Enhanced FOPID controller for AGC of two-area power system using a Modified Chernobyl Disaster Optimizer

Abstract

Abstract Ensuring frequency stability in interconnected power systems is challenging due to continuous load variations and fluctuations in tie-line power. This study focuses on designing and optimizing controllers for Automatic Generation Control (AGC) of a two-area power system to achieve zero-frequency deviation under dynamic load conditions. Five different controllers—PID (Proportional-Integral-Derivative), PIDn, FOPID (Fractional Order PID), TID (Tilt-Integral-Derivative), and PIDA—were tested. Their parameters were optimized using seven advanced metaheuristic algorithms: Artificial Rabbit Optimization, Chernobyl Disaster Optimizer (CDO), Modified Chernobyl Disaster Optimizer (mCDO), Golden Jackal Optimization, Honey Badger Algorithm, Mont-Flame Optimization, and Spider Wasp Optimizer. A total of 35 simulation studies were conducted, and performance was evaluated using the Integral of Time-Weighted Absolute Error (ITAE) metric Among the tested controllers, the FOPID-mCDO combination achieved the lowest ITAE value (0.320684), a settling time of 3.6 s, and minimal overshoot (0.0083 Hz) and undershoot (− 0.1480 Hz). Compared to conventional PID controllers, this configuration reduced settling time by 10% and improved frequency stability under dynamic load variations. The proposed mCDO algorithm, which integrates neighborhood–global and wandering search strategies to enhance the exploration–exploitation balance of the original CDO, outperformed the standard CDO by enabling faster convergence and more precise parameter tuning. The findings indicate that the FOPID-mCDO combination is a promising approach for automatic generation control in multi-area power systems.