Several laboratories are involved in developing wind forecasting programs and their accuracy has been improving. Collaborative work by the California Energy Commission and the US Electric Power Research Institute (EPRI) is now ongoing to improve wind forecasting, using modelling techniques developed in Denmark and the US, reports EPRI. In parallel, Denmark's Risø Laboratory is designing a model that takes into account not only the high level winds which drive weather systems, but also local winds, together with site-specific obstacles and types of terrain.
Consumer demand for electricity rises with increasing winds, especially at low temperatures when the chill factor comes into play. Thus wind forecasts have always been important to utilities for scheduling generation to match demand. In areas of large concentrations of wind plant, such as in Denmark and northern Germany, these forecasts are today already used to predict the availability of wind energy on utility systems. But the power output from any given wind farm is influenced by local topographical effects and the old forecasting methods lack accuracy.
In California, a forecasting model for a single wind plant is being developed and tested through comparisons with observed wind generation during a one month period. Three parallel forecasting systems are to undergo longer term testing at four sites in different regions. In the final phase of the project, one of these models will be further developed with intentions of commercial use, states EPRI. The work is likely to continue until 2002, and it will be carried out by an impressive international consortium, which includes the Risø lab.
In Denmark, the computer program under development by Risø also takes into account wind farm geometry and the power curves of the machines installed. On-line predictions have been made available to the two Danish utilities and have proved valuable in predicting rapid increases in wind power generation that occur with the onset of storms. Risø's current research project gives more weight to low level winds, and the accuracy of the forecasting has increased.