Development of a Novel Power Curve Monitoring Method for Wind Turbines and Its Field Tests

被引:64
|
作者
Park, Joon-Young [1 ]
Lee, Jae-Kyung [1 ]
Oh, Ki-Yong [2 ]
Lee, Jun-Shin [1 ]
机构
[1] Korea Elect Power Corp, KEPCO Res Inst, Future Technol Lab, Taejon 305380, South Korea
[2] Univ Michigan, Dept Mech Engn, Ann Arbor, MI 48109 USA
关键词
Alarm generation; condition monitoring; fault data queue; power curve; turbine monitoring; wind turbine;
D O I
10.1109/TEC.2013.2294893
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
A novel power curve monitoring method for wind turbines was developed to prevent a turbine failure in a wind farm. Compared with the existing methods, this algorithm automatically calculates the power curve limits for power curve monitoring, even when a considerable number of abnormal data are included in wind speed-output power data measured at a wind turbine. In addition, the proposed algorithm automatically generates an alarm message when the wind speed-power data measured at the wind turbine deviate from the power curve limits, particularly considering their degree of deviation from the power curve limits and the cases when the measured data hover between the Warning Zones and the Alarm Zones. We confirmed its effectiveness through its field tests.
引用
收藏
页码:119 / 128
页数:10
相关论文
共 50 条
  • [11] A novel power curve prediction method for horizontal-axis wind turbines using artificial neural networks
    Tai V.C.
    Tan Y.C.
    Rahman N.F.A.
    Chia C.M.
    Zhakiya M.
    Saw L.H.
    Energy Engineering: Journal of the Association of Energy Engineering, 2021, 118 (03): : 507 - 516
  • [12] Power Curve Modelling of a Wind Turbine for monitoring its behaviour
    de Andrade Vieira, Rodrigo J.
    Sanz-Bobi, Miguel A.
    2015 INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY RESEARCH AND APPLICATIONS (ICRERA), 2015, : 1052 - 1057
  • [13] Characterisation of the power curve for wind turbines by stochastic modelling
    Anahua, E.
    Barth, S.
    Peinke, J.
    WIND ENERGY, 2007, : 173 - +
  • [14] An Algorithm for Practical Power Curve Estimation of Wind Turbines
    Javadi, Milad
    Malyscheff, Alexander M.
    Wu, Di
    Kang, Chongqing
    Jiang, John N.
    CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2018, 4 (01): : 93 - 102
  • [15] A Normal Behavior Model Based on Power Curve and Stacked Regressions for Condition Monitoring of Wind Turbines
    Bilendo, Francisco
    Badihi, Hamed
    Lu, Ningyun
    Cambron, Philippe
    Jiang, Bin
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
  • [16] Novel on-field method for pitch error correction in wind turbines
    Elosegui, Unai
    Ulazia, Alain
    PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON APPLIED ENERGY, 2017, 142 : 9 - 16
  • [17] A Novel Condition Monitoring Method of Wind Turbines Based on GMDH Neural Network
    Tian, Xiange
    Jiang, Yongjian
    Liang, Chen
    Liu, Cong
    Ying, You
    Wang, Hua
    Zhang, Dahai
    Qian, Peng
    ENERGIES, 2022, 15 (18)
  • [18] Power curve modelling of wind turbines- A comparison study
    Al-Quraan, Ayman
    Al-Masri, Hussein
    Al-Mahmodi, Mohammed
    Radaideh, Ashraf
    IET RENEWABLE POWER GENERATION, 2022, 16 (02) : 362 - 374
  • [19] Abnormal State Analysis of Wind Turbines Based on the Power Curve
    Yuan, Li
    Huang Qiujuan
    Yi, Yang
    Xing Zuoxia
    2018 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON), 2018, : 4135 - 4142
  • [20] Ice detection on wind turbines using the observed power curve
    Davis, Neil N.
    Byrkjedal, Oyvind
    Hahmann, Andrea N.
    Clausen, Niels-Erik
    Zagar, Mark
    WIND ENERGY, 2016, 19 (06) : 999 - 1010