Wind Speed Forecasting Based on Variable Weight Combination Model of Neural Network and Grey Model

Abstract:

The wind speed forecasting accuracy of artificial neural network(ANN) and grey model(GM) is poorly satisfied. Thus, we proposed a new variable weight combined (VWC) model, which was based on the ANN and GM, to improve the wind speed forecasting accuracy. VWC used weighting coefficient of different time to fit the two single models. The forecasting accuracy of VWC is higher than either of the two single models, and is also higher than the unchanged weight combination(UWC) model. Our data show a new method for wind speed forecasting and the reduction of auxiliary service costs of wind farms.

• Periodical: Applied Mechanics and Materials (Volumes 217-219)
• Pages: 2654-2657
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.217-219.2654
• Online since: November 2012
• Authors: Jian Zhang, Lun Nong Tan
• Keywords: Combination Forecasting Model, Grey Model (GM), Neural Network (NN), Variable Weight

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