A Moth–Flame Optimization for UPFC–RFB-Based Load Frequency Stabilization of a Realistic Power System with Various Nonlinearities

In this article, a realistic multi-area multi-source test power system model is investigated by imposing the effects of nonlinearities for the betterment of automatic generation control (AGC) realization. The confined area of presented work is to cogitate the effectiveness of combined unified power flow controller (UPFC) and redox flow battery (RFB) in view of damping of oscillations subjected to increased load perturbation. The investigated power system model is a six-area system having reheat thermal, hydro and gas-generating units lumped together in each control area. The present prospect analyzes a very realistic approach of AGC by adding physical constraints like time delay, governor dead band, boiler dynamics, reheat turbine and generation rate constraint to the aforesaid system. A nature-inspired novel moth–flame optimization (MFO) algorithm is employed as an optimization tool in the design of proportional–integral–derivative gains and the tunable parameters of UPFC and RFBs. The substantial point of discussion is the guaranteed convergence mobility as the moths in this algorithm update their positions with respect to the flames which represent the most promising solutions. The MFO-based results are compared with genetic algorithm-based method to show the superiority of MFO over other similar metaheuristic optimization techniques. Robustness of the designed controller is also studied over ± 25% uncertainties in parametric values and under loaded condition. The simulation works showed that the inclusion of UPFC and RFB is very much effective in load frequency stabilization and is quite robust for a realistic power system.