DocumentCode
605062
Title
Harmonic current characteristic analysis for wind turbines
Author
Chuo-Yean Chang ; Shun-Yu Chan ; Jen-Hao Teng ; Rong-Ceng Leou
Author_Institution
Dept. of Electr. Eng., Cheng-Shiu Univ., Kaohsiung, Taiwan
fYear
2013
fDate
22-25 April 2013
Firstpage
919
Lastpage
923
Abstract
This paper analyzes the harmonic current characteristic of wind turbines. Field measurement, data sorting, and analysis are conducted for wind turbine. Most wind turbines at present use a power converter and are equipped with harmonic filters, the control results of these equipments will become highly stochastic as wind speed changes. Even if there is a slight difference in the wind speed, harmonic output of wind turbine will be quite different. If harmonic currents are segmented and the probability density distributions are calculated, then different viewpoints as can be observed. Although harmonic currents of the wind turbine are stochastic, the probability density distributions are close to normal distribution. A stochastic harmonic current predictor is then proposed in this paper based on the probability density distributions of harmonic current. Test results show that the harmonic currents of a wind turbine in long-term operation can be effectively analyzed by the established probability density distributions.
Keywords
harmonic analysis; power convertors; power harmonic filters; statistical distributions; stochastic processes; wind turbines; data sorting; field measurement; harmonic current characteristic analysis; harmonic filters; power converter; probability density distributions; stochastic harmonic current predictor; wind speed; wind turbines; Current measurement; Gaussian distribution; Harmonic analysis; Power harmonic filters; Wind speed; Wind turbines; Harmonic Current Characteristic; Probability Density Distribution; Wind Turbine;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Electronics and Drive Systems (PEDS), 2013 IEEE 10th International Conference on
Conference_Location
Kitakyushu
ISSN
2164-5256
Print_ISBN
978-1-4673-1790-0
Electronic_ISBN
2164-5256
Type
conf
DOI
10.1109/PEDS.2013.6527149
Filename
6527149
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