梁健锋, 胡振球, 黄灿, 许长盛, 曾飞, 黄浩锋. 基于红外热成像检测的光伏电站异常分析[J]. 太阳能, 2024, (1): 70-76. DOI: 10.19911/j.1003-0417.tyn20221022.01
引用本文: 梁健锋, 胡振球, 黄灿, 许长盛, 曾飞, 黄浩锋. 基于红外热成像检测的光伏电站异常分析[J]. 太阳能, 2024, (1): 70-76. DOI: 10.19911/j.1003-0417.tyn20221022.01
Liang Jianfeng, Hu Zhenqiu, Huang Can, Xu Changsheng, Zeng Fei, Huang Haofeng. ANALYSIS OF PV POWER STATIONS ANOMALY BASED ON INFRARED THERMAL IMAGING DETECTION[J]. Solar Energy, 2024, (1): 70-76. DOI: 10.19911/j.1003-0417.tyn20221022.01
Citation: Liang Jianfeng, Hu Zhenqiu, Huang Can, Xu Changsheng, Zeng Fei, Huang Haofeng. ANALYSIS OF PV POWER STATIONS ANOMALY BASED ON INFRARED THERMAL IMAGING DETECTION[J]. Solar Energy, 2024, (1): 70-76. DOI: 10.19911/j.1003-0417.tyn20221022.01

基于红外热成像检测的光伏电站异常分析

ANALYSIS OF PV POWER STATIONS ANOMALY BASED ON INFRARED THERMAL IMAGING DETECTION

  • 摘要: 红外热成像检测具有非接触、检测速度快、检测范围广、易于实现自动化和可以实时观测等优点,在众多行业中都有广泛应用。为了更好地把红外热成像技术应用于光伏电站检测领域,利用手持式红外热成像仪和无人机搭载红外热成像仪两种检测方式,对多个在运光伏电站现场进行了红外热成像检测,根据红外热成像检测结果挑选出光伏电站常见的故障案例,然后分析了这些故障导致的异常红外热成像图的典型特征及形成原因。通过红外热成像检测结果发现:光伏组件和电气设备存在一些热异常问题,导致这些热异常的故障类型可分为5类,分别为:1)光伏组件中单片太阳电池热斑;2)光伏组件内太阳电池串开路;3)光伏组串(或光伏组件)短路或开路;4)光伏阵列完整性缺失或机械受损;5)电气设备异常。研究结果可以为红外热成像技术在光伏电站检测中的应用提供参考和借鉴,通过红外热成像图来准确识别光伏电站的故障类型,及时发现光伏电站存在的发热故障和隐患,从而可以提高光伏电站的运维效率,对促进光伏电站的安全高效运行和新能源行业的发展具有重要意义。

     

    Abstract: Infrared thermal imaging detection has the advantages of non-contact,fast detection speed,wide detection range,easy to automate and enable real-time observation,and is widely used in many industries. In order to better apply infrared thermal imaging technology to the field of PV power station detection,this paper uses two detection methods,that is handheld infrared thermal imaging devices and UAV equipped with infrared thermal imaging devices to conduct infrared thermal imaging detection on multiple operational PV power station sites. Based on the infrared thermal imaging detection results,common fault cases of PV power stations are selected,and the typical characteristics and causes of abnormal infrared thermal imaging caused by these faults are analyzed. Through infrared thermal imaging detection results,it is found that there are some thermal anomalies in PV modules and electrical equipment. The types of faults that cause these thermal anomalies can be divided into five categories,namely:1) One piece of solar cell hot spots in PV modules;2) Open circuit of the solar cell string inside the PV module;3) Short circuit or open circuit of PV string(or PV module);4) Lack of integrity or mechanical damage to the PV array;5) Electrical equipment abnormality. The research results can provide reference and inspiration for the application of infrared thermal imaging technology in the detection of PV power stations. By using infrared thermal imaging images,the types of faults in PV power stations can be accurately identified,and heating faults and hidden dangers in PV power stations can be discovered in a timely manner. This can improve the operation and maintenance efficiency of PV power stations,and is of great significance for promoting the safe and efficient operation of PV power stations and the development of the new energy industry.

     

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