Very Short-Term Wind Speed Prediction of a Wind Farm Based on Artificial Neural Network

Abstract:

Wind speed prediction is critical for wind energy conversion system since it not only can relieve or avoid the disadvantageous impact on power system, but also can enhance the competitive ability of wind power plants against others in electricity markets. The model presented in this paper was based on artificial neural network (ANN) and the selection of the model parameters was presented in detail. The autocorrelation function (ACF) of wind speed time series was used to determine the input variables of the neural network. The simulation was carried out with the proposed ANN model.The conclusion that the optimal network structure may be different corresponding to different error evaluation was drawn through a large number of simulation experiments. And the simulaiton results showed that the ANN model is less than 10.77% in terms of root mean square error and 5.86% in terms of mean absolute error compared with the persistence model.

• Periodical: Advanced Materials Research (Volumes 608-609)
• Pages: 677-682
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.608-609.677
• Online since: December 2012
• Authors: Rui Ma, Shu Ju Hu, Hong Hua Xu
• Keywords: Artificial Neural Network (ANN), Very Short-Term Prediction, Wind Farm, Wind Speed Prediction

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