摘要
对光伏电站运维中的故障预测与智能运维策略展开研究。首先分析了光伏组件、逆变器及其他关键设备的故障类型及成因,为后续的故障预测提供基础。接着,探讨了大数据分析在光伏电站故障预测中的应用,包括数据采集与预处理技术、故障预测模型构建方法及预测模型的评估与优化策略。在此基础上,设计了智能运维系统的架构与功能,提出了运维决策支持与优化算法,并考虑了系统集成与接口设计。最后,通过实施案例验证了故障预测与智能运维系统的有效性,分析了实施效果,并提出了存在的问题与改进方向。
This paper investigates fault prediction and intelligent operation and maintenance(O&M)strategies for photovoltaic(PV)power stations.It begins by analyzing the types and causes of faults in PV modules,inverters,and other critical equipment,laying the foundation for subsequent fault prediction.Next,it discusses the application of big data analysis in fault prediction for PV power stations,including data collection and preprocessing techniques,methods for constructing fault prediction models,and strategies for evaluating and optimizing these models.Based on this,the architecture and functions of an intelligent O&M system are designed,and decision support and optimization algorithms for O&M are proposed,with consideration given to system integration and interface design.Finally,the effectiveness of the fault prediction and intelligent O&M system is verified through implementation cases,the implementation effects are analyzed,and existing problems and directions for improvement are proposed.
作者
田志杰
唐耀斌
马维琛
王龙
贾雪
TIAN Zhijie;TANG Yaobin;MA Weichen;WANG Long;JIA Xue(Dunhuang Shazhou Energy Development Co.,Ltd.,Dunhuang 736200,China)
出处
《电工技术》
2025年第S1期240-242,245,共4页
Electric Engineering
基金
中小企业创新基金(编号22CX3JF001)。
关键词
光伏电站
故障预测
大数据分析
智能运维
photovoltaic power station
fault prediction
big data analysis
intelligent operation and maintenance
