location of short circuit faults in the electrical power transmission line. The hybrid method used Discrete Wavelet Transform (DWT) and Adaptive Neuro Fuzzy Inference System (ANFIS). The transmission system of bus Koto Panjang (KP) to bus Garuda Sakti (GS) in Riau province with a length of 64km were used in this research. DWT was utilized to process information from each phase voltage and current transient signals as well as the zero sequence current for one cycle after the fault begins. The ANFIS classification was designed to detect any fault in each phase and ground in determining the type of short circuit fault. ANFIS estimation was used to measure the fault location that occurs in the transmission line. The training and testing data were generated by simulating type of short circuit fault in Matlab/Simulink with variations in the fault location and fault resistance. The results obtained are classification of fault with an accuracy of 100% and the estimation of fault location with the lowest error is 0.000605% and the highest error is 0.029827%.
Keywords: ANFIS, DWT, fault classification, fault estimation, short circuit.

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