Ding Haotian, Guo Rui, Xing Huan, Chen Yu, He Jiajun, Luo Junxian, Chen Maojie, Chen Ye, Tang Shaochun, Xu Fei
Key National Laboratory of Solid State Microstructures, Collaborative Innovation Center of Advanced Microstructures, College of Engineering and Applied Sciences, Nanjing University, Nanjing 210023, China.
College of Physics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Sensors (Basel). 2025 Aug 7;25(15):4879. doi: 10.3390/s25154879.
Against the backdrop of an urgent energy crisis, solar energy has attracted sufficient attention as one of the most inexhaustible and friendly types of environmental energy. Faced with long service and harsh environment, the poor performance ratios of photovoltaic arrays and safety hazards are frequently boosted worldwide. In particular, the hot spot effect plays a vital role in weakening the power generation performance and reduces the lifetime of photovoltaic (PV) modules. Here, our research reports a spatial-temporal hot spot management system integrated with fiber Bragg grating (FBG) temperature sensor arrays and cooling hydrogels. Through finite element simulations and indoor experiments in laboratory conditions, a superior cooling effect of hydrogels and photoelectric conversion efficiency improvement have been demonstrated. On this basis, field tests were carried out in which the FBG arrays detected the surface temperature of the PV module first, and then a classifier based on an optimized artificial neural network (ANN) recognized hot spots with an accuracy of 99.1%. The implementation of cooling hydrogels as a feedback mechanism achieved a 7.7 °C reduction in temperature, resulting in a 5.6% enhancement in power generation efficiency. The proposed strategy offers valuable insights for conducting predictive maintenance of PV power plants in the case of hot spots.
在紧迫的能源危机背景下，太阳能作为最取之不尽且环保的能源类型之一，已引起了足够的关注。面对光伏阵列服役时间长且环境恶劣的情况，全球范围内光伏阵列的性能不佳和安全隐患问题频繁出现。特别是，热点效应在削弱发电性能和缩短光伏（PV）组件寿命方面起着至关重要的作用。在此，我们的研究报告了一种集成了光纤布拉格光栅（FBG）温度传感器阵列和冷却水凝胶的时空热点管理系统。通过有限元模拟和实验室条件下的室内实验，已证明水凝胶具有出色的冷却效果，并提高了光电转换效率。在此基础上，进行了现场测试，其中FBG阵列首先检测光伏组件的表面温度，然后基于优化人工神经网络（ANN）的分类器以99.1%的准确率识别热点。作为反馈机制实施的冷却水凝胶使温度降低了7.7°C，发电效率提高了5.6%。所提出的策略为在出现热点的情况下对光伏电站进行预测性维护提供了有价值的见解。
