TY - JOUR
T1 - 2D VAR single Doppler lidar vector retrieval and its application in offshore wind energy
AU - Cherukuru, Nihanth W.
AU - Calhoun, Ronald
AU - Krishnamurthy, Raghavendra
AU - Benny, Svardal
AU - Reuder, Joachim
AU - Flügge, Martin
N1 - Funding Information:
This work was funded by the Navy Neptune Project . The OBLEX -F1 campaign was performed within the NORCOWE (Norwegian Centre for Offshore Wind Energy) project funded by the Research Council of Norway (RCN) under project number 193821. The wind lidars used for the analysis are part of the National Norwegian infrastructure project OBLO (Offshorer Boundary Layer Observatory) also funded by RCN under project number 277770
Publisher Copyright:
© 2017 The Author(s).
PY - 2017
Y1 - 2017
N2 - Remote sensors like Doppler lidars can map the winds with high accuracy and spatial resolution. One shortcoming of lidars is that the radial velocity measured by the lidar does not give a complete picture of the windfield necessitating additional data processing to reconstruct the windfield. Most of the popular vector retrieval algorithms rely on the homogenous wind field assumption which plays a vital role in reducing the indeterminacy of the inverse problem of obtaining Cartesian velocity from radial velocity measurements. Consequently, these methods fail in situations where the flow is heterogeneous e.g., Turbine wakes. Alternate methods are based either on statistical models (e.g., optimal interpolation [1]) or computationally intensive four dimensional variational methods [2]. This study deals with a 2D variational vector retrieval for Doppler lidar that uses the radial velocity advection equation as an additional constraint along with a tangential velocity constraint derived from a new formulation with gradients of radial velocity. The retrieval was applied on lidar data from a wind farm and preliminary analysis revealed that the algorithm was able to retrieve the mean wind field while preserving the small scale flow structure.
AB - Remote sensors like Doppler lidars can map the winds with high accuracy and spatial resolution. One shortcoming of lidars is that the radial velocity measured by the lidar does not give a complete picture of the windfield necessitating additional data processing to reconstruct the windfield. Most of the popular vector retrieval algorithms rely on the homogenous wind field assumption which plays a vital role in reducing the indeterminacy of the inverse problem of obtaining Cartesian velocity from radial velocity measurements. Consequently, these methods fail in situations where the flow is heterogeneous e.g., Turbine wakes. Alternate methods are based either on statistical models (e.g., optimal interpolation [1]) or computationally intensive four dimensional variational methods [2]. This study deals with a 2D variational vector retrieval for Doppler lidar that uses the radial velocity advection equation as an additional constraint along with a tangential velocity constraint derived from a new formulation with gradients of radial velocity. The retrieval was applied on lidar data from a wind farm and preliminary analysis revealed that the algorithm was able to retrieve the mean wind field while preserving the small scale flow structure.
KW - 2D-VAR
KW - Doppler Wind lidars
KW - Offshore Wind Energy
KW - Optimization
KW - Vector wind retrieval
KW - Wind turbine control
KW - Wind turbine wakes
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U2 - 10.1016/j.egypro.2017.10.378
DO - 10.1016/j.egypro.2017.10.378
M3 - Conference article
AN - SCOPUS:85040309707
SN - 1876-6102
VL - 137
SP - 497
EP - 504
JO - Energy Procedia
JF - Energy Procedia
T2 - 14th Deep Sea Offshore Wind R and D Conference, EERA DeepWind 2017
Y2 - 18 January 2017 through 20 January 2017
ER -