Particle swarm optimization Backstepping controller for a grid-connected PV/wind hybrid system

被引：0

作者：

Bechouat M. ^{[1
]}

Sedraoui M. ^{[1
]}

Soufi Y. ^{[2
]}

Yousfi L. ^{[3
]}

Borni A. ^{[4
]}

Kahla S. ^{[1
]}

机构：

[1] Laboratoire des télécommunications, Université 8 Mai 1945, Guelma

[2] Labget laboratory, Department of Electrical Engineering, University of Tebessa

[3] University of Tebessa, Algeria Laboratory Inverses Problems: Modeling, Information and Systems (PI:MIS)

[4] Unité de Recherche Appliquée en Energies Renouvelables, URAER, Centre de Développement Des Energies Renouvelables, CDER, Ghardaïa

来源：

Journal of Engineering Science and Technology Review | 2017年 / 10卷 / 01期

关键词：

Backstepping controller; Matlab/simulink; MPPT; PSO; PV/wind grid-connected;

D O I：

10.25103/jestr.101.13

中图分类号：

学科分类号：

摘要：

The current paper investigates Backstepping controller using Particle Swarm Optimization for Photovoltaic "PV"/Wind hybrid system. The tested system was connected to the grid by three-phase inverter commissioned to address current depending on the grid parameters and still deliver its reactive power to zero. Backstepping control is a recursive methodology that uses Lyapunov function which can ensure the system stability. The best selection of Lyapunov function gains values should give a good result. In most of the literatures, the choice was based on the expertise of the studied system using hurwitzienne method considered as heuristic choice. The aim of this work is to propose an optimization using a powerful method commonly called Particle Swarm Optimization "PSO" able to calculate the gains values depending on the grid parameters by minimizing a selected criterion. The simulation results show that the PSO Backstepping controller gives good results shown in the current injected to grid with a small harmonic distortion despite climate change in the wind speed and the irradiation, which also shows the robustness of the applied control. © 2017 Eastern Macedonia and Thrace Institute of Technology.

引用

页码：91 / 99

页数：8

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