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Review and Prospects of Artificial Intelligence Technology in Virtual Power Plants

Author

Listed:
  • Xinxing Liu

    (College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Ciwei Gao

    (College of Electrical Engineering, Southeast University, Nanjing 210096, China)

Abstract

With the rapid development of global renewable energy, the virtual power plant (VPP), as an emerging power management model, has attracted increasing attention. Traditional manual management is difficult to effectively deal with because of the complexity and uncertainty of the VPP. The application of artificial intelligence (AI) technology provides new solutions for the VPP to cope with these problems. This review presents the research of AI technology in the VPP. Firstly, the basic concepts and theoretical framework of the VPP are presented. Then, the application of AI technology in VPP functional modules is discussed. Finally, the challenges of the VPP in coping with uncertainty, improving algorithmic interpretability and ensuring data security are pointed out, which provides theoretical support for subsequent research in the field of VPPs.

Suggested Citation

  • Xinxing Liu & Ciwei Gao, 2025. "Review and Prospects of Artificial Intelligence Technology in Virtual Power Plants," Energies, MDPI, vol. 18(13), pages 1-26, June.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3325-:d:1686791
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    References listed on IDEAS

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    1. Yong Zhu & Liangyi Pu & Di Yang & Tun Kang & Chao Liang & Mingzhi Peng & Chao Zhai, 2025. "A Virtual Power Plant Load Forecasting Approach Using COM Encoding and BiLSTM-Att-KAN," Energies, MDPI, vol. 18(21), pages 1-23, October.

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