A new fractional-order cascade controller structure for frequency regulation of interconnected renewable-dominant power systems

Abstract Ensuring reliable frequency regulation in contemporary multi-area interconnected power systems has become increasingly demanding due to changes in consumption patterns, the massive integration of intermittent renewable energy sources (RESs), the integration of distributed energy resources, reductions in power system inertia, and the rising complexity of network interconnections. Although conventional proportional-integral-derivative (PID) controllers continue to serve as a standard solution for load frequency control (LFC), their fixed-structure design and limited adaptability restrict their effectiveness in coping with rapid fluctuations, nonlinear dynamics, and parametric uncertainties characteristic of renewable-dominated grids. To address these challenges, this work proposes a new fractional-order cascaded controller, which combines fractional-order PID (FOPID) and one plus tilt fractional-order integral derivative (1 + TFOID), namely FOPID-(1 + TFOID). Moreover, a recently developed population-based metaheuristic technique, known as the Stellar Oscillation Optimizer (SOO), is employed to determine the optimal parameter set of the proposed cascaded controller, marking its first implementation within the LFC framework. To systematically evaluate its effectiveness, the performance of SOO is benchmarked against four well-established optimization approaches, namely Golden Jackal Optimization (GJO), the Crayfish Optimization Algorithm (COA), the Artificial Hummingbird Algorithm (AHA), and the Grey Wolf Optimizer (GWO). The proposed controller is evaluated in a two-area interconnected power system incorporating photovoltaic and wind generation under single and successive load disturbances, renewable generation variations, and ± 50% variations in key power-system parameters, and practical governor dead-band (GDB) and generation rate constraint (GRC) nonlinearities. Simulation results show that the proposed cascaded controller is superior to four recently proposed controllers based on recent optimization algorithms, achieving significant reductions in the Integral of Time Absolute Error (ITAE), frequency deviations, and tie-line power deviations. Moreover, the proposed controller demonstrated its robustness under significant changes in power system parameters. Furthermore, the proposed SOO demonstrated its superiority in the LFC application for tuning the proposed controller over the other four algorithms.