PREDICTION OF ASH ACCUMULATION DEGREE OF PHOTOVOLTAIC MODULES BASED ON AVERAGE GRAYSCALE VALUE AND RANDOM FOREST ALGORITHM

Chen Jiahao, Yang Jianmeng, Zhai Yongjie, Li Bin, Zeng Qiaofei

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (12) : 107-114.

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (12) : 107-114. DOI: 10.19912/j.0254-0096.tynxb.2023-1245

PREDICTION OF ASH ACCUMULATION DEGREE OF PHOTOVOLTAIC MODULES BASED ON AVERAGE GRAYSCALE VALUE AND RANDOM FOREST ALGORITHM

  • Chen Jiahao1, Yang Jianmeng1, Zhai Yongjie2, Li Bin1, Zeng Qiaofei1
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Abstract

This article numerically processes the grayscale histogram of visible light images of photovoltaic modules, introduces the concept of average grayscale value, and combines it with the photovoltaic experimental platform built by the school to confirm the corresponding relationship between the average grayscale value and the ash density of photovoltaic modules. Based on this conclusion, the image of a visual inspection platform for a photovoltaic power station in Inner Mongolia is identified and processed, and it is found that over time, the change in the average gray level difference between the clean side and the accumulated side is positively correlated with power generation loss. Based on the meteorological and image data collected by the experimental platform, a prediction model for the degree of ash accumulation is established using the random forest algorithm. Based on relevant meteorological factors, the average gray level of the ash accumulation board from the previous day is combined as the input variable to predict the average gray level of the ash accumulation board day by day. Different tuning parameters are set to improve the optimization robustness of the prediction algorithm.

Key words

photovoltaic modules / ash deposition / random forest / image recognition / average grayscale value

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Chen Jiahao, Yang Jianmeng, Zhai Yongjie, Li Bin, Zeng Qiaofei. PREDICTION OF ASH ACCUMULATION DEGREE OF PHOTOVOLTAIC MODULES BASED ON AVERAGE GRAYSCALE VALUE AND RANDOM FOREST ALGORITHM[J]. Acta Energiae Solaris Sinica. 2024, 45(12): 107-114 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1245

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