Design of High–performance Fuzzy–Predictive Controllers for a Photovoltaic/Battery Pumping System

Zakaria Massaq

Abstract


In this paper, three cascaded fuzzy–predictive controllers are designed to control a photovoltaic/battery pumping system. For maximum power point tracking (MPPT), the outer loop consists of a fuzzy controller that provides the reference current corresponding to the maximum power. The inner loop regulates the photovoltaic current with a predictive controller based on pulse width modulation (PWM). Meanwhile, another fuzzy–predictive controller drives the bidirectional converter to manage the power flow between the different stages of the system. The third fuzzy–predictive controller consists of the duty ratio control (DRC) of the induction motor, in which a fuzzy estimator provides the switching vector (SV) to be applied to the inverter during the ON time (TON). Afterwards, a predictive controller calculates the optimal OFF time (TOFF) for which a zero voltage will be applied. The proposed controllers are compared by simulation to three different control strategies presented in the literature. The system was subjected to different irradiances and speeds to test its performance under different environmental and load conditions. It turns out that the proposed MPPT algorithm provides the best tracking speed during system start-up and helps to reduce the PV power ripples. In addition, the battery current ripples are reduced, and the DC link voltage is regulated with zero overshoot and better accuracy. The proposed DRC is the best in terms of reducing torque and flux ripples and it tracks the reference speed with high accuracy. In addition, it can protect the motor from overcurrent.


Keywords


Hybrid pumping system; Fuzzy–predictive control; Current ripples reduction; MPPT; Torque ripples reduction.

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v13i1.13587.g8702

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