Small-signal stability analysis of DFIG based wind power system using teaching learning based optimization

被引：27
|
作者：
Chatterjee, Shamik [1 ]
Naithani, Abishek [1 ]
Mukherjee, V. [1 ]
机构：
[1] Indian Sch Mines, Dept Elect Engn, Dhanbad 826004, Jharkhand, India
来源：
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 2016年 / 78卷
关键词：
Doubly fed induction generator; Eigenvalues; Low voltage ride through; Teaching learning based optimization (TLBO); Wind turbine generator; INDUCTION MACHINE; ALGORITHM; PERFORMANCE;
D O I：
10.1016/j.ijepes.2015.11.113
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The present paper formulates the state space modelling of doubly fed induction generator (DFIG) based wind turbine system for the purpose of small-signal stability analysis. The objective of this study is to discuss" the various modes of operation of the DFIG system under different operating conditions such as three phase fault and voltage sags with reference to variable wind speed and grid connection. In the present work, teaching learning based optimization (TLBO) algorithm optimized proportional-integral (PI) controllers are utilized to control the dynamic performance of the modelled DFIG system. For the comparative analysis, TLBO based simulated results are compared to those yielded by particle swarm optimization (PSO) method for the same DFIG model. The simulation results show that the proposed TLBO based PI controller effectively works in minimizing the damping phenomena, oscillation in rotor currents and fluctuation in electromagnetic torque for the studied DFIG model. It is also observed that TLBO is offering better results than the PSO for the dynamic performance analysis of the studied model. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：672 / 689
页数：18
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