Incorporating Geostrophic Wind Information for Improved Space-Time Short-Term Wind Speed Forecasting and Power System Dispatch

• Activity Number: 14
• Type: Topic Contributed
• Date/Time: Sunday, August 3, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Marc G. Genton*+ and Kenneth Bowman and Xinxin Zhu
• Companies: King Abdullah University of Science and Technology and TAMU and Texas A&M
• Keywords: Geostrophic wind ; Space-time statistical model ; Wind energy ; Wind speed forecasting

Abstract

Accurate short-term wind speed forecasting is needed for the rapid development and efficient operation of wind energy resources. This is, however, a very challenging problem. We propose to incorporate the geostrophic wind as a new predictor in an advanced space-time statistical forecasting model, the trigonometric direction diurnal (TDD) model. The geostrophic wind captures the physical relationship between wind and pressure through the observed approximate balance between the pressure gradient force and the Coriolis acceleration due to the Earth's rotation. Based on our numerical experiments with data from West Texas, our new method produces more accurate forecasts than does the TDD model using air pressure and temperature for 1- to 6-hour-ahead forecasts based on three different evaluation criteria. For example, our new method obtains between 13.9% and 22.4% overall mean absolute error improvement relative to persistence in 2-hour-ahead forecasts, and between 5.3% and 8.2% improvement relative to the best previous space-time methods in this setting. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified.