基于功率信号分析的光伏电站故障诊断方法OA北大核心CSTPCD
Fault Diagnosis Algorithm for PV Power Plant Based on Power Signal Analysis
为提高光伏电站故障诊断精度,提出一种基于功率信号分析的光伏电站故障诊断方法.首先,用卷积神经网络结合长短记忆CNN-LSTM(convolutional neural networks-long short-term memory)模型和岭回归模型对历史发电的时序信息进行充分挖掘,再依据实际与预测发电功率之间的动态时间规整DTW(dynamic time warping)距离进行电站故障检测;其次,提出一个基于实际发电功率频域特征的故障分类指标,…查看全部>>
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 …查看全部>>
郑晏;厉小润;张天文
浙江大学电气工程学院,杭州 310027浙江大学电气工程学院,杭州 310027浙江正泰智维能源服务有限公司,杭州 310052
动力与电气工程
故障检测故障分类光伏电站时序分析频域分析
fault detectionfault classificationPV power planttime series analysisfrequency-domain analysis
《电力系统及其自动化学报》 2024 (5)
150-158,9
浙江省尖兵计划资助项目(2023C01129)
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