Normalized-wake characterization by long-range lidars
Creators: name: Orozco, Priscila MS
Publisher: name: Zenodo
Year: 2020
Subjects: wakes
lidar measurements
boundary layer
wake tracking
averaged wake

description: Slide presentation on Priscila Orozco's PhD project entitled "Normalized-wake characterization by long-range lidars" given on the EAWE Phd Seminar 2020. This PhD project is inserted in the LIdar Knowledge Europe (LIKE) project H2020-MSCA-ITN-20 (https://www.msca-like.eu) - funded by the European Union (grant no. 858358) - and developed at UL International GmbH under the supervision of Dr. Juan Trujillo. It is co-supervised by Prof. Dr. Martin Kühn from the ForWind Center for Wind Energy Research at the Carl von Ossietzky University of Oldenburg. Submitted abstract for the EAWE Phd Seminar 2020: Remote sensing techniques such as lidars have proven to be the most versatile tool for measuring wind turbine wakes due to their good resolution and flexibility (Wildmann <em>et al</em>., 2018). Indeed, they have aided in revealing that wakes exhibit large-scale dynamics and that the measured field depends on which frame of reference is used to analyze them (e.g. Trujillo <em>et al</em>., 2011; Beck <em>et al</em>., 2015). These studies have shown that there is the potential of filtering out the large-scale effects to obtain a wake field unaffected by external atmospheric conditions. This PhD project strives to evaluate this potential and its possible applications. The main objective is to prove to which extent external large-scale effects of the boundary layer can be separated from the far wake from full-field measurements. More specifically, we intend to reach a site-independent “normalized wake”, analogous to the wake in an environment influenced only by turbulence. In the first phase of this PhD, different analysis techniques will be tested on single-wake lidar measurements to obtain the normalized wake under different operational conditions. The PARKCAST project data from the Alpha Ventus wind farm, acquired by two nacelle-mounted long-range lidars (one looking upwind and the other downwind), will be used in this stage. By applying different wake tracking techniques, we first intend to estimate a local quasi-steady wake from the downwind-looking lidar measurements and represent it in a meandering frame of reference. Secondly, the aim is to spot the optimal analysis method to reach a normalized wake and perform a proof of concept of its application, i.e., turning it back to a local wake by considering the atmospheric conditions of the measurement site.
description: LIdar Knowledge Europe (LIKE) project H2020-MSCA-ITN-20 (https://www.msca-like.eu) - funded by the European Union (grant no. 858358)
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