Control chart monitoring of wind turbine generators using the statistical inertia of a wind farm average

A method for monitoring wind turbine generators (WTG) using data provided by the SCADA system is proposed. This method relies mainly upon comparing one WTG with the average of all remaining WTGs on a wind farm. Because environmental conditions on a wind farm are roughly the same over its entirety, the difference between each WTG and the average of the remaining WTGs on the wind farm is constant over time. The statistical inertia of averaged conditions for the entire farm provides a good yardstick for WTG monitoring. The results of monitoring four aspects of a WTG are presented here: these are electrical energy produced; tower vibration; nacelle yaw; and gearbox temperature. Control charts are used to detect abnormal behaviour. With regard to the electrical energy produced, one accidental activation of a curtailment algorithm was found. For tower vibration, we describe an application for the detection of rotor imbalance. For yaw, an example showing detection of nacelle drift is covered. Lastly, for gearbox temperature, the proposed methodology succeeded in detecting an issue two months prior to failure. We have included limitations as to the minimum wind farm size required in order to use the wind farm average. A centralized control chart is also proposed.

[1]  Steven X. Ding,et al.  A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches , 2015, IEEE Transactions on Industrial Electronics.

[2]  Andrew Kusiak,et al.  The prediction and diagnosis of wind turbine faults , 2011 .

[3]  Steven X. Ding,et al.  A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part II: Fault Diagnosis With Knowledge-Based and Hybrid/Active Approaches , 2015, IEEE Transactions on Industrial Electronics.

[4]  Paul Fleming,et al.  Use of SCADA Data for Failure Detection in Wind Turbines , 2011 .

[5]  Yingning Qiu,et al.  Wind turbine SCADA alarm analysis for improving reliability , 2012 .

[6]  Zhiwei Gao,et al.  Pitch control for wind turbine systems using optimization, estimation and compensation , 2016 .

[7]  Nadège Bouchonneau,et al.  A review of wind turbine bearing condition monitoring: State of the art and challenges , 2016 .

[8]  Jae-Kyung Lee,et al.  Development of a Novel Power Curve Monitoring Method for Wind Turbines and Its Field Tests , 2014, IEEE Transactions on Energy Conversion.

[9]  Mayorkinos Papaelias,et al.  Condition monitoring of wind turbines: Techniques and methods , 2012 .

[10]  Mei-Ling Huang,et al.  Detection of Wind Turbine Faults Using a Data Mining Approach , 2016 .

[11]  Kesheng Wang,et al.  SCADA data based condition monitoring of wind turbines , 2014 .

[12]  Christophe Bérenguer,et al.  Using SCADA Data for Fault Detection in Wind Turbines: Local Internal Model Versus Distance to a Wind Farm Reference , 2014 .

[13]  S. W. Roberts Control chart tests based on geometric moving averages , 2000 .

[14]  Andrew Kusiak,et al.  Analysis of wind turbine vibrations based on SCADA data , 2010 .

[15]  Ming-Hung Shu,et al.  A comparative study of the monitoring performance for weighted control charts , 2009 .

[16]  Jia Xu,et al.  A New Condition Monitoring Method for Wind Turbines Based on Power Curve Model , 2016, AST 2016.

[17]  A Kusiak,et al.  A Data-Driven Approach for Monitoring Blade Pitch Faults in Wind Turbines , 2011, IEEE Transactions on Sustainable Energy.

[18]  Douglas C. Montgomery,et al.  Introduction to Statistical Quality Control , 1986 .

[19]  Iain Staffell,et al.  How does wind farm performance decline with age , 2014 .

[20]  Chengliang Liu,et al.  Wind turbines abnormality detection through analysis of wind farm power curves , 2016 .

[21]  Zhong Guo Bian,et al.  Wind Turbine On-Line Monitoring System Based on Vibration Mechanics , 2012 .

[22]  Peter Tavner,et al.  Wind turbine downtime and its importance for offshore deployment. , 2011 .

[23]  Andrew Kusiak,et al.  On-line monitoring of power curves , 2009 .

[24]  Pablo del Río,et al.  Policies and design elements for the repowering of wind farms: A qualitative analysis of different options , 2011 .

[25]  Antoine Tahan,et al.  Power curve monitoring using weighted moving average control charts , 2016 .

[26]  A. Kusiak,et al.  Monitoring Wind Farms With Performance Curves , 2013, IEEE Transactions on Sustainable Energy.