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An effort is given in this paper, for the first time, to discuss the load-frequency control (LFC) problem of an interconnected power system by implementing a novel heuristic optimization method called quasi-oppositional-based JAYA (QOJAYA). The proposed algorithm houses the knowledge of quasi-oppositional-based learning to enhance convergence speed and find the best solutions to the LFC problem. To show the effectiveness, the proposed QOJAYA scheme is, individually, applied to a two-area multi-unit multi-source power plant and a three-area hydrothermal power plant considering the system nonlinearities. The structural simplicity and performance adequacy of the well-known proportional-integral (PI) controller enforces to optimally design it as a secondary controller at the first instant. Afterward, the dynamic stability of the concerned power systems is increased with a 2DOF-PID controller. The proposed algorithm is employed to search the optimal settings of the said controllers by minimizing the time-based single-valued fitness functions. Simulation results validate the success of the proposed QOJAYA scheme and demonstrate its dominance over original JAYA, teaching-learning-based optimization (TLBO), and other recently introduced optimization techniques in the state-of-the-art for the same power system. Finally, the robustness of the designed controller is established by performing sensitivity analysis considering parameters and loading uncertainties.

Quasi-oppositional JAYA optimized 2-degree-of-freedom PID controller for load-frequency control of interconnected power systems