Cascaded fractional order control for load frequency stability of power systems integrated with renewable energy and electric vehicles

Frequency stability is vital for maintaining the reliable operation of a modern power network, as load frequency control (LFC) ensures the effective frequency regulation through balanced generation and demand, enabling a secure and adaptable grid environment. With increasing penetration of renewable energy sources (RESs), modern grids require advanced energy storage strategies (ESSs) to handle frequency deviations triggered by intermittent renewable generation and declining system inertia. Among promising solutions, electric vehicles (EVs) are increasingly being investigated as distributed energy storage units, providing valuable flexibility for supporting frequency regulation in low-inertia power systems. To address the dynamic complexities introduced by EV integration, this study evaluates various conventional generation units (reheat-based thermal, hydro and gas plants), renewable units (solar and wind) and energy storage technologies such as EVs and integrates them within a newly designed hybrid cascaded controller embedded in the LFC loop of a symmetrical two-area power grid. The proposed scheme combines a fractional order proportional integral derivative (FOPID) controller with a tilt fractional order integral derivative (TFOID) in a cascaded configuration. The combined CC FOPID-TFOID controller is optimally tuned using the golden jackal optimization (GJO) algorithm, while the integral time square error (ITSE) serves as the performance metric. Improved dynamic performance under stochastic RES behavior and multiple load perturbations demonstrates the effectiveness of the proposed controller in maintaining frequency regulation. Furthermore, the robustness of the proposed controller is verified under communication delays, system parameter variations and varying renewable penetration levels, without re-optimization of the controller gains. The supremacy of the GJO-based cascaded CC FOPID-TFOID controller is further validated through statistical analysis, Bode-based stability assessment and computational complexity evaluation.