Robust Hybrid MPPT Controller for PV Pumping System

Abstract

This article suggests a maximum power point tracking (MPPT) method for a photovoltaic (PV) pumping system based on a nonlinear robust method combining the backstepping and the sliding mode techniques, which is referred to us as the BSMC controller. The system’s power circuit comprises of a solar panel, a step-up converter and a DC motor feeds a water pump. Two loops are in the control system: the first, provides the reference voltage, that is given by intelligent method based on artificial neural network (ANN), according with the maximum power point (MPP), to the BSMC in the second loop that regulates the PV array voltage in MPP and allows the converter to produce the required power to set the motor at the maximum speed. This is done through adjustment of the DC-DC boost converter duty ratio. The system is, on one side, able to predict the desired optimal voltage quickly by using the ANN, and also to prevent unnecessary calculation and research of the MPP. On the other side, the sliding mode and the backstepping controllers are used to provide good performance and robustness against rapid changes in the insolation and temperature. Also, the system’s asymptotic stability is proven by lyapunov’s functions. The proposed approach is compared to the method, P&O, IC and the hybrid technique ANN-integral sliding mode controller. Simulation results depict the proposed regulator effectiveness and robustness in relation to rapidly irradiance and temperature changes, using Maltab/Simulink.