Fault Detection and Classification in Double-Circuit Transmission Line in the Presence of TCSC Using Hybrid Intelligent Method

Document Type : Original Article

Authors

1 Faculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran

2 Faculty of Electrical and Computer Engineering, Damghan University, Damghan, Iran

Abstract

This paper proposes an effective method for fault detection and classification in a double-circuit transmission line compensated with TCSC. The mutual coupling of parallel transmission lines as well as the presence of TCSC affects the frequency content of the input signal of a distance relay; hence, challenges are posed to fault detection and fault classification. One of the most effective methods for fault detection and classification in a compensated line is the pattern-recognition method. Prerequisites for the optimal using of these methods are the extraction and the selection of appropriate features to feed the classifier. In this paper, wavelet transform, as a signal processing tool to extract features, is used.  Due to a variety of mother wavelets, firstly db1, as the best mother wavelet, is identified by using a new method, and the feature vector is made by the coefficients obtained from the best mother wavelet. After this stage, decision tree, supporting vector machines, and k-nearest neighbor, as the classifiers, are trained by feeding the feature vector. Then, their accuracy is evaluated against different simulation scenarios in order to select the best classifier with the best performance. In this paper, the sample system and the proposed method are implemented in MATLAB environment.

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References

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Energy Engineering and Management
Volume 13, Issue 1
March 2023
Pages 54-63

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