Performance analysis of dual-mode PI controller using quasi-oppositional whale optimization algorithm for load frequency control

Abstract

In this work, a novel optimization technique named quasi-oppositional whale optimization algorithm (QOWOA) is employed for the LFC problem. In this study to improve the convergence speed, accuracy, and reliability of WOA, WOA is integrated with quasi-oppositional–based learning theory and applied first time for the LFC problem. To show the efficacy of the QOWOA technique, at first, it is applied to an interconnected two-area system with governor dead band nonlinearity then expanded to a realistic three-area hybrid power system, and another system with two-area four-unit hydro-thermal system is considered. Proportional-integral and dual-mode PI controllers are considered as secondary controller for system analysis. The optimization supremacy of the QOWOA technique is validated contrasting the outcomes with original WOA, moth flame optimization algorithm, other recent competitive algorithms, and fuzzy PI controller for an identical system. Robustness of the projected approach is tested with random load perturbation at area-1 and step load perturbation at diverse location at diverse instant that establishes the efficacy of QOWOA. The critical system analysis demonstrates that the proposed QOWOA technique may be effectively applied for the LFC problem.