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MSVMD-Informer: A Multi-Variate Multi-Scale Method to Wind Power Prediction

Author

Listed:
  • Zhijian Liu

    (Faculty of Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China)

  • Jikai Chen

    (Faculty of Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China)

  • Hang Dong

    (Faculty of Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China)

  • Zizhuo Wang

    (Faculty of Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China)

Abstract

Wind power prediction plays a crucial role in enhancing power grid stability and wind energy utilization efficiency. Existing prediction methods demonstrate insufficient integration of multi-variate features, such as wind speed, temperature, and humidity, along with inadequate extraction of correlations between variables. This paper proposes a novel multi-variate multi-scale wind power prediction method named multi-scale variational mode decomposition informer (MSVMD-Informer). First, a multi-scale modal decomposition module is designed to decompose univariate time-series features into multiple scales. Adaptive graph convolution is applied to extract correlations between scales, while self-attention mechanisms are utilized to capture temporal dependencies within the same scale. Subsequently, a multi-variate feature fusion module is proposed to better account for inter-variable correlations. Finally, the informer is reconstructed by integrating the aforementioned modules, enabling multi-variate multi-scale wind power forecasting. The proposed method was evaluated through comparative experiments and ablation studies against seven baselines using a public dataset and two private datasets. Experimental results demonstrate that our proposed method achieves optimal metric performance, with its lowest MAPE scores being 1.325%, 1.500% and 1.450%, respectively.

Suggested Citation

  • Zhijian Liu & Jikai Chen & Hang Dong & Zizhuo Wang, 2025. "MSVMD-Informer: A Multi-Variate Multi-Scale Method to Wind Power Prediction," Energies, MDPI, vol. 18(7), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1571-:d:1617472
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    References listed on IDEAS

    as
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