光伏板局部阴影遮蔽图像的边缘检测算法研究
Research on Edge Detection Algorithm of Photovoltaic Panel’s Partial Shadow Shading Image

为大幅降低光伏板受阴影遮蔽影响导致的热斑效应以及功率损失，本文把研究对象定为局部阴影条件下的光伏组件，通过对光伏组件上不同的位置进行随机遮挡，得到多种阴影条件下的阴影图像，用不同的算法对所得数据进行对比分析。利用图像配准、图像增强、图像分割等数字图像处理技术来分辨阴影区，采用中值滤波对光伏板条纹复杂所造成的影响进行去噪处理。研究实验结果表明：在模拟实验空间内，canny边缘检测法可精确分割阴影，准确得出阴影区域，不会因膨胀使得阴影区域扩大。精确的阴影区域定位有利于研究光伏组件的输出特性，提升光伏板发电效率。
In order to greatly reduce the hot spot effect and power loss caused by the shadow shading of photovoltaic panels, this paper sets the research object as the photovoltaic modules under partial shadow conditions. By randomly shielding different positions on the photovoltaic modules, various shadow conditions are obtained. Different algorithms are used to compare and analyze the obtained data. Digital image processing technologies, such as image registration, image enhancement, and image segmentation, are used to distinguish shadow areas, and median filtering is used to denoise the effects of complex stripes on photovoltaic panels. The experimental results show that: in the simulated experimental space, the canny edge detection method can accurately segment the shadow and accurately obtain the shadow area without expanding the shadow area due to expansion. Precise positioning of the shaded area is conducive to studying the output characteristics of photovoltaic modules and improving the power generation efficiency of photovoltaic panels.