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Developing an optimization algorithm with independent algorithm-specific parameters is crucial in tuning the controller parameters of Automatic Generation Control (AGC). In 2020, Rao developed a robust and newly proposed algorithm independent of algorithm-specific parameters with faster convergence and less computational complexities. This paper presents the AGC of a sample two-area interconnected multi-source power systems with fractional-order PID controllers optimized using the Rao algorithm. The objective function selected for tuning the optimal gain of the controller using the Rao algorithm is based on Integral Squared Error (ISE). The robustness of the Rao algorithm for parameter variations and load changes is compared with other metaheuristic algorithms such as Genetic Algorithm (GA), Grey Wolf Optimization (GWO), and Particle Swarm Optimization (PSO). The efficacy of the proposed tuning method for AGC application is validated using the dSPACE 1103 hardware-in-loop simulation.

Frequency Regulation on an Interconnected Power System With Fractional PID Controllers Optimized Using Rao Algorithms