Conference paper
Using forecast information for storm ride-through control
Department of Wind Energy, Technical University of Denmark1
Wind Energy Systems, Department of Wind Energy, Technical University of Denmark2
Department of Applied Mathematics and Computer Science, Technical University of Denmark3
Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark4
Meteorology, Department of Wind Energy, Technical University of Denmark5
Using probabilistic forecast information in control algorithms can improve the performance of wind farms during periods of extreme winds. This work presents a wind farm supervisor control concept that uses probabilistic forecast information to ride-through a storm with softer ramps of power. Wind speed forecasts are generated with a statistical approach (i.e. time series models).
The supervisor control is based on a set of logical rules that consider point forecasts and predictive densities to ramp-down the power of the wind farm before the storm hits. The potential of this supervisor control is illustrated with data from the Horns Rev 1 wind farm, located in the North Sea. To conclude, an overview of ongoing and future research in the Radar@Sea experiment is given.
This experiment aims at improving offshore wind power predictability and controllability through the increased use of meteorological information, and particularly weather radar images.
Language: | English |
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Publisher: | European Wind Energy Association (EWEA) |
Year: | 2013 |
Pages: | 1359-1367 |
Proceedings: | European Wind Energy Conference & Exhibition 2013 |
ISBN: | 1632663147 and 9781632663146 |
Types: | Conference paper |
ORCIDs: | Pinson, Pierre , Giebel, Gregor and Cutululis, Nicolaos Antonio |