Design of a cyber-resilient coordinated control scheme for electric vehicles to enhance dynamic frequency support in a multi-area power grid: A Nordic case study

This paper proposes a coordinated Electric Vehicle (EV) aggregation strategy to enhance frequency regulation and cyber-resilience in a multi-area power system under False Data Injection (FDI) attacks. The approach addresses frequency fluctuations caused by load dynamics and examines the impact of FDI cyberattacks in the presence of Automatic Generation Control (AGC). The increasing integration of communication-assisted control and EV participation introduces vulnerabilities to cyberattacks that can manipulate frequency measurement signals and degrade AGC performance. Aggregated EVs are therefore utilized as fast-responsive distributed resources to provide rapid frequency support during disturbances and cyber-compromised operating conditions. A Beluga Whale Optimization (BWO)-based switching controller is proposed to optimally tune EV controller parameters under varying operating conditions and attack scenarios. The proposed strategy is validated on a modified Nordic32 multi-area test system modeled in DIgSILENT PowerFactory. The study investigates the effect of FDI attacks on EV aggregator frequency measurements, where false signals conceal actual frequency deviations and delay EV frequency support. The performance of the proposed method is compared with Particle Swarm Optimization (PSO), BAT, Cuckoo Search Algorithm (CSA), and conventional AGC-based control tuned with PSO approaches. Simulation results show that the proposed BWO-based coordinated EV controller achieves a 59.2% reduction in settling time and a 66.7% reduction in frequency undershoot compared to AGC. The results indicate enhanced robustness, rapid convergence, and better frequency recovery performance when subjected to cyberattacks, thus making this approach more appropriate for practical applications on real-time cyber-physical power systems.