AI-based voltage and power quality control of high-penetration grid-connected photovoltaic power plant

The importance of using renewable energy systems (RESs) worldwide has been consolidated. Moreover, connecting more RESs to the utility grid will lead technical problems. Photovoltaic (PV) and wind turbine (WT) based power plants are most nonlinear sources energies contributing mix Electronic ballast switching mode supply in conservation PV WT have caused quality problems less reliable output voltage. becoming increasingly integrated with by onboarding certain superior features. This integration drastically reduces use fossil fuels prevents environmental hazards. article presents design a 26 MWp grid-connected plant, which is already tied Egyptian electrical network Fares City, Kom Ombo Center, Aswan Governorate, Egypt plant consists (11) blocks grid, simulated Matlab/Simulink. Every block contains 2,376 kWp arrays connected directly DC-DC boost converters regulate DC generated each array. fed into particular type inverter called “central inverter”, converts it AC power. In some cases, higher harmonic distortion at greater negative impact on system performance occur when this inverter. To optimize gains proportional-integral (PI) controller for both voltage current regulators central inverter, meta-heuristic optimization techniques (MOTs) used. During article, Gray Wolf Optimization (GWO), Harris Hawks (HHO), Arithmetic Algorithm (AOA) applied as MOTs enhance addition limiting total distortions (THD) under effect different sunlight conditions partial shading. As result, AOA-based controllers found show outstanding results compared GWO HHO regarding solution computational efficiency. Finally, best controlling high-penetration systems, such grid.