Wind Power Density Forecasting Using Wind Ensemble Predictions and Time Series Models

Taylor, James, McSharry, Patrick and Buizza, Roberto (2009) Wind Power Density Forecasting Using Wind Ensemble Predictions and Time Series Models. IEEE Transactions on Energy Conversion, 24 (3). pp. 775-782.

Abstract

Wind power is an increasingly used form of renewable energy. The uncertainty in wind generation is very large due to the inherent variability in wind speed, and this needs to be understood by operators of power systems and wind farms. To assist with the management of this risk, this paper investigates methods for predicting the probability density function of generated wind power from one to ten days ahead at five U.K. wind farm locations. These density forecasts provide a description of the expected future value and the associated uncertainty. We construct density forecasts from weather ensemble predictions, which are a relatively new type of weather forecast generated from atmospheric models. We also consider density forecasting from statistical time series models. The best results for wind power density prediction and point forecasting were produced by an approach that involves calibration and smoothing of the ensemble-based wind power density.

Item Type: Article
Keywords: Density forecasting; weather ensemble predictions; wind power
Subject(s): Management science
Date Deposited: 24 Jan 2012 19:47
Last Modified: 10 Feb 2017 16:43
URI: http://eureka.sbs.ox.ac.uk/id/eprint/1706

Actions (login required)

Edit View Edit View