DUST ACCUMULATION PREDICTION FOR PHOTOVOLTAIC MODULES USING IDBO-OPTIMIZED BiTCN-BiLSTM-SA

Feng Pingping; Wen Qiao; Wang Xiao; Yang Jing; Wang Tao; Xu Linghua

doi:10.19912/j.0254-0096.tynxb.2024-1244

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (11) : 319-329. DOI: 10.19912/j.0254-0096.tynxb.2024-1244

DUST ACCUMULATION PREDICTION FOR PHOTOVOLTAIC MODULES USING IDBO-OPTIMIZED BiTCN-BiLSTM-SA

Feng Pingping¹, Wen Qiao², Wang Xiao¹, Yang Jing¹, Wang Tao¹, Xu Linghua¹

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Abstract

This study proposes an innovative dust accumulation prediction model for photovoltaic （PV） modules through the integration of an improved dung beetle optimization algorithm （IDBO） with a hybrid neural network architecture combining a bidirectional temporal convolutional network （BiTCN）, a bidirectional long short-term memory （BiLSTM）, and self-attention （SA）. The developed model achieves accurate prediction of PV module transmittance, subsequently enabling dust density estimation through established transmittance-dust density correlation formulas. The architecture strategically employs BiTCN for local feature extraction, BiLSTM for capturing global temporal dependencies, and SA for dynamic feature weighting optimization, thereby enhancing overall prediction precision. Furthermore, the IDBO algorithm is implemented for hyperparameter optimization to maximize model performance. To validate the approach, we establish an IoT-based data acquisition platform that collects comprehensive PV module transmittance data and associated environmental parameters, forming a robust dataset for model training and evaluation. Experimental results demonstrate superior performance metrics with root mean square error （RMSE） of 0.0126, mean absolute error （MAE） of 0.007, and prediction accuracy reaching 96.26%, significantly outperforming benchmark algorithms. This advancement enables more precise dust accumulation forecasting.

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photovoltaic modules / prediction model / dust deposition / bi-directional short-term memory network / attention mechanism

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Feng Pingping, Wen Qiao, Wang Xiao, Yang Jing, Wang Tao, Xu Linghua. DUST ACCUMULATION PREDICTION FOR PHOTOVOLTAIC MODULES USING IDBO-OPTIMIZED BiTCN-BiLSTM-SA[J]. Acta Energiae Solaris Sinica. 2025, 46(11): 319-329 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1244

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