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Wind direction modelling using multiple observation points.

Yoshito Hirata1, Danilo P Mandic, Hideyuki Suzuki

  • 1Department of Mathematical Informatics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan. yoshito@sat.t.u-tokyo.ac.jp

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|August 19, 2007
PubMed
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Improved wind direction forecasting using a novel nonlinear model enhances wind turbine efficiency. This approach integrates data from an extra measurement point and both wind speed and direction for better predictions.

Area of Science:

  • Renewable Energy Engineering
  • Atmospheric Science
  • Computational Fluid Dynamics

Background:

  • Accurate wind direction prediction is crucial for efficient wind turbine operation.
  • Wind's intermittent, non-Gaussian, and nonlinear behavior complicates forecasting.
  • Coupling between wind speed and direction adds complexity to prediction models.

Purpose of the Study:

  • To develop an improved wind direction forecasting model.
  • To enhance prediction accuracy by incorporating augmented data and vector components.
  • To demonstrate the practical benefits of improved wind forecasts for power generation.

Main Methods:

  • Proposed a nonlinear forecasting model.
  • Augmented the model with data from an additional measurement point.

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  • Utilized both wind speed and direction components of the wind field vector.

    • Main Results:

    • The proposed model demonstrated superior prediction performance compared to standard and persistent models.
    • Simulations confirmed the enhanced prediction accuracy of the novel approach.
    • Even minor forecast improvements led to significant increases in generated power output.

    Conclusions:

    • The developed nonlinear model offers a significant advancement in wind direction forecasting.
    • Integrating augmented data and vector components effectively addresses forecasting complexities.
    • The approach provides a viable pathway to substantially increase wind energy production efficiency.