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基于红外图像识别技术的光伏发电组件热斑效应智能检测系统应用研究

Application of Intelligent Detection System for Thermal Spot Effectof Photovoltaic Modules Based on Infrared Image Recognition Technology

  • 摘要: 新能源光伏场站发电组件是转化电能的主要设备,因外部因素或自身材质损耗在运行中会发生组串连接失效、二极管故障、隐裂、遮挡等影响电站发电效益的缺陷。而这类缺陷的显现方式是以热斑效应出现的,通过红外图像中色温和形状差异对热斑进行分析、处理来区分热斑产生的原因。而利用计算机信息处理技术可以提高光伏组件热斑检测效率,同时更加快速的统计、分类、汇总发电组件热斑效应对发电量影响的结果。这对电站运营中及时发现设备隐患和消除缺陷以及提升发电效益和设备安全稳定运行有着重要意义。

     

    Abstract: The power generation module of the new energy photovoltaic plant is the main equipment for transforming electric energy. Due to external factors or material loss, it will occur in the operation of cluster connection failure, diode failure, hidden cracking, occlusion and other defects that affect the power generation efficiency of the power station. Such defects appear in the form of hot spot effect. The causes of hot spots are distinguished by analyzing and processing the hot spots based on the color and shape differences in infrared images. And the use of computer information processing technology can improve the efficiency of photovoltaic module hot spot detection, and more quickly statistics, classification, summary of the effect of power generation module hot spot effect on the power generation results. It is of great significance to find hidden dangers and eliminate defects of equipment in time and to improve the efficiency of power generation and the safe and stable operation of equipment.

     

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