In the nationally funded project ParkCast new methods for short-term power prediction for offshore wind farms will be developed, optimized and evaluated. The power forecasts focus on the time range up to 60 minutes with high temporal resolution. The aim is to significantly improve the temporal resolution and prediction quality of the park power in the above time range and thus contribute to grid stability and security of supply. For this purpose, long-range lidar measurements were performed at the alpha ventus wind farm to measure the inflow and wake of the wind farm. The dataset contains wind measurement lidar data from March 2020 to March 2021 which was recorded on top of the nacelle of the AV04 turbine in the farm. The data is provided as hdf5 files with a time resolution of 1h per file. The hdf5 files are zipped month-wise. The lidar did not measure continuously due to e.g. maintenance work of the wind farm. Therefore the zipped files vary in size.
Würth, Ines/Stuttgart Wind Energy, University of Stuttgart, Wigger, Maayen/Stuttgart Wind Energy, University of Stuttgart, Berlinger, Philipp/Stuttgart Wind Energy, University of Stuttgart
%0 Generic
%1 wurth2022scanning
%A Würth, Ines
%A Wigger, Maayen
%A Berlinger, Philipp
%D 2022
%K darus ubs_10006 ubs_20010 ubs_30093 ubs_40324 unibibliografie
%R 10.18419/darus-2298
%T Scanning wind lidar dataset from the alpha ventus wind farm
%X In the nationally funded project ParkCast new methods for short-term power prediction for offshore wind farms will be developed, optimized and evaluated. The power forecasts focus on the time range up to 60 minutes with high temporal resolution. The aim is to significantly improve the temporal resolution and prediction quality of the park power in the above time range and thus contribute to grid stability and security of supply. For this purpose, long-range lidar measurements were performed at the alpha ventus wind farm to measure the inflow and wake of the wind farm. The dataset contains wind measurement lidar data from March 2020 to March 2021 which was recorded on top of the nacelle of the AV04 turbine in the farm. The data is provided as hdf5 files with a time resolution of 1h per file. The hdf5 files are zipped month-wise. The lidar did not measure continuously due to e.g. maintenance work of the wind farm. Therefore the zipped files vary in size.
@misc{wurth2022scanning,
abstract = {In the nationally funded project ParkCast new methods for short-term power prediction for offshore wind farms will be developed, optimized and evaluated. The power forecasts focus on the time range up to 60 minutes with high temporal resolution. The aim is to significantly improve the temporal resolution and prediction quality of the park power in the above time range and thus contribute to grid stability and security of supply. For this purpose, long-range lidar measurements were performed at the alpha ventus wind farm to measure the inflow and wake of the wind farm. The dataset contains wind measurement lidar data from March 2020 to March 2021 which was recorded on top of the nacelle of the AV04 turbine in the farm. The data is provided as hdf5 files with a time resolution of 1h per file. The hdf5 files are zipped month-wise. The lidar did not measure continuously due to e.g. maintenance work of the wind farm. Therefore the zipped files vary in size.},
added-at = {2022-06-09T19:15:45.000+0200},
affiliation = {Würth, Ines/Stuttgart Wind Energy, University of Stuttgart, Wigger, Maayen/Stuttgart Wind Energy, University of Stuttgart, Berlinger, Philipp/Stuttgart Wind Energy, University of Stuttgart},
author = {Würth, Ines and Wigger, Maayen and Berlinger, Philipp},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2432a1915b6edde4e5edaa631d23a4db7/unibiblio},
doi = {10.18419/darus-2298},
howpublished = {Dataset},
interhash = {99d30ae8a6814fe8c41598a5a5a99f34},
intrahash = {432a1915b6edde4e5edaa631d23a4db7},
keywords = {darus ubs_10006 ubs_20010 ubs_30093 ubs_40324 unibibliografie},
orcid-numbers = {Würth, Ines/0000-0002-1365-0243, Wigger, Maayen/0000-0002-6284-8117, Berlinger, Philipp/0000-0002-0004-5255},
timestamp = {2022-06-09T17:15:45.000+0200},
title = {Scanning wind lidar dataset from the alpha ventus wind farm},
year = 2022
}
