A multi-sensor information fusion monitoring system for photovoltaic power generation

Xiao Wang, Bo Zhao, Shengxian Cao, Siyuan Fan
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Abstract

In this paper, a novel multi-sensor information fusion (MSIF) monitoring system of photovoltaic (PV) power station is proposed, which can solve the difficulty in determining the dust accumulation degree of PV power station operation and maintenance personnel to the panels. According to the real-time monitoring data, a relationship model can be established to reflect the effect of dust accumulation on PV panels operating state. Meanwhile, a dust detection and classification method based on convolutional neural network (CNN) is also given to analyze the visible-light images and operation data. Because of identifying rapidly the images of the dust-covered PV panels, the classification result can be used as a guideline for cleaning the dust accumulation of PV panels. Finally, the experimental results show the effectiveness of the proposed monitoring system.
光伏发电多传感器信息融合监测系统
本文提出了一种新型的光伏电站多传感器信息融合(MSIF)监测系统,解决了光伏电站运维人员对面板积尘程度难以确定的问题。根据实时监测数据,可以建立反映积尘对光伏板运行状态影响的关系模型。同时,提出了一种基于卷积神经网络(CNN)的粉尘检测分类方法,对可见光图像和运行数据进行分析。由于可以快速识别光伏板上的灰尘图像,因此分类结果可以作为清洁光伏板上积尘的指导方针。最后,实验结果表明了所提出的监测系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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