MPPT algorithm based on metaheuristic techniques (PSO & GA) dedicated to improve wind energy water pumping system performance

This paper presents a comparative study between four techniques recently used to improve the wind energy conversion system (WECS) to water pumping systems. The WECS is a renewable energy source which has developed rapidly in recent years. The use of the WECS in the water pumping field is a free solution (economically) compared to the use of the electricity grid supply. The control of WECS, equipped with a permanent magnet synchronous generator, has the objective of carefully maximising power generation. A comparative study between the proposed Fuzzy Logic Control, optimised using a genetic algorithm and particle swarm optimisation algorithm, and the conventional Perturb and Observe MPPT method using Matlab/Simulink, is presented. The performance of the proposed system has been verified against the generated output voltage, current and power waveforms, intermediate circuit voltage waveform, and generator speed. The presented results demonstrate the effectiveness of the control strategy applied in this work.

• maximum power point tracking
• wind energy conversion system
• water pumping
• particle swarm optimization
• genetic algorithm
• fuzzy logic control
• permanent magnet synchronous generator
• metaheuristic optimization
• perturb and observe

• 7 — Énergie propre et d’un coût abordable

• Wind Turbine Control Systems
• Photovoltaic System Optimization Techniques
• Power Systems and Renewable Energy
• maximum power point tracking
• wind energy conversion system
• water pumping
• particle swarm optimization
• genetic algorithm
• fuzzy logic control
• permanent magnet synchronous generator
• metaheuristic optimization
• Electrical and Electronic Engineering
• Renewable Energy, Sustainability and the Environment
• Energy Engineering and Power Technology
• Engineering
• Energy