Enhanced Ant Lion Optimizer for cascade (1+PI)-PIDF control in hydro-thermal power systems with capacitive storage

Abstract

It is becoming harder to keep the frequency steady in linked power systems since demand is changing in ways that can not be expected, the systems are getting more complicated, and more renewable energy sources are being used. When there are random disturbances and fast changes in load, classic controllers like PI and PID typically do not work as well as they might because of how the system works. This work introduces a cascade (1+PI)-PIDF controller for automated generation control (AGC) in a two-area hydro-thermal power system using capacitive energy storage (CES). The suggested cascade architecture keeps global ACE control independent from local frequency stability. This improves transient responsiveness and steady-state performance compared to standard single-loop controllers. The EALO approach makes global search operate better and stops controller settings from converging too quickly by using random perturbation and adaptive exploration. MATLAB/Simulink examines how effectively the controller operates with step load disturbances by using four objective functions: IAE, ITAE, ISE, and ITSE. The optimization process is done across 30 different trials, each with 50 iterations, to make sure the results are statistically sound. The simulation results show that the suggested cascade controller makes controlling load frequency much better. The suggested technique gets an ITAE value of 0.0068 in the ITAE-based optimization context. The regular PIDF controller gets 0.0643, while the 1+PI controller gets 0.2540. After a step load disruption, the time it takes for the frequency to settle goes from around 14 s to about 3–4 s.