Metaheuristic Based Stability Enhancement of Hybrid Energy System

The quality of the power is a critical concern for grids that are interconnected with various energy sources nowadays. In order to meet the necessary power consumption, hybrid renewable energy sources are essential. There may occasionally be greater power and frequency fluctuations when there is constant electricity generation because of an increase in power demand. The efficient control of solar photovoltaic (PV) systems is essential for maximizing energy production and maintaining system stability. This paper presents an automatic tuning approach for proportional-integral (PI) controllers in solar PV systems using Artificial Bee Colony Optimization (ABCO) implemented in MATLAB/Simulink. The study demonstrates that the ABCO-based tuning method significantly improves the performance of the PI controller, resulting in enhanced tracking accuracy and reduced system oscillations. The findings of this research offer a promising solution to enhance the control of solar PV systems, contributing to their increased efficiency and reliability. In this research work the proposed model of solar PV system implemented on the hybrid energy system of wind, diesel and grid for controlling the fluctuation and fulfilling the load demand across the consumer side.