Improving wind turbine power curve monitoring with standardisation. (January 2020)

• Record Type: Journal Article
• Authors: Helbing, Georg; Ritter, Matthias
• Is Part Of: Renewable energy. Volume 145(2020)
• Page Start: 1040
• Page End: 1048
• Publication Date: 2020-01
• Subjects: Power curve monitoring -- Control charts -- Wind energy; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2019.06.112
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: Against the background of increasing cost pressure, condition monitoring is becoming increasingly relevant to the wind energy industry. The present study examines the role of wind turbulence and the non-constant variance of residuals in power curve monitoring. Power curve monitoring methods are classified and compared by means of Monte Carlo simulations. It is found that adjusting for the non-constant variance of residuals using standardisation may considerably improve the performance of control charts, no matter what method is used to generate them. Additionally, turbulence is found to be an important factor, and including it may further increase the performance of control charts. Highlights: Standardising power curve residuals may improve the performance of control charts. The standard deviation of wind speed over 10 min intervals is an important factor. Monte Carlo simulation performs well at predicting aggregated power output. Local linear regression performs well at estimating residual variance.