Dynamic Behavior Analysis for Optimally Tuned On-Grid DFIG Systems

被引：11

作者：

Soued, S. ^{[1
]}

Ramadan, H. S. ^{[1
,2
]}

Becherif, M. ^{[1
]}

机构：

[1] Bourgogne Franche Comte Univ UTBM, CNRS, FR 3539, Femto ST,Dept Energy,FCLab,UMR 6174, Belfort, France

[2] Zagazig Univ, Fac Engn, Elect Power & Machines Dept, Zagazig 44519, Egypt

来源：

EMERGING AND RENEWABLE ENERGY: GENERATION AND AUTOMATION | 2019年 / 162卷

关键词：

Doubly-fed induction generator; Metaheuristic Optimization Techniques; Wind Energy Conversion System; MANAGEMENT;

D O I：

10.1016/j.egypro.2019.04.035

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Metaheuristic Optimization Techniques (MOTs) such as the Artificial Bee Colony (ABC) algorithms and Grey Wolf Optimizer (GWO) can be conveniently used for reaching the Maximum Power Point Tracking (MPPT) of Wind Energy Conversion System (WECS). This paper presents an enhanced control strategy for both Rotor Side Converter (RSC) and Grid Side Converter (GSC) of the Doubly Fed Induction Generator (DFIG)-based WECS using the ABC and the GWO algorithms to ensure the MPPT for the WECS. The control strategy for the RSC and GSC are verified via 9 MW DFIG Wind Turbine (WT) using MATLAB(TM)/ Simulink. The dynamic performance improvement of the DFIG depends on the appropriate choice of the optimal PI controllers' gains. The numerical simulation results show the superiority of the proposed GWO-PI and the ABC-PI optimal controllers over the traditional PI regulators towards enhancing the DFIG system dynamic performance. (C) 2019 The Authors. Published by Elsevier Ltd

引用

页码：339 / 348

页数：10

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