Analysis of the Role of Artificial Intelligence in Enhancing the Network Security Protection of Renewable Energy Systems

The rapid advancement and integration of renewable energy systems (RES) such as solar, wind, and hydropower have intensified the need for robust network security solutions to protect against emerging cyber vulnerabilities. These systems are increasingly interconnected with digital grids and IoT devices, heightening their exposure to cyber threats that, if exploited, could disrupt energy supply and lead to severe socio-economic repercussions. This paper proposes an artificial intelligence (AI)-driven approach to enhance network security specifically for renewable energy (RE) infrastructures, targeting vulnerabilities that affect data integrity and operational stability. This research introduces an Adaptive Spider Wasp optimizer-mutated Extreme Gradient Boosting (ASW-XGBoost) model as a novel solution designed to improve detection accuracy and enhance resilience across diverse RE networks. The proposed method initiates the creation of a dataset representative of both power system behaviors and potential cyber-attacks, pre-processed using a normalization algorithm to improve data quality. Feature extraction leverages a scalable approach to identify critical indicators unique to RE environments. The ASW-XGBoost model combines the optimization advantages of adaptive spider wasp algorithms with the classification robustness of XGBoost, allowing precise identification of attack signatures even within fluctuating renewable power outputs. Performance evaluations, conducted in simulated power networks with high renewable penetration, demonstrate that ASW-XGBoost surpasses conventional methods in both detection rate and operational efficiency. The findings underscore the model’s capacity to adapt to dynamic, renewable-intensive environments, offering a more responsive solution to evolving cyber threats. This paper concludes with a discussion on the implications of AI-enhanced security protocols for the RE sector, highlighting ASW-XGBoost’s potential as a foundation for further research and application in sustainable energy cybersecurity.