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International Journal for Engineering Modelling, Vol. 34 No. 2 Regular Issue, 2021.

Original scientific paper

https://doi.org/10.31534/engmod.2021.2.ri.05d

Comparative Study of P&O and Fuzzy MPPT Controllers and Their Optimization Using PSO and GA to Improve Wind Energy System

Abdelhalim Borni ; Unité de Recherche Appliquée en Energies Renouvelables, URAER, Centre de Développement des Energies Renouvelables, CDER, 47133, Ghardaïa, ALGERIA
Mohcene Bechouat ; Faculty of Science and Technology, University of Ghardaïa, ALGERIA
Noureddine Bessous ; Department of Electrical Engineering University of El Oued, Fac. Technology, El-Oued 39000, ALGERIA
Abdelhak Bouchakour ; Unité de Recherche Appliquée en Energies Renouvelables, URAER, Centre de Développement des Energies Renouvelables, CDER, 47133, Ghardaïa, ALGERIA
Zarour Laid ; Department of Electrical Engineering, Laboratory of Electrical, Constantine (LEC), Brother Mentoury University, ALGERIA
Layachi Zaghba ; Unité de Recherche Appliquée en Energies Renouvelables, URAER, Centre de Développement des Energies Renouvelables, CDER, 47133, Ghardaïa, ALGERIA

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Abstract

Many academics have recently focused on wind energy installations. WECS (wind energy conversion system) is a renewable energy source that has seen significant development in recent years. Furthermore, compared to the use of power grid supply, the use of the WECS in the water pumping field is a cost-free option (economically). The purpose of this study is to demonstrate a wind-powered pumping mechanism. To obtain the best option, it considers and contrasts four distinct approaches. This research aims to improve the system's performance and the quality of the generated power. The objective of the control of WECS with a permanent magnet synchronous generator (PMSG) is to carefully maximize power generation. Finally, this research employed the fuzzy logic control (FLC) and particle swarm optimization (PSO) algorithms improved using a genetic algorithm (GA). The proposed system's performance was tested using the generated output voltage, current, and power waveforms, as well as the intermediate circuit voltage waveform and generator speed. The provided data show that the control technique used in this study was effective.

Keywords

Wind energy; Fuzzy logic control; Maximum power point tracking (MPPT); Genetic algorithm (GA); Perturb and observe (P&O); Particle swarm optimization (PSO)

Hrčak ID:

265070

URI

https://hrcak.srce.hr/265070

Publication date:

25.11.2021.

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