Photovoltaic Output Loss Forecasting Based on Image Correction and Reconstruction

WU Yunyi; WANG Sen; SUN Yonghui; ZHANG Wenjie

doi:10.7500/AEPS20231201001

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Photovoltaic Output Loss Forecasting Based on Image Correction and Reconstruction

Basic Research | 更新时间：2025-06-16

- Photovoltaic Output Loss Forecasting Based on Image Correction and Reconstruction
- Automation of Electric Power Systems Vol. 48, Issue 20, Pages: 130-139(2024)
- 作者机构：
  
  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，香港 999077
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(62073121)
- DOI：10.7500/AEPS20231201001
  CLC：
- Received：01 December 2023，
  
  Revised：2024-04-19，
  
  Published Online：13 September 2024，
  
  Published：25 October 2024
- 稿件说明：
移动端阅览
武云逸,王森,孙永辉等.基于图像矫正与重构的光伏出力损失预测[J].电力系统自动化,2024,48(20):130-139.

WU Yunyi,WANG Sen,SUN Yonghui,et al.Photovoltaic Output Loss Forecasting Based on Image Correction and Reconstruction[J].Automation of Electric Power Systems,2024,48(20):130-139.
武云逸,王森,孙永辉等.基于图像矫正与重构的光伏出力损失预测[J].电力系统自动化,2024,48(20):130-139. DOI： 10.7500/AEPS20231201001.

WU Yunyi,WANG Sen,SUN Yonghui,et al.Photovoltaic Output Loss Forecasting Based on Image Correction and Reconstruction[J].Automation of Electric Power Systems,2024,48(20):130-139. DOI： 10.7500/AEPS20231201001.

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。

Abstract

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

Keywords

references

孙永辉，孟雲帆，葛磊蛟，等 . 人工智能赋能微电网运行优化的应用及展望［J］. 高电压技术， 2023 ， 49 （ 6 ）： 2239 - 2252 .

SUN Yonghui ， MENG Yunfan ， GE Leijiao ， et al . Application and prospects of artificial intelligence empowered microgrid operation optimization ［J］. High Voltage Technology ， 2023 ， 49 （ 6 ）： 2239 - 2252 .

GE L ， LIU H ， YAN J ， et al . Optimal integrated energy system planning with DG uncertainty affine model and carbon emissions charges ［J］. IEEE Transactions on Sustainable Energy ， 2022 ， 13 （ 2 ）： 905 - 918 .

SUN Y ， ZHOU Y ， WANG S ， et al . Nonparametric prediction intervals of regional PV outputs based on Granule-based clustering and direct optimization programming ［J］. Modern Power Systems and Clean Energy ， 2023 ， 11 （ 5 ）： 1450 - 1461 .

CAI Y ， YAO W ， WEN J ， et al . Impact of active frequency support control of photovoltaic on PLL-based photovoltaic of wind-photovoltaic-thermal coupling system ［J］. IEEE Transactions on Power Systems ， 2023 ， 38 （ 5 ）： 4788 - 4799 .

PENG X ， LI Y ， DONG L ， et al . Short-term wind power prediction based on wavelet feature arrangement and convolutional neural networks deep learning ［J］. IEEE Transactions on Industry Applications ， 2021 ， 57 （ 6 ）： 6375 - 6384 .

HOU J ， LEI S ， SONG Y ， et al . The cost and benefit of enhancing cybersecurity for hybrid AC/DC grids ［J］. IEEE Transactions on Smart Grid ， 2023 ， 14 （ 6 ）： 4758 - 4771 .

林帆，张耀，东琦，等 . 基于分位数插值和深度自回归网络的光伏出力概率预测［J］. 电力系统自动化， 2023 ， 47 （ 9 ）： 79 - 87 .

LIN Fan ， ZHANG Yao ， DONG Qi ， et al . Prediction of photovoltaic output probability based on quantile interpolation and deep autoregressive network ［J］. Automation of Electric Power Systems ， 2023 ， 47 （ 9 ）： 79 - 87 .

MA J ， BI Z ， WANG K ， et al . Real-time maximum power point estimation of photovoltaic systems using shading information ［J］. IEEE Transactions on Industry Applications ， 2021 ， 57 （ 6 ）： 6395 - 6404 .

刘嘉诚，刘俊，赵宏炎，等 . 基于DKDE与改进mRMR特征选择的短期光伏出力预测［J］. 电力系统自动化， 2021 ， 45 （ 14 ）： 13 - 21 .

LIU Jiacheng ， LIU Jun ， ZHAO Hongyan ， et al . Short-term PV output prediction based on DKDE and improved mRMR feature selection ［J］. Automation of Electric Power Systems ， 2021 ， 45 （ 14 ）： 13 - 21 .

黎敏，林湘宁，张哲原，等 . 超短期光伏出力区间预测算法及其应用［J］. 电力系统自动化， 2019 ， 43 （ 3 ）： 10 - 16 .

LI Min ， LIN Xiangning ， ZHANG Zheyuan ， et al . Ultra-short-term PV output interval prediction algorithm and its application ［J］. Automation of Electric Power Systems ， 2019 ， 43 （ 3 ）： 10 - 16 .

LIN Y ， XU Z ， CHEN D ， et al . Wood crack detection based on data-driven semantic segmentation network ［J］. IEEE/CAA Journal of Automatica Sinica ， 2023 ， 10 （ 6 ）： 1510 - 1512 .

MUHAMMAD U ， SAJID S ， HARIS M ， et al . Early hotspot detection in photovoltaic modules using color image descriptors： an infrared thermography study ［J］. International Journal of Energy Research ， 2022 ， 46 （ 2 ）： 774 - 785 .

MUHAMMAD U ， HAFIZ F ， MANZAR M ， et al . A machine learning framework to identify the hotspot in photovoltaic module using infrared thermography ［J］. Solar Energy ， 2020 ， 208 （ 15 ）： 643 - 651 .

CHRIS H ， SAHADEV P ， SANG W ， et al . Automatic detection system of deteriorated PV modules using drone with thermal camera ［J］. Applied Sciences ， 2020 ， 10 （ 11 ）： 3802 .

MUSTAFA Y ， NURETTIN B ， ABDULKADIR G . Efficient deep feature extraction and classification for identifying defective photovoltaic module cells in electroluminescence images ［J］. Expert Systems with Applications ， 2021 ， 175， 114810 ： 0957 - 4174 .

AHMAD M ， JUSTIN S ， NICHOLAS A ， et al . Generalized and mechanistic PV module performance prediction from computer vision and machine learning on electroluminescence images ［J］. IEEE Journal of Photovoltaics ， 2020 ， 10 （ 3 ）： 878 - 887 .

ROBINSON C ， RODRIGO B ， DANILO E ， et al . Automatic soiling and partial shading assessment on PV modules through RGB images analysis ［J］. Applied Energy ， 2022 ， 306 ： 117964 .

ZHANG Wenjie ， LIU Shunqi ， GANDHI O ， et al . Deep-learning-based probabilistic estimation of solar PV soiling loss ［J］. IEEE Transactions on Sustainable Energy ， 2021 ， 12 （ 4 ）： 2436 - 2444 .

WANG Yiqian ， ZHANG Junkang ， CAVICHINI M ， et al . Robust content-adaptive global registration for multimodal retinal images using weakly supervised deep-learning framework ［J］. IEEE Transactions on Image Processing ， 2021 ， 30 ： 3167 - 3178 .

白捷予，董存，王铮，等 . 考虑云层遮挡的光伏发电功率超短期预测技术［J］. 高电压技术， 2023 ， 49 （ 1 ）： 159 - 168 .

BAI Jieyu ， DONG Cun ， WANG Zheng ， et al . Ultra-short-term prediction technology of photovoltaic power generation considering cloud covering ［J］. High Voltage Engineering ， 2023 ， 49 （ 1 ）： 159 - 168 .

ZHOU Jingchun ， PANG Lei ， ZHANG Dehuan ， et al . Underwater image enhancement method via multi-interval subhistogram perspective equalization ［J］. IEEE Journal of Oceanic Engineering ， 2023 ， 48 （ 2 ）： 474 - 488 .

BHANDARI A ， SINGH A ， KUMAR I ， et al . Spatial context energy curve-based multilevel 3-D OTSU algorithm for image segmentation ［J］. IEEE Transactions on Systems， Man， and Cybernetics： Systems ， 2021 ， 51 （ 5 ）： 2760 - 2773 .

YI Z ， HU J ， ZHAO Y ， et al . Fast and calibration-less low-rank parallel imaging reconstruction through unrolled deep learning estimation of multi-channel spatial support maps ［J］. IEEE Transactions on Medical Imaging ， 2023 ， 42 （ 6 ）： 1644 - 1655 .

WANG Dini ， LI Lang ， ZHAO Da . Corporate finance risk prediction based on LightGBM ［J］. Information Sciences ， 2022 ， 602 ： 259 - 268 .

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