Detection of Wind Turbine Power Performance Abnormalities Using Eigenvalue Analysis

Georgios Alexandros Skrimpas, Christian Walsted Sweeney, Kun Marhadi, Bogi Bech Jensen, Nenad Mijatovic, and Joachim Holbøll
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Full Paper
phmc_14_073.pdf1.08 MBAugust 14, 2014 - 10:19pm

Power performance analysis is a method applicable to wind turbines for the detection of power generation changes due to external factors, such as icing, internal factors, such as controller malfunction, or deliberate actions, such as power de-rating. In this paper, power performance analysis is performed by sliding a time-power window and calculating the two eigenvalues corresponding to the two dimensional wind speed - power distribution. An important aspect of the proposed technique is its independence of the ideal power curve. It is shown that by detecting any changes of the two eigenvalues , power generation anomalies are consistently identified.

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Submission Keywords: 
fault diagnosis; Wind turbines ; Pattern recognition
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
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