Rapidly Updated Forecasts for Wind Energy Production

The RapidWind project works to improve wind forecasting for the Norwegian wind energy industry where rapid delivery of short-range forecasts is important. The project works to prepare an operational weather forecast model for updating with observation s with higher frequency in time than before, through a process calles "data assimilation". This so-called Rapid Update Cycling will use 3 hour updating invervals or even more frequent updates. The aim is to improve the forecasted wind intensity, and the timing of wind events, and for this the project has focussed on assimilation of radar radial wind observations from the Norwegian weather radar network. Implementation of a first version of radar data assimilation in the operational weather predi ction model of MET Norway (the so called AROME-Norway 2.5 km model) has been completed with 3 hours assimilation cycling.

For the wind power industry, it is essential to have as precise as possible wind forecasts. Point forecasts of wind intensities is important, but even more so, the exact timing of wind events. The producers face a decision making problem under uncertainty where a large difference between contracted and produced energy leads to significant balancing cost for the producer. The necessary regulation power is typically more expensive than bulk power. More precise and better forecasts would reduce the differen ce between contracted and produced energy and reduce the uncertainty when making production plans. More rapid forecast updates would enable the producers to more efficiently handle the difference in the continuous Elbas market. In order to give precise w eather forecasts at the meso-scale, it is crucial to have an initial state of the weather model that is as close as possible to the corresponding true atmospheric state. This is done by data assimilation utilizing various observations at given intervals, typically every six hours in operational models. As the model resolution increases, and the model updates (cycling) are performed more frequently, observations of high temporal frequency and high spatial resolution is important. This project focusses on the use of novel observation types, and use of rapid update cycling of the model state, aiming at more precise timing of forecasted weather events, with main focus on wind. This includes the use of radial wind measurements from weather radars, which are available at high observation frequency and of very high resolution, the use of 10 m wind observations from synop stations, the use of scatterometer data from satellites and preparation of the next generation weather model for rapid update cycling. Also , focus will be put on distribution methods for the new model output, to let the industry utilize the results without unnecessary delay.