Title :
WEC condition monitoring based on SCADA data analysis
Author_Institution :
Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
Condition Monitoring (CM) can greatly reduce the maintenance cost for a Wind Energy Converter (WEC). In this paper, history data of Supervisory Control and Data Acquisition (SCADA) system is analyzed to detect the incipient failure of WEC generator bearing. A new condition monitoring method based on the Nonlinear State Estimate Technique (NSET) is proposed. NSET is used to construct the normal behavior model of the generator bearing temperature. When the generator bearing has an incipient failure, the residuals between NSET model estimates and the measured generator bearing temperature will become significant. When the residual exceeds the predefined thresholds, an incipient failure is flagged. Analysis of a manual drift added on the historical SCADA data for a WEC generator bearing demonstrates the effectiveness of this new condition monitoring method.
Keywords :
SCADA systems; condition monitoring; data analysis; electric generators; power convertors; power generation reliability; state estimation; wind power plants; SCADA data analysis; WEC condition monitoring; WEC generator bearing failure; generator bearing temperature; maintenance cost; nonlinear state estimation technique; supervisory control and data acquisition; wind energy converter; Condition monitoring; Generators; Predictive models; Temperature measurement; Vectors; Wind speed; Wind turbines; Condition monitoring; Nonlinear State Estimate Technique (NSET); Residual analysis; SCADA data; WEC generator bearing;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
