Two-area load frequency control with redox ow battery using intelligent algorithms in a restructured scenario


Abstract: Load frequency control (LFC) is an essential aspect of power system dynamics. This paper focuses on the optimization of LFC for a two-area deregulated power system under different scenarios. A recent nature-inspired ower pollination algorithm (FPA), based on the pollination process of plants, is used to tune the proportional integral (PI) controller parameters of LFC for the global minima solution. FPA is compared with a genetic algorithm, particle swarm optimization, and a conventional PI controller. During large load disturbance in the areas, controllers are incapable of reducing frequency deviations and tie-line power oscillations due to the slow response of the speed governor mechanism. Hence, to improve the dynamic response of the LFC, redox ow batteries (RFBs) are added to both areas due to their quick response and lower time constant. The simulation results show the effectiveness of the RFBs and FPA, especially in terms of overshoots, undershoots, and settling time, thereby improving the performance of LFC in the deregulated power system. The simulation was carried out on the MATLAB/Simulink platform.

Keywords: Flower pollination algorithm, genetic algorithm, load frequency control, particle swarm optimization, redox ow battery

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