Research of GIS partial discharge type evaluation based on convolutional neural network

Liuhuo Wang,Kang Hou,Lingqi Tan

doi:10.1063/5.0011998

Liuhuo Wang, Kang Hou + Show 1 more

Open Access

https://doi.org/10.1063/5.0011998

Copy DOI

Journal: AIP Advances	Publication Date: Aug 1, 2020
Citations: 5	License type: cc-by

Affiliation: China Southern Power Grid (China)

Abstract

This paper presents a GIS (Gas Insulated Switchgear) partial discharge type evaluation based on the convolutional neural network. It is significant to study GIS partial discharge and effectively classify the types of GIS partial discharge. In order to effectively and efficiently distinguish the types of GIS partial discharge, phase resolved partial discharge is researched and evaluated based on the convolutional neural network. First, the hardware of the evaluation system is introduced in detail. Second, the partial discharge signal is analyzed. Third, the partial discharge signal evaluation based on the convolutional neural network is studied. Finally, the experiment of the evaluation is presented to verify that the evaluation system can effectively and accurately perform GIS partial discharge monitoring and improve the reliability of power grid operation.

Highlights

Since GIS (Gas Insulated Switchgear) is widely used in power systems, its safety directly affects the reliability of the entire power grid
The hardware of the evaluation system is introduced in detail
The partial discharge signal evaluation based on the convolutional neural network is studied

Summary

Introduction

Since GIS (Gas Insulated Switchgear) is widely used in power systems, its safety directly affects the reliability of the entire power grid. GIS insulation aging will be further aggravated, and it will seriously threaten the safe operation of the power grid. Partial discharge refers to the partial breakdown of electrical discharge in GIS, and it can occur near the high-voltage conductor or at other locations. Partial discharge often appears in GIS in the early stage of insulation deterioration. There are often multiple defects in the long-term operation process of GIS, and it will generate various forms of partial discharge signals.. It is necessary to distinguish the types of GIS partial discharge faults so that electric power personnel can provide an effective measure for different partial discharge types

Objectives

Results

Conclusion