SHORT-TERM PHOTOVOLTAIC POWER FORECASTING BASED ON CLUSTERING AND HYBRID FEATURE EXTRACTION USING BiGRU-MDSA

Zhou Yucai, Qin Yuanheng, Xiao Zhenjiang, Xie Qiyue, Fu Qiang, Tan Yanxiang

Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (8) : 244-251.

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (8) : 244-251. DOI: 10.19912/j.0254-0096.tynxb.2025-0729

SHORT-TERM PHOTOVOLTAIC POWER FORECASTING BASED ON CLUSTERING AND HYBRID FEATURE EXTRACTION USING BiGRU-MDSA

  • Zhou Yucai1,2, Qin Yuanheng1,3, Xiao Zhenjiang2, Xie Qiyue1, Fu Qiang1, Tan Yanxiang4
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Abstract

To address the volatility and uncertainty of photovoltaic (PV) power generation, this study proposes a short-term PV power forecasting method based on fuzzy C-means (FCM) clustering, hybrid scale feature extraction (HSFE), and multi-head dynamic sparse attention (MDSA) mechanism integrated into a bidirectional gated recurrent unit (BiGRU) framework. First, historical PV data undergo preprocessing and outlier analysis, followed by a correlation analysis of the factors influencing PV output under different weather conditions. Then, dimensionality reduction is performed, and FCM is used to classify the input data based on weather conditions. The clustered data are fed into a BiGRU model enhanced with the HSFE module to enhance its capability in extracting information across different temporal scales. Furthermore, the multi-head dynamic sparse attention mechanism is incorporated to dynamically adjust the model’s focus on temporal features across time steps. Simulation results and comparative experiments demonstrate that the proposed composite model achieves superior accuracy and generalization performance compared to benchmark methods.

Key words

PV power generation / feature extraction / short-term power forecasting / multi-head dynamic sparse attention mechanism / bidirectional gated recurrent unit

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Zhou Yucai, Qin Yuanheng, Xiao Zhenjiang, Xie Qiyue, Fu Qiang, Tan Yanxiang. SHORT-TERM PHOTOVOLTAIC POWER FORECASTING BASED ON CLUSTERING AND HYBRID FEATURE EXTRACTION USING BiGRU-MDSA[J]. Acta Energiae Solaris Sinica. 2026, 47(8): 244-251 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0729

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