电力系统及其自动化学报2024，Vol.36Issue(5)：150-158,9.DOI:10.19635/j.cnki.csu-epsa.001358
基于功率信号分析的光伏电站故障诊断方法
Fault Diagnosis Algorithm for PV Power Plant Based on Power Signal Analysis
摘要
Abstract
To improve the fault diagnosis accuracy of a PV power plant fault,a fault diagnosis method for PV power plant based on power signal analysis is proposed.First,a convolutional neural networks-long short-term memory(CNN-LSTM)network model and a ridge regression model are used to mine the time series information about the historical power generation data,and the dynamic time warping(DTW)distance between the actual and predicted power genera-tion is selected to detect fault.Second,a fault classification index based on the frequency-domain characteristics of ac-tual power generation is put forward,and the classification rules are built to classify the power plant faults into commu-nication fault,equipment fault and power cut fault,and the fault impact equivalent power generation hours are com-bined to assess the degree of each type of fault.Finally,the analysis of an example verifies the effectiveness of the pro-posed algorithm.关键词
故障检测/故障分类/光伏电站/时序分析/频域分析Key words
fault detection/fault classification/PV power plant/time series analysis/frequency-domain analysis分类
信息技术与安全科学引用本文复制引用
郑晏,厉小润,张天文..基于功率信号分析的光伏电站故障诊断方法[J].电力系统及其自动化学报,2024,36(5):150-158,9.基金项目
浙江省尖兵计划资助项目(2023C01129) （2023C01129）
