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Entropy 2018, 20(6), 421; https://doi.org/10.3390/e20060421

Entropy SVM–Based Recognition of Transient Surges in HVDC Transmissions

School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
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Received: 19 April 2018 / Revised: 23 May 2018 / Accepted: 28 May 2018 / Published: 31 May 2018
(This article belongs to the Special Issue Wavelets, Fractals and Information Theory III)
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Abstract

Protection based on transient information is the primary protection of high voltage direct current (HVDC) transmission systems. As a major part of protection function, accurate identification of transient surges is quite crucial to ensure the performance and accuracy of protection algorithms. Recognition of transient surges in an HVDC system faces two challenges: signal distortion and small number of samples. Entropy, which is stable in representing frequency distribution features, and support vector machine (SVM), which is good at dealing with samples with limited numbers, are adopted and combined in this paper to solve the transient recognition problems. Three commonly detected transient surges—single-pole-to-ground fault (GF), lightning fault (LF), and lightning disturbance (LD)—are simulated in various scenarios and recognized with the proposed method. The proposed method is proved to be effective in both feature extraction and type classification and shows great potential in protection applications. View Full-Text
Keywords: HVDC transmission; frequency spectrum entropy; SVM; transient surge recognition HVDC transmission; frequency spectrum entropy; SVM; transient surge recognition
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Luo, G.; Yao, C.; Liu, Y.; Tan, Y.; He, J. Entropy SVM–Based Recognition of Transient Surges in HVDC Transmissions. Entropy 2018, 20, 421.

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