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Hong Liu CanWEA presentation

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Synergizing Two NWP Models to Improve Hub-Height Wind Speed Forecasts

Synergizing Two NWP Models to Improve Hub-Height Wind Speed Forecasts

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  • 1. Synergizing Two NWP Models to Improve Hub-Height Wind Speed Forecasts
    Hong Liu, Ph.D., ORTECH Power
    Peter Taylor, Ph.D., Prof., York University
    CanWEA2010, 26th Annual Conference and Exhibition
    Montreal, Quebec – November 1, 2010
  • 2. Synergizing Two NWP Models to Improve Hub-Height Wind Speed Forecasts
    Drivers
    Methodology
    Evaluation Criteria
    Data Source
    Results
    Discussions
  • 3. ORTECH Power
    An engineering/consulting firm that specialized in getting renewable energy projects completed, from project management to permitting to financial analysis onto commissioning.
    ORTECH helps;
    investors buy Wind Farms
    developers build Wind Farms
  • 4. Drivers
    Two forecast paradigms:
    Statistical
    Physical
    Forecast errors dictated by phase error (Lange, 2003; Liu, 2009 )
    Refined NWP modelling limited by data availability (Giebel, 2003, Yu, et al, 2008, Liu, 2009)
    Ensemble forecasts constrained by computational resources (Cutler, et al, 2008, Mohrlen, 2004)
    Synergizing outputs from more than 1 NWP model as an alternative (Marti, 2006, Nielsen et al, 2007)
  • 5. Methodology (1)
  • 6. Methodology (2)
  • 7. Methodology (3)
  • 8. Methodology (3)
    Relative improvement of combined forecast (Nielsen et al, 2007):
    Weight on the best of two (Nielsen et al, 2007):
  • 9. Methodology (4)
  • 10. Evaluation Criteria
    Root Mean Squared Error (RMSE, Lange,2003)
    Improvement
  • 11. Data Sources (NWPs)
  • 12. Data Sources (Measurements)
    Onshore Met Masts near Great Lakes
    Site1 (80-m)
    Site2 (60-m)
    Site3 (80-m)
    Site4 (60-m)
  • 13. Results (Site1)
  • 14. Results (Site2)
  • 15. Results (Site3)
  • 16. Results (Site4)
  • 17. Results (IP - GEM)
  • 18. Results (IP - NAM)
  • 19. Which forecast is better?
  • 20. Discussions
    Importance of forecast aspects
    Trading
    Unit commitment & scheduling
    O&M
    Next step is to see if this approach could improve the ramp forecasts
  • 21. References
    Cutler, N., Kepert, J. D., Outhred, H. R. and MacGill, I. F., 2008, Characterizing Wind Power Forecast Uncertainty with numerical Weather Prediction Spatial Fields, Wind Engineering, 32, 509-524.
    Giebel, G., 2003, The State-of-the-Art in Short-Term Prediction of wind Power - A Literature Overview, Project ANEMOS, Risø National Laboratory.
    Lange, M., 2003, Analysis of the Uncertainty of Wind Power Predictions, PhD Thesis, University Oldenburg, Oldenburg, Germany.
    Liu, H., 2009, Wind Speed Forecasting for Wind Energy Applications, PhD Thesis, York University, Toronto, Ontario, Canada.
    Marti, I., 2006, Evaluation of Advanced Wind Power Forecasting Models – Results of the Anemos Project, European Wind Energy Conference, Athens, Greek.
    Mohrlen, C., 2004, Uncertainty in wind energy forecasting, PhD Thesis, University College Cork, National University of Ireland.
    Nielsen, H. A., Nielsen, T. S. and Madsen H., 2007, Optimal Combination of wind Power Forecasts, Wind Energy, 10: 471-482
    Yu, W, Plante, A., Chardon, L., Benoit, R., Glazer, A., Tran, L. D., Gauthier, F., Petrucci, F., Forcione, A. and Roberge, G., 2008, A Wind Forecasting System for Application in Wind Power Management – Results from One-year Real-Time Tests in Quebec, CanWEA 2008 Annual Conference, Vancouver, Canada.
  • 22. Synergizing Two NWP Models to Improve Hub-Height Wind Speed Forecasts
    Hong Liu, Ph.D., ORTECH Power
    Peter Taylor, Ph.D., Prof., York University
    Thank you
    CanWEA2010, 26th Annual Conference and Exhibition
    Montreal, Quebec – November 1, 2010