Study of Wind Farm Power Output Predicting Model Based on Nonlinear Time Series

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 670-671)
• Pages: 1526-1529
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.670-671.1526
• Online since: October 2014
• Authors: Yun Teng*, Zhi Yao An, Xin Yu, Zhen Hao Wang, Yong Gang Zhang
• Keywords: Double ANNs, Nonlinear Time Series, Power Prediction, Wind Power

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