Characterization of Daily Wind Farm Power Fluctuations Using Wavelet Transform

被引：1
|
作者：
Chu, Xiaodong [1 ]
Zhang, Wen [1 ,2 ]
Nwachukwu, Tochi [2 ]
Hiskens, Ian A. [2 ]
机构：
[1] Shandong Univ, Sch Elect Engn, Jinan, Peoples R China
[2] Univ Wisconsin, Dept Elect & Comp Engn, Madison, WI USA
来源：
ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 4, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/ICNC.2008.133
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With the increase of wind power installed capacities, the cost of integration is large due to the intermittent nature of wind energy. To accommodate wind farm power fluctuations, additional control measures are required. Accurate characterization of the fluctuations paves the way for optimal control design. In identifying localized characteristics of the signal, wavelet transform provides a suitable tool. Data gathered at a wind farm of New Mexico are studied with its daily output variations characterized using wavelet transform.
引用
收藏
页码：481 / +
页数：2
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