基于人工智能的物联网系统用于光伏模块中的热点检测,用于广泛的辐射范围
Leonardo Cardinale-Villalobos1, Efren Jimenez-Delgado2, Yariel García-Ramírez1
1School of Electronic Engineering, Costa Rica Institute of Technology, Cartago 159-7050, Costa Rica.
Sensors (Basel, Switzerland)
|August 12, 2023
概括
这项研究介绍了一种人工智能驱动的物联网平台,用于检测光伏 (PV) 热点,使用红外热学 (IRT) 即使在较低的辐射. 该系统实现了高精度,可实现高效的光伏模块诊断和潜在的成本节省.
科学领域:
- 可再生能源系统可再生能源系统
- 在工程领域的人工智能.
- 非破坏性测试 不破坏性测试
背景情况:
- 光伏 (PV) 装置需要定期诊断以确保最佳性能和寿命.
- 红外热学 (IRT) 是一个关键的诊断工具,但受到高辐射要求 (>700 W/m2) 的限制.
- 智能城市日益采用光伏技术,需要针对不同环境条件改进诊断技术.
研究的目的:
- 开发和评估一个物联网平台,利用人工智能 (AI) 来自动检测光伏模块中的热点.
- 在较低辐射条件下 (> 300 W/m2) 实现基于IRT的光伏诊断.
- 为光伏安装管理和检查提供一个具有成本效益和效率的替代方案.
主要方法:
- 实施一个集成AI算法 (深度学习和机器学习) 的物联网平台.
- 训练和测试人工智能模型的数据来自一个真正的光伏安装与诱导热点的数据.
- 在不同的辐射水平下分析光伏模块之间的温度差异.
主要成果:
- 这种由人工智能驱动的系统成功地检测到热点,灵敏度为0.995,准确度为0.923.
- 在包括污垢,短路和部分阴影在内的具有挑战性的条件下实现了有效的检测.
- 该平台在低至300W/m2的辐射强度下表现出可靠的性能.
结论:
- 开发的物联网平台为在减少辐射条件下的光伏热点检测提供了可行的解决方案.
- 这种人工智能驱动的方法增强了IRT在光伏诊断方面的实际应用.
- 该系统通过提高效率和早期故障检测,为光伏安装经理和检查员带来了显著的经济效益.
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