MULTI-FACTOR PHOTOVOLTAIC POWER GENERATION PREDICTION BASED ON TIME-FREQUENCY DOMAIN DECOMPOSITION ENHANCEMENT FUSION TRANSFORMER

Luo Qiang; Gao Chong; Cao Huazhen; He Xuan; Zeng Qingbin; Zhang Yongjun

doi:10.19912/j.0254-0096.tynxb.2024-1912

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (3) : 604-615. DOI: 10.19912/j.0254-0096.tynxb.2024-1912

MULTI-FACTOR PHOTOVOLTAIC POWER GENERATION PREDICTION BASED ON TIME-FREQUENCY DOMAIN DECOMPOSITION ENHANCEMENT FUSION TRANSFORMER

Luo Qiang¹, Gao Chong¹, Cao Huazhen¹, He Xuan¹, Zeng Qingbin^2,3, Zhang Yongjun³

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Abstract

A multi-factor photovoltaic power prediction method based on a time-frequency domain decomposition enhancement fusion Transformer is proposed to address the performance limitations caused by insufficient mining of the trend and randomness of the photovoltaic power change curve in existing photovoltaic power prediction methods. Firstly, an encoder-decoder framework is constructed, in which historical and current PV power data are decomposed into periodic and trend components through time-domain and frequency-domain enhancement modules. The semantic relationships between current and historical data are further extracted using time-domain and frequency-domain enhanced attention mechanisms. Subsequently, a stochastic layer is employed to capture the stochastic component of the current data. Then, a multi-level adaptive fusion strategy integrates the periodic, trend, and stochastic components of PV power data for forecasting. In addition, multiple factors such as solar irradiance, humidity, wind speed, and temperature are incorporated using an independent multi-channel feature extraction approach to reduce data redundancy and further improve model performance. Experiments on PVGD-1 and DKASC-Sanyo datasets show that the proposed method outperforms Informer, Autoformer, and Fedformer.

Key words

photovoltaic power / prediction / Transformer / attention mechanism / time-frequency domain decomposition

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Luo Qiang, Gao Chong, Cao Huazhen, He Xuan, Zeng Qingbin, Zhang Yongjun. MULTI-FACTOR PHOTOVOLTAIC POWER GENERATION PREDICTION BASED ON TIME-FREQUENCY DOMAIN DECOMPOSITION ENHANCEMENT FUSION TRANSFORMER[J]. Acta Energiae Solaris Sinica. 2026, 47(3): 604-615 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1912

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