Surge Arrester Leakage Current Analysis by Using Particle Swarm Optimization Technique

Abstract:

Surge arresters, as protective equipment, are used to limit any overvoltage in a power system resulting from various sources. The surge arrester affects from degradation due to the continuous operating voltage system as well as due to repeated lightning current discharge. Therefore, condition monitoring and health diagnostics of surge arresters are a necessary issue. Hence, as a feasible solution, a condition monitoring based on leakage current measurement techniques was selected to tackle the problem of age diagnostics of surge arresters. The Particle Swarm Search Algorithm was introduced as a method for extracting the third harmonic resistive component, Ir_3rd, from the total leakage current. To employ this method for extracting Ir_3rd, codes were developed in Matlab. The setting of Particle Swarm Search Algorithm was configured for extracting Ir_3rd and accuracy of 94% was obtained.

• Periodical: Applied Mechanics and Materials (Volume 554)
• Pages: 608-612
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.554.608
• Online since: June 2014
• Authors: Vahabi Mashak Saeed, Zulkurnain Abdul-Malek*, Nabipour Afrouzi Hadi, Chin Leong Wooi, Amir Hesam Khavari
• Keywords: Age Diagnostics, Condition Monitoring, Neural Network (NN), Surge Arrester, Thermography Analysis

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