NDLI: SCADA-based wind turbine anomaly detection using Gaussian process models for wind turbine condition monitoring purposes

Content Provider	IET Digital Library
Author	Pandit, Ravi Kumar Infield, David
Abstract	The penetration of wind energy into power systems is steadily increasing; this highlights the importance of operations and maintenance, and specifically the role of condition monitoring. Wind turbine power curves based on supervisory control and data acquisition data provide a cost-effective approach to wind turbine health monitoring. This study proposes a Gaussian process (a non-parametric machine learning approach) based algorithm for condition monitoring. The standard IEC binned power curve together with individual bin probability distributions can be used to identify operational anomalies. The IEC approach can also be modified to create a form of real-time power curve. Both of these approaches will be compared with a Gaussian process model to assess both speed and accuracy of anomaly detection. Significant yaw misalignment, reflecting a yaw control error or fault, results in a loss of power. Such a fault is quite common and early detection is important to prevent loss of power generation. Yaw control error provides a useful case study to demonstrate the effectiveness of the proposed algorithms and allows the advantages and limitations of the proposed methods to be determined.
Starting Page	1249
Ending Page	1255
Page Count	7
ISSN	17521416
Volume Number	12
e-ISSN	17521424
Issue Number	Issue 11, Aug (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/12/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2018.0156
Journal	IET Renewable Power Generation
Publisher Date	2018-05-31
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Aerodynamics Condition Monitoring Control Engineering Computing Control of Electric Power System Control Technology And Theory Data Acquisition System Data Acquisition System For Control Energy ReSource Fluid Mechanics Gaussian Process Model Gaussian Processes IEC Approach Individual Bin Probability Distribution Knowledge Engineering Technique Learning in AI Loss-of-power Maintenance And Reliability Mechanical Engineering Nonparametric Machine Learning Approach Operational Anomalies Other Engineering Application of IT Power And Plant Engineering Power Engineering Computing Power System Power System Analysis Computing Power System Control Power System Economics Power System Managemen Power System Operation Power System Protection Power System Security Real-time Power Curve SCADA System Statistical Distribution Statistics Supervisory Control-and-data Acquisition-based Wind Turbine Anomaly Detection The Standard IEC Binned Power Curve Wind Energy Penetration Wind Power Wind Power Plant Wind Turbine Wind Turbine Condition Monitoring Purposes Wind Turbine Health Monitoring Wind Turbine Power Curves Yaw Control Error Yaw Fault Yaw Misalignment
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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