Abstract
The wind farm output of an offshore-farm such as Horns Rev changes between nearly constant output to highly variable power output. A balance responsible will therefore benefit from knowing the variability of a wind farm in advance. Some understanding of the observed variability and the corresponding forecast error on offshore wind farms had been gathered in the past few years, while a large fraction (about 60%) of the error still lacked understanding and required further intense research. This was the outset at the beginning of the HREnsemble project. Results from the wave study, variability study, ocean coupling, findings from the sensitivity experiments, the iEnKF short-term forecast and finally the demonstration phase have given significant synergy. The most basic research result in the project is that the two empirical mode decomposition approaches, Hilbert-Huang and later the Ensemble Empirical Mode Decomposition (EEMD). Both approaches confirmed that significant variability exists in offshore conditions. It was found that the variability of the short time-scales (24 minutes) are either not explicitly visible in the grid-scale of the NWP models or in the best case significantly smoothed out in all of the tested model configurations. If we interpret 2/3 of the variability due to vertical waves
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Citation Formats
None.
HRensembleHR. High resolution ensemble for Horns Rev. Final project report; Offshore wind power.
Denmark: N. p.,
2010.
Web.
None.
HRensembleHR. High resolution ensemble for Horns Rev. Final project report; Offshore wind power.
Denmark.
None.
2010.
"HRensembleHR. High resolution ensemble for Horns Rev. Final project report; Offshore wind power."
Denmark.
@misc{etde_1000232,
title = {HRensembleHR. High resolution ensemble for Horns Rev. Final project report; Offshore wind power}
author = {None}
abstractNote = {The wind farm output of an offshore-farm such as Horns Rev changes between nearly constant output to highly variable power output. A balance responsible will therefore benefit from knowing the variability of a wind farm in advance. Some understanding of the observed variability and the corresponding forecast error on offshore wind farms had been gathered in the past few years, while a large fraction (about 60%) of the error still lacked understanding and required further intense research. This was the outset at the beginning of the HREnsemble project. Results from the wave study, variability study, ocean coupling, findings from the sensitivity experiments, the iEnKF short-term forecast and finally the demonstration phase have given significant synergy. The most basic research result in the project is that the two empirical mode decomposition approaches, Hilbert-Huang and later the Ensemble Empirical Mode Decomposition (EEMD). Both approaches confirmed that significant variability exists in offshore conditions. It was found that the variability of the short time-scales (24 minutes) are either not explicitly visible in the grid-scale of the NWP models or in the best case significantly smoothed out in all of the tested model configurations. If we interpret 2/3 of the variability due to vertical waves not present in the mean flow and 1/3 of the variability due to meso-scale weather, then the model results and EEMD are consistent. We can however not verify this theory. At present we do not know if EEMD counts neither the events correct nor whether the ensemble forecast suppresses variability. The existence of variability above the time-scale related to friction between ocean waves and air can in fact explain some of the inconsistent results published in the literature and set a question mark behind the correctness of the calculation of friction in wave, ocean and weather modelling. (LN)}
place = {Denmark}
year = {2010}
month = {Mar}
}
title = {HRensembleHR. High resolution ensemble for Horns Rev. Final project report; Offshore wind power}
author = {None}
abstractNote = {The wind farm output of an offshore-farm such as Horns Rev changes between nearly constant output to highly variable power output. A balance responsible will therefore benefit from knowing the variability of a wind farm in advance. Some understanding of the observed variability and the corresponding forecast error on offshore wind farms had been gathered in the past few years, while a large fraction (about 60%) of the error still lacked understanding and required further intense research. This was the outset at the beginning of the HREnsemble project. Results from the wave study, variability study, ocean coupling, findings from the sensitivity experiments, the iEnKF short-term forecast and finally the demonstration phase have given significant synergy. The most basic research result in the project is that the two empirical mode decomposition approaches, Hilbert-Huang and later the Ensemble Empirical Mode Decomposition (EEMD). Both approaches confirmed that significant variability exists in offshore conditions. It was found that the variability of the short time-scales (24 minutes) are either not explicitly visible in the grid-scale of the NWP models or in the best case significantly smoothed out in all of the tested model configurations. If we interpret 2/3 of the variability due to vertical waves not present in the mean flow and 1/3 of the variability due to meso-scale weather, then the model results and EEMD are consistent. We can however not verify this theory. At present we do not know if EEMD counts neither the events correct nor whether the ensemble forecast suppresses variability. The existence of variability above the time-scale related to friction between ocean waves and air can in fact explain some of the inconsistent results published in the literature and set a question mark behind the correctness of the calculation of friction in wave, ocean and weather modelling. (LN)}
place = {Denmark}
year = {2010}
month = {Mar}
}