About X-WiWa

Left to right: Mark Kelly, Jianting Du, Merete Badger, Xiaoli G. Larsén, Rodolfo Bolaños, Andrea Hahmann, Sara Jackson, Patrick Volker, Jacob Tornfeldt Sørensen.

Team members
: Xiaoli G. Larsén, Rodolfo Bolaños, Jianting Du, Mark C. Kelly, Jake Badger, Merete Badger, Andrea N. Hahmann, Henrik Kofoed-Hansen, Jacob T. Sørensen, Sara Jackson, Ioanna Karagali, Patrick Volker, Søren Ejling Larsen, Marc Imberger, Ole Svenstrup Petersen, Alastair Jenkins, Angus Graham, Joakim Refslund Nielsen.


The Danish government has declared a long term vision for Denmark to be free of fossil fuels. The government has defined the goal of having half of the Danish electricity consumption covered by renewable energy in 2025, essentially through wind energy. Building a large number of small wind farms offshore, especially in coastal zones (within 20 km of the coast), is seen as an effective solution to reach this Danish governmental goal (Ref.
Kystnære 2012). 

X-WiWa deals with a chain of issues related to wind turbine design and wind power operations in offshore and coastal areas during storms. Currently, the forecast of offshore wind up to the hub height during storms is inaccurate (Larsén and Badger, 2012). To a great extent, this is due to the misrepresentation of the surface conditions determined by the underlying waves. At the same time, the prediction of very high waves suffers from inaccurate wind forcing (e.g. Cavaleri 2009). Roughly speaking, a 10% error in the wind speed results in 15% error in the wave height and 30% error in the wave loads on the marine structures. Errors in the prediction of strong winds and waves bring considerable risks to the secure operation systems and maintenance of offshore wind farms. With more accurate prediction of strong winds to guide turbine operation, the chances of turbine damage can be greatly reduced. With the daily cost of a service vessel on the order of one million DKK, great savings can be achieved if more reliable weather is predicted, to allow 10% more efficient operations.  Equally important, high uncertainty is inherent in the estimation of extreme winds and waves, which needs to be known for turbine and substructure design. Estimates indicate that tens of millions of DKK can be saved per substructure if the estimation of the design extreme wave height is 1 m lower and millions of DKK can be saved if the extreme wind is classified in the correct category.

This project, X-WiWa, aims at improving the forecast of wind and waves during storm conditions for the Danish coastal zones. X-WiWa has the potential to reduce the number of failures by providing design parameters through better estimation of the extreme wind (conventionally called the 50-year return wind) and waves. It also allows the establishment of a more accurate operation and maintenance plans for specific regions, thus reducing associated costs.