WITHDRAWN: Powering the Future: Wind Power Forecasts for Solano, California

• Author(s): Tamara Greasby and Prabir Bruman
• Keywords: Wind Power ; Forecasting ; Non-Parametric ; Semi-Parametric ; Link Function

Abstract

Alternative energy sources have become increasingly important. The drawback to these sources is they do not provide consistent amounts of power. For successful power grid management, utility companies need accurate power production forecasts at a variety of horizons. Wind power depends primarily on wind speed and to a lesser extent on wind direction, barometric pressure, and temperature. We explored parametric, semi-parametric, non-parametric, and combination models to create forecasts. Due to natural restrictions on power values we consider a link function that relates the response, power, to its predictors. These models were fit to data collected every ten minutes during all seasons. Forecasts were created every ten minutes for horizons between ten minutes and six hours. The results of these model fits will be discussed along with confidence bounds.