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Artificial Intelligence in Renewable Energy Systems: Applications and Security Challenges

Author

Listed:
  • Hui Xiang

    (State Grid Information and Telecommunication Group Co., Ltd., Beijing 100029, China)

  • Xiaolei Li

    (State Grid Information and Telecommunication Group Co., Ltd., Beijing 100029, China)

  • Xiao Liao

    (State Grid Information and Telecommunication Group Co., Ltd., Beijing 100029, China)

  • Wei Cui

    (State Grid Information and Telecommunication Group Co., Ltd., Beijing 100029, China)

  • Fengkai Liu

    (School of Automation Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, China
    National Innovation Platform (Center) for Industry-Education Integration of Energy Storage Technology, Xi’an Jiaotong University, Xi’an 710049, China)

  • Donghe Li

    (School of Automation Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

In the context of the global active pursuit of sustainable development and the heightened priority placed on sustainable energy, renewable energy systems, as a crucial solution to energy crises and environmental challenges, are of increasing significance. The extensive development and utilization of renewable energy sources such as wind and solar have become the core driving force for promoting the transformation of the energy structure. The research and construction of energy storage systems have also become trends in future energy development. AI, with its powerful data-processing and intelligent decision-making capabilities, has been deeply integrated into multiple key aspects of renewable energy systems. This review fills a gap in the relevant literature by conducting an updated technological assessment of the application of AI technology in renewable energy systems including wind power systems, PV power systems, energy storage systems, and others. Moreover, this paper analyzes the security challenges of AI in renewable energy systems. The primary aim of this review is to identify the advantages and existing security challenges of introducing AI technology into renewable energy systems, so as to help improve the production efficiency and information security level of different forms of renewable energy systems.

Suggested Citation

  • Hui Xiang & Xiaolei Li & Xiao Liao & Wei Cui & Fengkai Liu & Donghe Li, 2025. "Artificial Intelligence in Renewable Energy Systems: Applications and Security Challenges," Energies, MDPI, vol. 18(8), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:8:p:1931-:d:1631871
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    References listed on IDEAS

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