Grey Predictor reference model for assisting particle swarm optimization for wind turbine control

被引:28
作者
Hodzic, Migdat [1 ,2 ]
Tai, Li-Chou [1 ]
机构
[1] Santa Clara Univ, Sch Engn, Santa Clara, CA 95053 USA
[2] IUS, Fac Engn & Nat Sci, Sarajevo, Bosnia & Herceg
关键词
Grey predictor; Performance prediction; Intelligent optimization; Particle swarm optimization; PID controller; Wind turbine control;
D O I
10.1016/j.renene.2015.08.001
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper proposes an approach of forming the average performance by Grey Modeling, and use an average performance as reference model for performing evolutionary computation with error type control performance index. The idea of the approach is to construct the reference model based on the performance of unknown systems when users apply evolutionary computation to fine-tune the control systems with error type performance index. We apply this approach to particle swarm optimization for searching the optimal gains of baseline PI controller of wind turbines operating at the certain set point in Region 3. In the numerical simulation part, the corresponding results demonstrate the effectiveness of Grey Modeling. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:251 / 256
页数:6
相关论文
共 35 条
[1]  
[Anonymous], 2012, hal-00764996
[2]   Annual Wind Speed Estimation Utilizing Constrained Grey Predictor [J].
Atwa, Y. M. ;
El-Saadany, E. F. .
IEEE TRANSACTIONS ON ENERGY CONVERSION, 2009, 24 (02) :548-550
[3]  
Chou Pen Chen, 2005, INT C COMP INT MEAS
[4]  
Clerc M, 1999, P C EV COMP, DOI [10.1109/CEC.1999.785513, DOI 10.1109/CEC.1999.785513]
[5]  
Deng J.L., 1990, THEORY GREY SYSTEM
[6]  
Deng J. L., 1982, Journal of Huazhong Institute of Technology, V3, P9, DOI 10.13245/j. hust.1982.03.002
[7]   CONTROL-PROBLEMS OF GREY SYSTEMS [J].
DENG, JL .
SYSTEMS & CONTROL LETTERS, 1982, 1 (05) :288-294
[8]  
Eberhart R., 2002, MHS95 P 6 INT S MICR, DOI [DOI 10.1109/MHS.1995.494215, 10.1109/MHS.1995.494215]
[9]  
Eberhart R.C., 2010, P C EVOL COMPUT, V1, P84
[10]  
Eberhart R.C., 2001, Swarm Intelligence