DocumentCode :
2099753
Title :
Notice of Retraction
A Novel Power Predicting Model of Wind Farm Based on Double ANNs
Author :
Lin Xin ; Li Bin ; Xu Jianyuan ; Teng Yun
Author_Institution :
Sch. of Electr. Eng., Shenyang Univ. of Technol., Shenyang, China
fYear :
2010
fDate :
28-31 March 2010
Firstpage :
1
Lastpage :
4
Abstract :
Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

To solve the problem of the variancy of the wind power when wind farm connect with the power grid, a wind power predicting model of wind farm based on double ANNs is proposed in the paper. Wind velocity and wind direction on wind farm are the key of wind power predicting, and other circumstance conditions such as temperature, humidity, atmospheric pressure, are also great influence on it. The observed values of these five circumstance conditions can be treated as a nonlinear time series and be analyzed by the nonlinear time series ANNs model. The wind power predicting model consists of double artificial neural networks. The first is consisted of five artificial neural networks which is used to prediction the circumstance conditions time series, the second is employed to prediction the power of wind farm use predicting value of the five conditions. A series of simulation show that the results of the predicting model is acceptable in engineering application.
Keywords :
neural nets; power engineering computing; power grids; wind power; double artificial neural networks; nonlinear time series; power grid; power predicting model; wind direction; wind farm; wind velocity; Artificial neural networks; Atmospheric modeling; Humidity; Power grids; Predictive models; Temperature; Wind energy; Wind farms; Wind forecasting; Wind speed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Type :
conf
DOI :
10.1109/APPEEC.2010.5448680
Filename :
5448680
Link To Document :
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