Novel fuzzy-assisted nonlinear optimal power generation method for grid-connected SPV system with TLBO optimisation

摘要

This research article presents a novel fuzzy-assisted nonlinear proportional-integral (f-NPI) controller based optimal power generation method for a 100 kW grid-connected solar photovoltaic (SPV) system with boost converter topology. The primary objective is to optimise power generation when variations in irradiance and temperature are experienced. f-PI and novel f-NPI based PV array reference current predictor is implemented to adjust the duty cycle for the converter. The gain parameters of controllers are being fairly tuned using teaching-learning based optimisation (TLBO) technique. A comprehensive simulation analysis is carried out using MATLAB R2017a, which verifies that the utilisation of primitive parameters, i.e., irradiance and temperature for the proposed controller exhibits enhanced performance in comparison to extant P&O and fuzzy logic controller (using secondary/conventional parameters like voltage and current) in terms of settling time, efficiency and THD. Moreover, the operation of the novel f-NPI based method is found to comply with IEEE 929 standard.