智能电网下电力系统故障诊断方法研究

Research on Power System Fault Diagnosis Methods in Smart Grid

摘要

随着智能电网大规模建设，电力系统由原来的高比例常规能源系统向高比例新能源接入、多源信息交互的复杂系统转变，故障发生具有随机性和隐蔽性的特点越来越明显，传统的诊断方法已经不能满足系统安全稳定运行的要求。针对电力系统故障定位精度低、波形识别鲁棒性差、多源信息利用率低等主要问题，创建包含故障特征提取、定位识别、融合诊断、阈值优化的全流程诊断体系，借助理论分析和仿真检验，改善诊断算法的实时性和可靠性，冲破传统方法在复杂工况下应用的瓶颈，给智能电网故障迅速处置和安全守护赋予技术助力。

Abstract

With the large-scale construction of smart grids, power systems have evolved from traditional high-proportion conventional energy systems to complex systems featuring high-proportion new energy integration and multi-source information interaction. The characteristics of randomness and concealment in fault occurrence have become increasingly evident, and traditional diagnostic methods have been unable to meet the requirements for safe and stable system operation. To address the main issues of low fault location accuracy, poor robustness in waveform recognition, and low utilization of multi-source information in power systems, a comprehensive diagnostic system encompassing fault feature extraction, location identification, fusion diagnosis, and threshold optimization has been established. Through theoretical analysis and simulation testing, the real-time performance and reliability of diagnostic algorithms have been improved, breaking through the bottleneck of traditional methods in complex operating conditions and providing technical support for rapid fault handling and safety protection in smart grids.

关键词

智能电网 / 电力系统 / 故障诊断 / 深度学习 / 多源信息融合

Key words

Smart grid / Power system / Fault diagnosis / Deep learning / Multi-source information fusion

参考文献

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