Robust load frequency control in renewable integrated Multi Area grids using hybrid SA and QIO tuned PIDF controller

Frequency stability in renewable-integrated power systems faces critical challenges from load fluctuations, solar/wind intermittency, and nonlinear dynamics. Conventional Proportional-Integral-Derivative (PID) controllers exhibit poor disturbance rejection during concurrent solar irradiance drops and load steps, while optimization algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Neural Network (ANN), and Support Vector Machine (SVM) controllers suffer from premature convergence or computational inefficiency. To address this, we propose a hybrid Simulated Annealing-Quadratic Interpolation Optimizer (hsa-QIO)-tuned filtered PID (PID-F) controller for robust load frequency control in two-area grids with wind, photovoltaic (PV), and thermal generation. The hsa-QIO synergizes global exploration (quadratic interpolation) and probabilistic refinement (simulated annealing), overcoming solution space stagnation. Validated through MATLAB/Simulink simulations under dynamic solar irradiance fluctuations and random load perturbations (0.1-0.4 pu), our approach achieves: 55.7% reduction in Integral Time-weighted Absolute Error (ITAE) versus QIO; 25% lower overshoot (0.9% vs. ANN-PID's 1.2%) and 50% faster settling (0.1 s vs. GA-PID's 0.2 s) in Area 1; superior tie-line regulation (0.3% overshoot/0.4% undershoot vs. SVM's 0.5% and PSO-PID's 0.8%); and statistical robustness with 98.8% lower ITAE deviation (σ = 0.010578) across 30 runs. This computationally efficient solution enables stringent frequency stability (± 0.2 Hz) in high-renewable penetration grids.