Artificial Intelligent Maximum Power Point Controller based Hybrid Photovoltaic/Battery System

Abstract

Photovoltaic (PV) cells have non-linear properties influenced by environmental factors, including irradiation and temperature. As a result, a method known as maximum power point tracking (MPPT) was implemented to boost the PV cells' efficiency and make the most of the energy they could provide. The traditional perturb and observe (P&O) approach for determining the maximum power point tracking (MPPT) has various drawbacks, including poor steady-state performance, increased oscillation around the MPP point, and delayed reaction. As a result, this work aims to present a hybrid fuzzy logic (FL) and P&O MPPT approach to improve the PV system's performance coupled to the lithium battery storage system. Matlab/Simulink is used to bring the suggested technique to life, after which its efficacy is evaluated in the context of rapid changes in the irradiance level. According to the findings of the simulations, the suggested strategy has the potential to enhance the steady-state performance of PV systems in terms of oscillation and time response. Finally, the proposed results are compared with that obtained by the conventional P&O technique, and the stress of PV power is limited to ∆P=1kW and the overshoot power is limited to 5%.