Quasi-oppositional Backtracking Search Algorithm to Solve Load Frequency Control Problem of Interconnected Power System

This study addresses a powerful optimization technique with the notion of quasi-oppositional-based learning, namely quasi-oppositional backtracking search algorithm (QOBSA), for load frequency control (LFC) of power system. Two widely used power systems have been selected to establish the efficiency of QOBSA. Supplementary controllers in LFC are designed by taking frequency and tie-line power deviations of each area as an input, and QOBSA is applied for simultaneous optimization of the controller gains. Integral error-based performance criterions are formulated to claim the tuning optimality of QOBSA. Comparisons are also made with the existing results to establish the superiority of QOBSA in terms of convergence mobility and time response measurements. The effectiveness and competence of the applied method have been confirmed after penetration of renewable energy resources, and in the presence of power system nonlinearities. The robustness of the developed controller has been appraised with system uncertainty and random perturbation.

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