Analysis of high voltage shunt capacitor bank over-voltage breakdown detection

  • Mohsen Rajabali Pour Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100, Kuala Lumpur, Malaysia
  • Mohammad Azimian Engineering Department, Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Jln Sultan Yahya Petra, 54100, Kuala Lumpur, Malaysia
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Abstract

The traditional over-voltage breakdown detection method ignores the suppression of the inrush current of over-voltage breakdown, resulting in low over-voltage signal detection accuracy and a large detection deviation. As a result, a method is proposed for detecting and analyzing the ageing over-voltage breakdown of high voltage shunt capacitor banks. The breakdown model of aged components of the container group is built to determine the breakdown time of the container's overvoltage. Based on this, the annual load of the capacitor bank's aged component material is evaluated, and data on over-voltage breakdown strength is collected. The Mallet algorithm is used to decompose and convert strength data into electrical signals. The high voltage shunt capacitor's over-voltage breakdown inrush current suppressor is built by combining the second-order under damping circuit and the voltage divider. Based on this, the parameters of HV shunt capacitor overvoltage breakdown are obtained, and the detection of HV shunt capacitor overvoltage breakdown of aged HV shunt capacitor banks is completed. The simulation results show that the proposed detection method's over-voltage breakdown output is in perfect agreement with the monitoring device's actual output and has ideal application performance.

Keywords
Shunt capacitor banks Component aging over-voltage breakdown, Detection method Mallet algorithm
How to Cite
Rajabali Pour, Mohsen, and Mohammad Azimian. 2022. “Analysis of High Voltage Shunt Capacitor Bank over-Voltage Breakdown Detection”. Future Energy 1 (1):16-23. https://fupubco.com/fuen/article/view/15.
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