精品文档---下载后可任意编辑GIS 特高频局部放电特征量优选及类型识别讨论的开题报告摘要GIS(Gas Insulated Switchgear)在高压输电和配电系统中扮演着重要角色。然而，由于其复杂的结构和高压的工作环境, GIS 常常发生局部放电现象，导致设备故障甚至损坏，影响电网的正常运行。因此, 讨论定量的 GIS 安全运行指标和技术参数，对保障电网稳定运行至关重要，也对 GIS 设备状态监测、诊断和维护提出了更高的要求。 本文提出了一种基于局部放电特征量的优选和类型识别方法，该方法可以对 GIS 进行在线检测和监测，确定其状态和安全性能。首先，通过对 GIS 模型进行数值分析，获得受局部放电影响的电场分布情况。接着，从这些分析结果中提取出几种有代表性的局部放电特征量，包括出现频率、能量大小、放电形态等，并应用统计学和机器学习算法进行特征量的优选和分类。最后，利用识别结果对 GIS 设备做出状态评估和故障诊断，以提高电力系统的安全和可靠性。关键词：GIS、局部放电、特征量、优选、分类、状态评估、故障诊断AbstractGas Insulated Switchgear (GIS) plays an important role in high-voltage transmission and distribution systems. However, due to its complex structure and high voltage working environment, GIS often suffers from partial discharge, which causes equipment failure or damage and affects the normal operation of the power grid. Therefore, it is of great significance to study quantitative safety operation indicators and technical parameters of GIS to ensure the stable operation of the power grid. This research also puts forward higher requirements for GIS equipment condition monitoring, diagnosis, and maintenance.This paper proposes a method based on partial discharge characteristic quantities optimization and type recognition, which can online detect and monitor GIS to determine its state and safety performance. Firstly, the electric field distribution affected by partial discharge is obtained by numerical analysis of GIS model. Then, several representative partial discharge characteristic quantities are extracted from these results, 精品文档---下载后可任意编辑including frequency of occurrence, energy scale, discharge form, etc., and statistical and machine learning algorithms are applied for characteristic quantities optimization and classification. Finally, the application of recognition results to GIS equipment to make state assessment and fault diagnosis has been studied, in order to improve the safety and reliability of the power system.Keywords: GIS, partial discharge, characteristic quantities, optimization, classification, state assessment, fault diagnosis
