
Fuzzy and predictive control of a photovoltaic pumping system based on three-level boost converter
Author(s) -
Zakaria Massaq,
Abdelouahed Abounada,
Mohamed Ramzi
Publication year - 2021
Publication title -
bulletin of electrical engineering and informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.251
H-Index - 12
ISSN - 2302-9285
DOI - 10.11591/eei.v10i3.2605
Subject(s) - control theory (sociology) , maximum power point tracking , photovoltaic system , duty cycle , boost converter , controller (irrigation) , maximum power principle , model predictive control , engineering , matlab , capacitor , inverter , voltage , computer science , control (management) , electrical engineering , artificial intelligence , biology , agronomy , operating system
In this work, an efficient control scheme for a double stage pumping system is proposed. On the DC side, a three-level boost converter is employed to maximize the photovoltaic power and to step-up the DC-link voltage. For maximum power point tracking, the classical incremental conductance method is substituted by a fuzzy logic controller. The designed controller estimates the optimal step size which speeds up the tracking process and improves the accuracy of the extracted photovoltaic power. Afterwards, the voltages across the three-level boost converter (TLBC) capacitors are balanced by phase shifting the applied duty ratios. On the motor pump side, a two-level inverter drives the motor pump with the cascaded nonlinear predictive control. The predictive controller is preferred over the conventional field-oriented control because it accelerates the torque response and resists to the change of the engine parameters. The designed controllers are evaluated using MATLAB/Simulink, and compared with the conventional controllers (incremental conductance algorithm and field-oriented control). The robust control scheme of the entire system has increased the hydraulic power by up to 23% during the system start-up and up to 10% in steady state.