Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 62, Issue 10, Pages 6627-6635Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2015.2447508
Keywords
Multivariate approach; performance monitoring; power curve; residual analysis; wind energy
Categories
Funding
- Research Grants Council of the Hong Kong Special Administrative Region [CityU 138313]
- National Natural Science Foundation of China [71001050]
Ask authors/readers for more resources
This paper investigates the wind turbine power generation performance monitoring based on supervisory control and data acquisition (SCADA) data. The proposed approach identifies turbines with weakened power generation performance through assessing the wind power curve profiles. Profiles that statistically summarize the curvatures and shapes of a wind power curve over consecutive time intervals are constructed by fitting power curve models into SCADA data sets with a least square method. To monitor the variations of wind power curve profiles over time, multivariate and residual approaches are introduced and applied. Two blind industrial studies are conducted to validate the effectiveness of the proposed monitoring approach, and the results demonstrate high accuracy in detecting the abnormal power curve profiles of wind turbines and their associated time intervals.
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