Sliding control with fuzzy type-2 controller of wind energy system based on doubly fed induction generator

被引:0
作者
Zouggar E.O. [1 ,2 ]
Chaouch S. [1 ]
Abdeslam D.O. [3 ]
Abdelhamid A.L. [1 ]
机构
[1] Laboratory of Electromagnetic Induction and Propulsion Systems
[2] IRIMAS Laboratory, Haute Alsace University, 61 Rue Albert Camus, Mulhouse
来源
Instrumentation Mesure Metrologie | 2019年 / 18卷 / 02期
关键词
DFIG; Powers regulation- sliding mode control- type-2 fuzzy logic control- robust control; Wind turbine- modeling;
D O I
10.18280/i2m.180207
中图分类号
学科分类号
摘要
The wind system based on double-fed induction generator (DFIG) has become a very important source of energy. To ensure the proper functioning of this system, many improved control algorithms have been developed for the rotor side converter (RSC). This article presents the analysis and design of a double-fed induction generator (DFIG) control technique based on coupling the type-2 fuzzy logic control with the sliding mode control (SMC). For the design of this technique, a decoupled modeling of the DFIG with the orientation of its stator flow is presented. The main purpose of the proposed technique is to make a control to meter the quantities of the powers produced by DFIG which are injected into the electrical network and to reduce the phenomenon of chattering which depends on control by sliding mode. This command has allowed us to reduce the chattering phenomenon and improve the performance of the system in terms of speed monitoring and stator side powers regulation. Simulations are performed using MATLAB / Simulink to validate the effectiveness of the proposed control algorithm. The simulation results, obtained when applying this control strategy to the system, demonstrated the validity of the results and thus validated the high performance of this control technique. © 2019 Lavoisier. All rights reserved.
引用
收藏
页码:137 / 146
页数:9
相关论文
共 35 条
[1]  
Blaabjerg F., Teodorescu R., Liserre M., Timbus A., Overview of control and grid synchronization for distributed power generation systems, IEEE Transactions on Industrial Electronics, 53, 5, pp. 1398-1409, (2006)
[2]  
Abad G., Lopez J., Rodriguez M., Marroyo L., Iwanski G., Doubly Fed Induction Machine, (2011)
[3]  
Errouissi R., Durra A.A., Muyeen S.M., Leng S., Blaabjerg F., Offset-free direct power control of DFIG under continuous-time model predictive control, IEEE Transactions on Power Electronics, 32, 3, pp. 2265-2277, (2017)
[4]  
Zavadil R., Miller N., Ellis A., Muljadi E., Making connections: Wind generation challenges and progress, IEEE Power and Energy Magazine, 3, 6, pp. 26-37, (2005)
[5]  
Xiong L., Wang J., Mi X., Khan M.W., Fractional order sliding mode based direct power control of grid-connected DFI, IEEE Transactions on Power Systems, 33, 3, pp. 3087-3096, (2018)
[6]  
Belounis O., Labar H., Fuzzy sliding mode controller of DFIG for wind energy conversion, International Journal of Intelligent Engineering and Systems, 10, 2, pp. 163-172, (2017)
[7]  
Krishnama R.S., Pillai G.N., Design and implementation of type-2 fuzzy logic controller for DFIG-based wind energy systems in distribution networks, IEEE Transactions on Sustainable Energy, 7, 1, pp. 345-353, (2016)
[8]  
Djafar D., Belhamdi S., Golea A., Speed control of induction motor with broken bars using sliding mode control (SMC) based to on type-2 fuzzy logic controller (T2FLC), AMSE Journals Advances C, 73, 4, pp. 197-201, (2018)
[9]  
Mendel J.M., Rajati M.R., On computing normalized interval type-2 fuzzy sets, IEEE Transactions on Fuzzy Systems, 22, 5, pp. 1335-1340, (2014)
[10]  
Mendel J.M., General type-2 fuzzy logic systems made simple: A tutorial, IEEE Transactions on Fuzzy Systems, 22, 5, pp. 1162-1182, (2014)