Wind speed forecast model for wind farm based on a hybrid machine learning algorithm

• Main Authors: Haque, AU, Mandal, P, Meng, J, Michael Negnevitsky
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: 2015
• Subjects: Electrical energy generation (incl. renewables; excl. photovoltaics); fuzzy ARTMAP network; machine learning algorithm; short-term wind speed forecasting; wavelet transform; Canada; North Cape
• Online Access: https://figshare.com/articles/journal_contribution/Wind_speed_forecast_model_for_wind_farm_based_on_a_hybrid_machine_learning_algorithm/22906970

This paper presents a newstrategy for wind speed forecasting based on a hybrid machine learning algorithm, composed of a data filtering technique based on wavelet transform (WT) and a soft computing model based on the fuzzy ARTMAP (FA) network. The prediction capability of the proposed hybrid WT + FA model is demonstrated by an extensive comparison with some other existing wind speed forecasting methods. The results show a significant improvement in forecasting error through the application of a proposed hybrid WT + FA model. The proposed wind speed forecasting strategy is applied to real data acquired from the North Cape wind farm located in PEI, Canada.