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Issue title: Special Section: Intelligent tools and techniques for signals, machines and automation
Guest editors: Smriti Srivastava, Hasmat Malik and Rajneesh Sharma
Article type: Research Article
Authors: Keshri, Jay Prakash; * | Tiwari, Harpal
Affiliations: Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, India
Correspondence: [*] Corresponding author. Jay Prakash Keshri, Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, India. E-mail: [email protected].
Abstract: Due to the recent advancement in power electronics devices in past few decades, HVDC system became mature but still has some protection issues, like tripping of the circuit breaker for a temporary fault as to load changes. Therefore, in this paper, a scheme of complete protection for fast, and accurate classification and detection of a fault in HVDC transmission line using support vector machine (SVM) is presented. In the proposed scheme, ac and dc side voltage and current at each converter station are measured and treated as the input of SVM binary classifier. For classification of fault, SVM module with multi-classification feature is used. For the normalization purposes of the signals, the standard deviation is used over half cycle before and after the occurrence of the fault. Features have been extracted through wavelet transform of predefined function for detection and classification of a fault. The proposed scheme is easy to use as it requires only one end data and a standard deviation over one cycle data.
Keywords: Support vector machines (SVM), hyper plane, multiclass SVM, multiterminal HVDC, regression, confusion matrix, receiver operating characteristic (ROC)
DOI: 10.3233/JIFS-169782
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 5, pp. 4977-4986, 2018
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