SOLAR RADIATION PREDICTION BASED ON VMD-T2V-TRANSFORMER

Hu Yabin; Shi Jiarong; Chen Yingrui; Yong Longquan

doi:10.19912/j.0254-0096.tynxb.2024-0442

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (7) : 778-784. DOI: 10.19912/j.0254-0096.tynxb.2024-0442

Special Topics of Academic Papers at the 111th Annual Meeting of the China Association for Science and Technology

SOLAR RADIATION PREDICTION BASED ON VMD-T2V-TRANSFORMER

Hu Yabin¹, Shi Jiarong¹, Chen Yingrui¹, Yong Longquan²

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Abstract

The uncertainty in solar radiation leads to obvious randomness and instability in solar power generation. To address this issue, this paper proposes a VMD-T2V-Transformer model for solar radiation prediction by integrating variational mode decomposition （VMD）, Time2Vec （T2V） and Transformer. First, the VMD is used to decompose the solar radiation sequence into several sub-sequences. Next, the T2V is adopted to embed the temporal features of each decomposed sub-sequence. Then, a Transformer prediction model is established for each sub-sequence based on the embedded time features. Finally, the predicted results of all sub-models are superimposed to obtain the final predicted values. The experimental results show that the proposed model in this paper outperforms other mainstream models in terms of RMSE and MAE, which can be reduced by at least 13.81％ and 16.44％ respectively.

Key words

solar radiation / solar power generation / variational mode decomposition / Time2Vec / Transformer

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Hu Yabin, Shi Jiarong, Chen Yingrui, Yong Longquan. SOLAR RADIATION PREDICTION BASED ON VMD-T2V-TRANSFORMER[J]. Acta Energiae Solaris Sinica. 2025, 46(7): 778-784 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0442

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