光伏阵列故障在线诊断技术的研究  

Research on Photovoltaic Array Fault Online Diagnosis Technology

作　　者：邓云[1] Deng Yun(Big Data College,Guangxi Vocational and Technical College,Nanning,China)

机构地区：[1]广西职业技术学院大数据学院,广西南宁

出　　处：《科学技术创新》2025年第2期60-63,共4页Scientific and Technological Innovation

基　　金：广西高校中青年教师科研基础能力提升项目:“基于神经网络的光伏阵列故障在线诊断技术的研究”(项目编号2023KY1025)。

摘　　要：针对光伏阵列裂纹、热斑、开路、短路等故障,人工巡检方式存在检查效率低、准确率不高的问题,本文提出了光伏组件故障在线检测及诊断方法,通过提取光伏组件故障特征参数,建立故障类型与故障原因映射关系网,并反映在神经网络的结构、连接权值和阈值之中,将故障数据录入到经过训练的神经网络模型中,进而实现光伏组件的故障监测及诊断。本文对提高光伏发电运维效率,以及降低运维成本具有十分重要的意义。For photovoltaic array cracks,hot spots,open circuits,short circuits and other faults,manual inspection methods have problems such as low inspection efficiency and low accuracy.This paper proposes an online detection and diagnosis method for photovoltaic module faults.By extracting photovoltaic module fault characteristic parameters,a mapping network of fault types and fault causes is established,which is reflected in the structure,connection weights and thresholds of the neural network,enter the fault data into the trained neural network model to realize fault monitoring and diagnosis of photovoltaic modules.This article is of great significance to improving the operation and maintenance efficiency of photovoltaic power generation and reducing operation and maintenance costs.

关 键 词：光伏阵列 故障诊断 神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TM914.4[自动化与计算机技术—控制科学与工程]