摘要
Abstract
Currently,a huge number of photovoltaic plants have been installed worldwide,most of which are installed outdoors and continuously exposed to harsh environmental conditions,making them prone to different types of faults.Therefore,it is crucial to design intelligent and automated remote monitoring systems and fault diagnosis systems for photovoltaic power plants.A review is conducted on the fault detection and diagnosis methods of photovoltaic array,Internet of Things technology,and the application of artificial intelligence in photovoltaic power plants.Two types of photovoltaic monitoring systems are introduced,namely centralized and decentralized.The workflow of photovoltaic monitoring system is divided into three stages,acquisition layer,preprocessing and recording layer,storage and application layer.A summary of research on photovoltaic array fault diagnosis is carried out from two perspectives:visual imaging and electrical characteristics.The most advanced algorithms such as machine learning and deep learning are introduced,and comparisons are made in terms of cost implementation,complexity,accuracy,software suitability,and feasibility of real-time applications.Finally,the shortcomings and development trends of these technologies are pointed out.关键词
光伏阵列故障类型/故障检测与诊断/物联网/机器学习/深度学习Key words
photovoltaic array fault types/fault detection and diagnosis/Internet of Things/machine learning/deep learning分类
信息技术与安全科学
