Faulted-phase selection scheme for China 500kV transmission line based on wavelet transforms and artificial intelligence

2012 ◽  
Author(s):  
Jianyi Chen ◽  
Yuping Lu ◽  
R.K. Aggarwal
Keyword(s):  
Artificial Intelligence ◽  
Transmission Line ◽  
Wavelet Transforms ◽  
Phase Selection ◽  
Selection Scheme

scholarly journals Comparison of Artificial Intelligence Methods for Fault Classification of the 115-kV Hybrid Transmission System

2020 ◽  
Vol 10 (11) ◽  
pp. 3967 ◽  
Author(s):  
Jittiphong Klomjit ◽  
Atthapol Ngaopitakkul
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Transmission Line ◽  
Fault Location ◽  
Back Propagation ◽  
Fault Classification ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Mother Wavelet ◽  
Hybrid Transmission

This research proposes a comparison study on different artificial intelligence (AI) methods for classifying faults in hybrid transmission line systems. The 115-kV hybrid transmission line in the Provincial Electricity Authority (PEA-Thailand) system, which is a single circuit single conductor transmission line, is studied. Fault signals in the transmission line were generated by the EMTP/ATPDraw software. Various factors such as fault location, type, and angle were considered. Then, fault signals were analyzed by coefficient details on the first scale of the discrete wavelet transform. Daubechies mother wavelet from MATLAB software was used to decompose the fault signal. The coefficient value of the mother wavelet behaved depending on the position, inception of fault angle, and fault type. AI methods including probabilistic neural networks (PNNs), back-propagation neural networks (BPNNs), and support vector machine (SVM) were used to identify faults. AI input used the maximum first peak coefficients of phase ABC and zero sequence. The results obtained from the study were found to be satisfactory with all AI methodologies having an average accuracy of more than 98% in the case study. However, the SVM technique can provide more accurate results than the PNN and BPNN techniques with less computation burden. Thus, it is suitable for being applied to actual protection systems.

An Integrated Fault Phase Selection Scheme for Double Circuit Lines on the Same Tower

2014 ◽  
Vol 668-669 ◽  
pp. 657-660
Author(s):  
Shu Tian ◽  
Fang Fang Liu
Keyword(s):  
Adaptive Capacity ◽  
Fault Location ◽  
Phase Selection ◽  
Selection Scheme ◽  
Transition Resistance ◽  
Simulation Results

For double circuit lines on the same tower, traditional phase selectors for single lines can not operate correctly in crossing-line faults. To ensure the performance of faults phase selection in the single lines and meanwhile achieve accurate phase selection in crossing-line faults, an integrated fault phase selection scheme based on fault component current is proposed. Firstly, faults are divided into single lines faults, same-name-phase crossing-line faults and non same-name-phase crossing-line faults, then the phase selection is classified. The process with adaptive capacity can automatically select the suitable phase selector not affected by fault types. Simulation results via PSCAD/EMTDC show that the phase selection scheme based on fault component current has good performances for different fault types, fault location and transition resistance.

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