As the global transition to sustainable energy accelerates, wind power remains pivotal in reducing carbon emissions and achieving renewable energy targets. However, greater reliance on wind energy systems increases susceptibility to cyberattacks, notably False Data Injection (FDI) attacks, which manipulate operational data and undermine the decision-making critical for efficient energy production. This study introduces a novel analytical framework to assess the impact of FDI attacks on variable-speed wind turbine output power. Simulations, conducted using a MATLAB-based induction generator model, evaluate the effects of injecting false data into parameters such as wind speed, blade pitch angle, and generator angular speed. Results demonstrate that FDI attacks targeting wind speed induce significant power output deviations, causing decision-making errors that threaten operational reliability. In contrast, pitch angle manipulations have negligible effects on power generation. These findings emphasize the urgent need for robust cybersecurity measures to protect wind energy infrastructure from evolving cyber-threats. This research advocates advanced detection and mitigation strategies to enhance system resilience, ensuring wind power’s role in a low-carbon future. By identifying critical vulnerabilities, the analysis informs policymakers and industry stakeholders, guiding investments in cybersecurity to safeguard renewable energy systems. Such efforts are essential to maintain operational stability and support global sustainability goals, reinforcing wind power’s contribution to clean energy transitions.
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Tanha et al. (2025) studied this question.
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