Review and Prospects of Artificial Intelligence Technology in Virtual Power Plants

Xinxing Liu and Ciwei Gao ()
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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

Energies, 2025, vol. 18, issue 13, 1-26

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.

Keywords: virtual power plant; artificial intelligence; optimal scheduling; power prediction; data security (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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