Adaptive Resilient Control for Variable-Speed Wind Turbines Against False Data Injection Attacks

With the increasing expansion of wind power installed capacity, the deployed wind farms are becoming an attractive target for malicious entities. The geographical scale of the wind farm, remoteness of its location, flat logical control network, and fragile control protocols make it vulnerable to cyber attacks. False data injection (FDI) attacks on the value of the rotor speed may lead to reduced power generation efficiency, overload of the drive-train, and even shutdowns and potentially costly equipment damage of wind turbines. Therefore, in this article, we attempt to propose an adaptive resilient control scheme for the variable-speed wind turbine (VSWT) operating at low-speed region in face of FDI attacks. The control goal is to meet the requirements in the low-speed operation of the WT and to optimize the power drawn from the wind by adjusting the generator torque in the presence of cyber attacks. Therein, a dynamic detection method based on rotor speed observer/estimator is designed to identify the FDI attacks. After locating the attack, an adaptive resilient control strategy for the generator torque is implemented to guarantee the control target of optimal power tracking and improve the attack resiliency of the WT control system. Extensive studies are carried out on a 1.5 MW doubly-fed induction generator-based WT, and the simulation results indicate that the proposed control strategy could effectively reduce both network and physical impacts caused by cyber attacks.

Automated summary

In this article, an adaptive resilient control scheme is proposed to address false data injection attacks on wind farms. A dynamic detection method and adaptive generator torque control strategy are implemented to ensure optimal power tracking and improve attack resilience.