Adaptive linear prediction for optimal control of wind turbines

被引:24
|
作者
Narayana, Mahinsasa [1 ]
Sunderland, Keith M. [2 ]
Putrus, Ghanim [3 ]
Conlon, Michael F. [2 ]
机构
[1] Univ Moratuwa, Moratuwa, Sri Lanka
[2] Dublin Inst Technol, Dublin, Ireland
[3] Northumbria Univ, Newcastle Upon Tyne, Tyne & Wear, England
关键词
Wind energy conversion systems; Wind turbine; Linear adaptive prediction; Power mapping technique; Wind speed sensor technique; Wind speed estimation; ENERGY-CONVERSION SYSTEMS; NEURAL-NETWORKS; SPEED; ALGORITHMS;
D O I
10.1016/j.renene.2017.06.041
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In order to obtain maximum power output of a Wind Energy Conversion System (WECS), the rotor speed needs to be optimised for a particular wind speed. However, due to inherent inertia, the rotor of a WECS cannot react instantaneously according to wind speed variations. As a consequence, the performance of the system and consequently the wind energy conversion capability of the rotor are negatively affected. This study considers the use of a time series Adaptive Linear Prediction (ALP) technique as a means to improve the performance and conversion efficiency of wind turbines. The ALP technique is introduced as a real time control reference to improve optimal control of wind turbines. In this study, a wind turbine emulator is developed to evaluate the performance of the predictive control strategy. In this regard, the ALP reference control method was applied as a means to control the torque/speed of the emulator. The results show that the employment of a predictive technique increases energy yield by almost 5%. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:895 / 906
页数:12
相关论文
共 50 条
  • [1] Wind direction prediction for yaw control of wind turbines
    Dongran Song
    Jian Yang
    Yao Liu
    Mei Su
    Anfeng Liu
    Young Hoon Joo
    [J]. International Journal of Control, Automation and Systems, 2017, 15 : 1720 - 1728
  • [2] Wind Direction Prediction for Yaw Control of Wind Turbines
    Song, Dongran
    Yang, Jian
    Liu, Yao
    Su, Mei
    Liu, Anfeng
    Joo, Young Hoon
    [J]. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2017, 15 (04) : 1720 - 1728
  • [3] Optimal Power Sharing Control of Wind Turbines
    Li, Yujun
    Xu, Zhao
    Meng, Ke
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (01) : 824 - 825
  • [4] Adaptive Variable Speed Control of Wind Turbines
    Wang, W. N.
    Li, R. M.
    Song, Y. D.
    Hu, Y. S.
    Zhang, X. K.
    [J]. ADVANCED MATERIALS AND PROCESSES, PTS 1-3, 2011, 311-313 : 2393 - +
  • [5] Adaptive H∞ Control of Large Wind Turbines
    Bobanac, Vedran
    Vasak, Mario
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT), 2015, : 85 - 92
  • [6] Adaptive Feed Forward Control for Wind Turbines
    Schlipf, David
    Cheng, Po Wen
    [J]. AT-AUTOMATISIERUNGSTECHNIK, 2013, 61 (05) : 329 - 338
  • [7] LINEAR STABILITY CONTROL OF OFFSHORE WIND TURBINES
    Mecklenborg, Christine A.
    Rouenhoff, Philipp
    Chen, Dongmei
    [J]. PROCEEDINGS OF THE ASME DYNAMIC SYSTEMS AND CONTROL CONFERENCE 2010, VOL 2, 2010, : 903 - 910
  • [8] Adaptive backstepping control of variable speed wind turbines
    Ozbay, U.
    Zergeroglu, E.
    Sivrioglu, S.
    [J]. INTERNATIONAL JOURNAL OF CONTROL, 2008, 81 (06) : 910 - 919
  • [9] Adaptive Pitch Control for Load Mitigation of Wind Turbines
    Yuan, Yuan
    Tang, J.
    [J]. SENSORS AND SMART STRUCTURES TECHNOLOGIES FOR CIVIL, MECHANICAL, AND AEROSPACE SYSTEMS 2015, 2015, 9435
  • [10] Adaptive tower damping control for offshore wind turbines
    Pascu, Valentin
    Kanev, Stoyan
    van Wingerden, Jan-Willem
    [J]. WIND ENERGY, 2017, 20 (05) : 765 - 781