ARTIFICIAL INTELLGENCE MODELLING AND SIMULATION OF HYBRID SOLAR AND WIND ENERGY SYSTEM USING MPPT ALGORITHM

Abstract

Hybrid renewable energy systems, encompassing both solar photovoltaic (PV) and wind power, are of ever-increasing importance for the provision of sustainable and clean electricity. This treatise presents a MATLAB/Simulink-based modelling and simulation of a hybrid solar–wind system, augmented by a battery energy storage system (BESS) and coupled to the electrical grid via a voltage source inverter (VSI). The outputs of the PV and wind installations are conjoined at a common DC bus, whence a closed-loop control regimen ensures the steady injection of AC voltage into the grid. In the first instance, a conventional Proportional–Integral (PI) controller is employed; yet, the simulations evince considerable voltage distortion owing to harmonics under fluctuating generation and load conditions. To remedy this, an Artificial Neural Network (ANN) controller is applied, adaptively modulating inverter switching so as to diminish Total Harmonic Distortion (THD). Comparative scrutiny confirms that the ANN controller enhances power quality, maintains grid conformity, and bolsters system stability, demonstrating its aptness for real-time integration of hybrid renewable systems.