ASH DEPOSITION PREDICTION OF PHOTOVOLTAIC MODULES BASED ON IMPROVED BES-LSSVM

Gao Yu; Kang Xingguo; Zhou Shaodi; Feng Xiaojing; Wang Yinqing; Kong Xiaolong

doi:10.19912/j.0254-0096.tynxb.2022-0098

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (6) : 213-219. DOI: 10.19912/j.0254-0096.tynxb.2022-0098

ASH DEPOSITION PREDICTION OF PHOTOVOLTAIC MODULES BASED ON IMPROVED BES-LSSVM

Gao Yu, Kang Xingguo, Zhou Shaodi, Feng Xiaojing, Wang Yinqing, Kong Xiaolong

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Abstract

In order to explore the relationship between meteorological factors and photovoltaic panel ash deposition, an ash deposition prediction model based on least squares support vector machine （LSSVM） optimized by improved bald eagle algorithm （IBES） is proposed. The model uses meteorological factors such as rainfall and wind speed as input to predict the ash content of the plate area. By introducing the Gauss-Cauchy mutation operator to mutate the optimal individual of the population, the optimal selection is entered into the next iteration, which improves the shortcomings of the original vulture algorithm, such as slow convergence speed and easy to fall into local optimum. The parameters obtained by the improved algorithm are substituted into the model, and compared with other kinds of algorithm models after simulation. The results show that the prediction error of the IBES-LSSVM ash accumulation prediction model is smaller and the fitting effect is better. Finally, the power generation loss is calculated according to the cumulative ash accumulation, and the component cleaning is guided according to the rainfall conditions.

Key words

photovoltaic modules / ash / rainfall / support vector machine / bald eagle search

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Gao Yu, Kang Xingguo, Zhou Shaodi, Feng Xiaojing, Wang Yinqing, Kong Xiaolong. ASH DEPOSITION PREDICTION OF PHOTOVOLTAIC MODULES BASED ON IMPROVED BES-LSSVM[J]. Acta Energiae Solaris Sinica. 2023, 44(6): 213-219 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0098

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