Article ID Journal Published Year Pages File Type
399181 International Journal of Electrical Power & Energy Systems 2016 11 Pages PDF
Abstract

•This work presents combined DWT and SVM based directional relaying scheme for double circuit lines.•The proposed scheme offers both primary and backup protection.•This schemes is applicable for inter-circuit faults, and cross-country faults also.•The 3rd level approximate DWT coefficients of three phase current signals only are used.•Proposed method is not affected by variations in fault type, fault location, fault inception angle, fault resistance.

The conventional distance relaying algorithms are unable to detect the inter-circuit faults, cross-country faults, high resistance faults which may occur in a double circuit line. This paper presents combined Discrete Wavelet Transform (DWT) and Support Vector Machine (SVM) based directional relaying and fault classification scheme including inter-circuit faults, cross-country faults and high resistance faults. SVM modules are designed for forward or reverse fault identification and fault classification using single terminal data. The 3rd level approximate discrete wavelet transform coefficients of three phase current signals only have been used. Proposed method is tested with variations in fault type, fault location, fault inception angle, fault resistance, inter-circuit faults, and cross-country faults. The proposed method based on SVM does not need any threshold to operate which is an exceptional attribute for a protective function. As SVMs are not based on comparing with some threshold, rather initially the SVMs are trained with the wide variety of fault patterns which is an offline process and then the trained SVMs are tested online to detect and classify the fault within short time. The test results show that all types of shunt faults can be identified within half cycle time. The proposed scheme offers both primary protection to 95% of the line section and also backup protection to 95% of the adjacent reverse and forward line section also.

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Physical Sciences and Engineering Computer Science Artificial Intelligence
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