基于图像矫正与重构的光伏出力损失预测  

Photovoltaic Output Loss Forecasting Based on Image Correction and Reconstruction

作　　者：武云逸 王森[2] 孙永辉[1,2] 张文杰 WU Yunyi;WANG Sen;SUN Yonghui;ZHANG Wenjie(College of Artificial Intelligence and Automation,Hohai University,Nanjing 210098,China;School of Electrical and Power Engineering,Hohai University,Nanjing 210098,China;Department of Electrical and Electronic Engineering,The Hong Kong Polytechnic University,Hong Kong 999077,China)

机构地区：[1]河海大学人工智能与自动化学院,江苏省南京市210098 [2]河海大学电气与动力工程学院,江苏省南京市210098 [3]香港理工大学电机与电子工程学系,中国香港999077

出　　处：《电力系统自动化》2024年第20期130-139,共10页Automation of Electric Power Systems

基　　金：国家自然科学基金资助项目(62073121)。

摘　　要：随着“双碳”目标的提出,光伏发电在电网中的渗透率不断提高,而光伏发电可能受到多种环境因素影响。其中,光伏面板污染造成的局部遮挡是造成功率损失、影响光伏发电效率的重要因素。针对传统污染检测依赖于大型数据集的构建,且损失预测存在着预测精度低、数据形式单一等问题,提出基于图像矫正与重构的光伏出力损失预测方法,利用图像矫正与重构检测光伏面板污染,并对功率损失进行估计。该方法首先通过图像矫正与图像重构检测污染,并将图像数据转换为文中数据;其次,从矫正与重构后的图像数据中挖掘特征;最后,构建包含时序信息的多模态特征数据进行损失预测。测试结果表明,文中所提方法较传统方法性能得到提升。With the proposal of the“carbon peaking and carbon neutrality”goals,the penetration rate of photovoltaic power generation in the power grid continues to increase.However,photovoltaic power generation may be affected by various environmental factors.Among them,local obstruction caused by photovoltaic panel pollution is an important factor that causes power loss and affects the efficiency of photovoltaic power generation.In response to the traditional pollution detection relying on the construction of large datasets,and the problems of low forecasting accuracy and single data form in loss forecasting,a forecasting method of photovoltaic output loss based on image correction and reconstruction is proposed,which uses image correction and reconstruction to detect photovoltaic panel pollution and estimate power loss.This method first detects pollution through image correction and image reconstruction,and converts image data into text data.Then,features are extracted from the corrected and reconstructed image data.Finally,multi-modal feature data containing temporal information is constructed for loss forecasting.The test results show that the proposed method has improved performance compared with traditional methods.

关 键 词：光伏发电 损失预测 图像重构 图像矫正 

分 类 号：TM615[电气工程—电力系统及自动化] TP391.41[自动化与计算机技术—计算机应用技术]