NDLI: Protection scheme for power transmission lines based on SVM and ANN considering the presence of non-linear loads

Content Provider	IET Digital Library
Author	Koley, Ebha Shukla, Sunil K. Ghosh, Subhojit Mohanta, Dusmanta K.
Abstract	The proliferation of non-linear loads in recent times has a strong bearing on power quality due to the presence of harmonics in the power system. Harmonics lead to erroneous measurement and malfunctioning of protective relays, thus reducing the efficacy of transmission line protection. With the aim of improving the dependability of the protection scheme under varying non-linear loading condition, the study presents a hybrid support vector machine (SVM), artificial neural network (ANN) and Kalman filter based algorithm using voltage harmonics for the protection of three-phase transmission line. The post-fault voltage signals are processed by a Kalman filter to estimate the harmonic components, which serve as feature vectors for performing the fault detection and classification by SVM and zone identification as well as the location by ANN. The harmonic information discriminates faults from disturbances based on variations in the fundamental component, to improve the selectivity and accuracy. Considering the stochastic nature of fault occurrence in power systems, the efficacy of the proposed scheme is validated using Monte Carlo simulation. The experimental results confirm the superiority of using voltage harmonics for improving the dependability of transmission line protection.
Starting Page	2333
Ending Page	2341
Page Count	9
ISSN	17518687
Volume Number	11
e-ISSN	17518695
Issue Number	Issue 9, Jun (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/11/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2016.1802
Journal	IET Generation, Transmission & Distribution
Publisher Date	2017-04-25
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	ANN Artificial Neural Network Fault Classification Fault Detection Fault Diagnosis Hybrid Support Vector Machine Kalman Filter Kalman Filter Based Algorithm Knowledge Engineering Technique Monte Carlo Method Monte Carlo Simulation Neural Computing Technique Neural Nets Nonlinear Load Post-fault Voltage Signal Power Engineering Computing Power Quality Power System Power System Protection Power Transmission Cables Power Transmission Line Power Transmission Protection Power Transmission, Distribution And Supply Protection Scheme Protective Relay Support Vector Machine SVM Three-phase Transmission Line Transmission Line Protection Voltage Harmonics
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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