Quasi-oppositional JAYA optimized 2-degree-of-freedom PID controller for load-frequency control of interconnected power systems. (2nd January 2022)

• Record Type: Journal Article
• Authors: Guha, Dipayan; Roy, Provas Kumar; Banerjee, Subrata
• Is Part Of: International journal of modelling & simulation. Volume 42:Number 1(2022)
• Page Start: 63
• Page End: 85
• Publication Date: 2022-01-02
• Subjects: Load-frequency control -- JAYA algorithm -- quasi-oppositional based learning -- 2DOF-PID controller -- teaching-learning based optimization -- competitive algorithms; Mathematical models -- Periodicals; Simulation methods -- Periodicals; Mathematical models; Simulation methods; Periodicals; 003.3
• DOI: 10.1080/02286203.2020.1829444
• Languages: English
• ISSNs: 0228-6203

Abstract

ABSTRACT: 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.