Journal
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 4, Issue 1, Pages 192-199Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2012.2212470
Keywords
Control chart; kappa-means clustering; Mahalanobis distance; performance monitoring; turbine performance curves
Categories
Funding
- Iowa Energy Center [07-01]
Ask authors/readers for more resources
Three different operational curves-the power curve, rotor curve, and blade pitch curve-are presented for monitoring a wind farm's performance. A five-year historical data set has been assembled for constructing the reference curves of wind power, rotor speed, and blade pitch angle, with wind speed as an input variable. A multivariate outlier detection approach based on kappa-means clustering and Mahalanobis distance is applied to this data to produce a data set for modeling turbines. Kurtosis and skewness of bivariate data are used as metrics to assess the performance of the wind turbines. Performance monitoring of wind turbines is accomplished with the Hotelling T-2 control chart.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available