Damping inter-area modes of oscillation using an adaptive fuzzy power system stabilizer

被引:65
作者
Hussein, T. [1 ]
Saad, M. S. [1 ]
Elshafei, A. L. [1 ]
Bahgat, A. [1 ]
机构
[1] Cairo Univ, Elect Power & Machines Dept, Giza, Egypt
关键词
Fuzzy logic system; Fuzzy identification; Feedback linearization; Variable-structure algorithm; Swarm optimization technique; DESIGN; IDENTIFICATION; LOGIC;
D O I
10.1016/j.epsr.2010.06.004
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
This paper introduces an indirect adaptive fuzzy controller as a power system stabilizer used to damp inter-area modes of oscillation following disturbances in power systems. Compared to the IEEE standard multi-band power system stabilizer (MB-PSS). indirect adaptive fuzzy-based stabilizers are more efficient because they can cope with oscillations at different operating points. A nominal model of the power system is identified on-line using a variable structure identifier. A feedback linearization-based control law is implemented using the identified model. The gains of the controller are tuned via a particle swarm optimization routine to ensure system stability and minimum sum of the squares of the speed deviations. A bench-mark problem of a 4-machine 2-area power system is used to demonstrate the performance of the proposed controller and to show its superiority over other conventional stabilizers used in the literature. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:1428 / 1436
页数:9
相关论文
共 20 条
[1]  
[Anonymous], 1999, IEEE INT C INTELL SY
[2]  
[Anonymous], 1992, NONLINEAR SYSTEMS
[3]  
[Anonymous], 2016, IEEE std 421.5-2016
[4]  
Astrom K.J., 1995, ADAPTIVE CONTROL
[5]   Power system stabilizers as undergraduate control design projects [J].
Chow, JH ;
Boukarim, GE ;
Murdoch, A .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2004, 19 (01) :144-151
[6]   Optimal tuning of power systems stabilizers and AVR gains using particle swarm optimization [J].
El-Zonkoly, A. M. .
EXPERT SYSTEMS WITH APPLICATIONS, 2006, 31 (03) :551-557
[7]   Variable-structure-based fuzzy-logic identification of a class of nonlinear systems [J].
Elshafei, AL ;
Karray, F .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2005, 13 (04) :646-653
[8]   A variable-structure adaptive fuzzy-logic stabilizer for single and multi-machine power systems [J].
Elshafei, AL ;
El-Metwally, KA ;
Shaltout, AA .
CONTROL ENGINEERING PRACTICE, 2005, 13 (04) :413-423
[9]   Adaptive fuzzy control of nonlinear systems via a variable-structure algorithm [J].
Elshafei, AL .
PROCEEDINGS OF THE 2002 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL, 2002, :620-625
[10]   Hybrid adaptive fuzzy identification and control of nonlinear systems [J].
Hojati, M ;
Gazor, S .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2002, 10 (02) :198-210