A Hierarchical Bias Model for Improvement of 80m Wind Speed Ensemble Forecasts

• Activity Number: 525
• Type: Contributed
• Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Lisa Bramer*+ and Petrutza Caragea and Mark Kaiser
• Companies: Iowa State University and Iowa State University and Iowa State University
• Keywords: wind forecasts ; numerical model output ; ensembles ; bias correction

Abstract

The ability to accurately and precisely forecast wind speeds has become increasingly important as more wind power is introduced into electricity markets. While statistical methods typically predict wind speeds best in the short-term, physical forecast models most often produce medium and long-range forecasts that are necessary for energy trading. Statistical and physical forecast methods can be combined to generate more accurate wind speed forecasts. We generate 54 hour ahead predictions for a location in central Iowa using several ensembles and model the bias of these ensembles using a hierarchical statistical structure. While observed wind speeds at a height of 10 meters are typically used to represent what happens at 80 meters, observed wind speeds at 80 meters are used here to assess the skill of ensembles and bias corrected models.