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Very short-term wind speed forecasting with Bayesian structural break model

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  • Jiang, Yu
  • Song, Zhe
  • Kusiak, Andrew

Abstract

This paper examines a new time series method for very short-term wind speed forecasting. The time series forecasting model is based on Bayesian theory and structural break modeling, which could incorporate domain knowledge about wind speed as a prior. Besides this Bayesian structural break model predicts wind speed as a set of possible values, which is different from classical time series model's single-value prediction This set of predicted values could be used for various applications, such as wind turbine predictive control, wind power scheduling. The proposed model is tested with actual wind speed data collected from utility-scale wind turbines.

Suggested Citation

  • Jiang, Yu & Song, Zhe & Kusiak, Andrew, 2013. "Very short-term wind speed forecasting with Bayesian structural break model," Renewable Energy, Elsevier, vol. 50(C), pages 637-647.
    • Handle: RePEc:eee:renene:v:50:y:2013:i:c:p:637-647
    DOI: 10.1016/j.renene.2012.07.041
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