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A SVM Based Condition Monitoring of Transmission Line Insulators Using PMU for Smart Grid Environment 被引量:3

A SVM Based Condition Monitoring of Transmission Line Insulators Using PMU for Smart Grid Environment
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摘要 A new methodology for the detection and identification of insulator arc faults for the smart grid environment based on phasor angle measurements is presented in this study and the real time phase angle data are collected using Phasor Measurement Units (PMU). Detection of insulator arcing faults is based on feature extraction and frequency component analysis. The proposed methodology pertains to the identification of various stages of insulator arcing faults in transmission lines network based on leakage current, frequency characteristics and synchronous phasor measurements of voltage. The methodology is evaluated for IEEE 14 standard bus system by modeling the PMU and insulator arc faults using MATLAB/Simulink. The classification of insulator arcs is done using Support Vector Machine (SVM) technique to avoid empirical risk. The proposed methodology using phasor angle measurements employing PMU is used for fault detection/classification of insulator arcing which further helps in efficient protection of the system and its stable operation. In addition, the methodology is suitable for wide area condition monitoring of smart grid rather than end to end transmission lines. A new methodology for the detection and identification of insulator arc faults for the smart grid environment based on phasor angle measurements is presented in this study and the real time phase angle data are collected using Phasor Measurement Units (PMU). Detection of insulator arcing faults is based on feature extraction and frequency component analysis. The proposed methodology pertains to the identification of various stages of insulator arcing faults in transmission lines network based on leakage current, frequency characteristics and synchronous phasor measurements of voltage. The methodology is evaluated for IEEE 14 standard bus system by modeling the PMU and insulator arc faults using MATLAB/Simulink. The classification of insulator arcs is done using Support Vector Machine (SVM) technique to avoid empirical risk. The proposed methodology using phasor angle measurements employing PMU is used for fault detection/classification of insulator arcing which further helps in efficient protection of the system and its stable operation. In addition, the methodology is suitable for wide area condition monitoring of smart grid rather than end to end transmission lines.
作者 Kailasam Saranya Chinnusamy Muniraj Kailasam Saranya;Chinnusamy Muniraj(Electrical and Electronics Engineering, K.S. Rangasamy College of Technology, Thiruchengode, India)
出处 《Journal of Power and Energy Engineering》 2016年第3期47-60,共14页 电力能源(英文)
关键词 Phasor Measurement Units Insulator Arc Feature Extraction Synchronous Phasor Measurements Leakage Current Support Vector Machine Phasor Measurement Units Insulator Arc Feature Extraction Synchronous Phasor Measurements Leakage Current Support Vector Machine
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