The environmental value of wind power can be increased by knowing the spinning reserve requirements. The reserve requirements are a function of the accuracy of the wind power prediction, but also the variability of the weather, which is typically generated on the mesoscale. By not only predicting the most likely production of the wind farm, but also the expected variability, the reserve requirements can be adjusted up and down in advance.
A deterministic high resolution numerical weather prediction system gives one result and no information about the expected uncertainty at a given time. An ensemble of forecasts can be used to generate a probability density function of the most likely outcome.
The variability of the wind farm output within one hour is however not well understood nor predicted by todays ensemble prediction systems, because they predict a wind speed which is averaged over an area much larger than the physical extend of offshore wind farms such as the Hornsrev wind farm.
The spatial and time resolution of the ensemble output needs to be increased to achieve a good estimate of the reserve requirements and a better air sea interaction scheme is required to simulate the planetary boundary layer eddies and the atmospheric flow under non-neutral conditions.
The project will focus on improving the wind power prediction and the mesoscale generated variability on the wind farm power output with special focus on the offshore wind farm Horns Rev. This will be done by developing different parameterizations and using them in a high resolution coupled atmospheric and ocean model. They will be tested in the model against measurements of waves and wind speed.