Abstract
This paper introduces a hybrid fuzzy logic control-based proportional-integral (FLC-PI) control strategy designed to enhance voltage stability, power quality, and overall performance of central inverters in photovoltaic power plants (PVPPs). The study is based on a real-world PVPP with an installed capacity of 26.136 MWp, connected to the Egyptian national grid at Fares City, Kom Ombo Centre, Aswan Governorate. A user-friendly MATLAB/SIMULINK environment is developed, incorporating eleven distinct blocks along with a modelled national utility grid, utilizing actual operational data from the PVPP. To optimize the FLC-PI control scheme, several artificial intelligence (AI)-based metaheuristic optimization techniques (MOTs) are employed to simultaneously tune all control parameters-namely Grey Wolf Optimization (GWO), Harris Hawks Optimization (HHO), and the Arithmetic Optimization Algorithm (AOA)-are employed. These techniques are used to simultaneously fine-tune all the gain parameters of FLC-PI control, based on four standard error-based objective functions: Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Absolute Error (ITAE), and Integral Time Square Error (ITSE). The optimized gains are applied to both voltage and current regulators of the central inverters, enabling the identification of optimal values. Among the tested methods, the HHO algorithm combined with the ISE objective function delivered the best performance, achieving a total harmonic distortion (THD) of 3.88%-well below the IEEE 519-2014 limit of 5.00%. The results confirm that the proposed FLC-PI controller significantly enhances the integration of high-penetration PVPPs into the utility grid by reducing power losses and inverter-induced harmonics, especially during maximum power point tracking (MPPT). Moreover, employing MOTs for controller tuning proves to be an effective solution for adapting to dynamic solar irradiance conditions. Ultimately, the optimized FLC-PI control approach enhances voltage stability, improves power quality, and boosts the overall efficiency of grid-connected PV systems.