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Study of wind farm power output predicting model based on nonlinear time series

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4 Author(s)
Teng Yun ; Liaoning Province Key Lab. of Power Grid Safe Oper. & Monitoring, Shenyang Univ. of Technol., Shenyang, China ; Xu Jianyuan ; Zhang Mingli ; Wang Liang

To solve the problem of the wind power variancy when wind farm connect with the power grid, a wind power output predicting model based on nonlinear time series 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 influence greatly on it. Values of these five circumstance conditions can be treated as a nonlinear time series and be analyzed by 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.

Published in:

Electrical Machines and Systems (ICEMS), 2011 International Conference on

Date of Conference:

20-23 Aug. 2011