基于支持向量机算法的钙钛矿光伏组件监测系统研究  

Research on perovskite photovoltaic module monitoring system based on support vector machine algorithm

作　　者：刘尧 LIU Yao(East China Electric Power Experimental Research Institute,China Datang Group Science and Technology Research Institute Co.,Ltd.,Hefei 230088,China)

机构地区：[1]中国大唐集团科学技术研究总院有限公司华东电力试验研究院,安徽合肥230088

出　　处：《中国高新科技》2025年第3期68-70,共3页

摘　　要：文章开发了一种基于支持向量机算法的钙钛矿光伏组件监测系统,旨在通过实时数据采集与性能分析,实现光伏电站的故障识别与效率优化。该系统集成了数据采集、故障诊断和性能评估模块,利用支持向量机算法构建数据模型,针对光伏逆变器及组件的性能参数进行精准监控与分析。实验结果表明,所提出的监测系统有效提高了钙钛矿光伏组件的工作效率与运行稳定性,为光伏电站的智能化运维提供了技术支持。This paper develops a monitoring system for perovskite photovoltaic modules based on support vector machine algorithm,aiming to achieve fault identification and efficiency optimization of photovoltaic power plants through real-time data acquisition and performance analysis.The system integrates data acquisition,fault diagnosis,and performance evaluation modules,and uses support vector machine algorithm to construct a data model for precise monitoring and analysis of performance parameters of photovoltaic inverters and components.The experimental results show that the proposed monitoring system effectively improves the working efficiency and operational stability of perovskite photovoltaic modules,providing technical support for the intelligent operation and maintenance of photovoltaic power plants.

关 键 词：支持向量机 钙钛矿光伏组件 故障诊断 

分 类 号：TM615[电气工程—电力系统及自动化]