Lu Zhan
Lu Zhan
Dirección de correo verificada de umn.edu
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Quantification of power losses due to wind turbine wake interactions through SCADA, meteorological and wind LiDAR data
S El‐Asha, L Zhan, GV Iungo
Wind Energy 20 (11), 1823-1839, 2017
502017
LiDAR measurements for an onshore wind farm: Wake variability for different incoming wind speeds and atmospheric stability regimes
L Zhan, S Letizia, G Valerio Iungo
Wind Energy 23 (3), 501-527, 2020
252020
Parabolic RANS solver for low‐computational‐cost simulations of wind turbine wakes
GV Iungo, V Santhanagopalan, U Ciri, F Viola, L Zhan, MA Rotea, ...
Wind Energy 21 (3), 184-197, 2018
222018
Optimal tuning of engineering wake models through lidar measurements
L Zhan, S Letizia, GV Iungo
Wind Energy Science 5 (4), 1601-1622, 2020
112020
One‐way mesoscale‐microscale coupling for simulating a wind farm in North Texas: Assessment against SCADA and LiDAR data
C Santoni, EJ García‐Cartagena, U Ciri, L Zhan, G Valerio Iungo, ...
Wind Energy 23 (3), 691-710, 2020
82020
Quantification of the axial induction exerted by utility-scale wind turbines by coupling LiDAR measurements and RANS simulations
G Valerio Iungo, S Letizia, L Zhan
Journal of Physics: Conference Series 1037, 2018
82018
LiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics–Part 2: Applications to lidar measurements of wind …
S Letizia, L Zhan, GV Iungo
Atmospheric Measurement Techniques 14 (3), 2095-2113, 2021
52021
Profitability optimization of a wind power plant performed through different optimization algorithms and a data-driven RANS solver
V Santhanagopalan, S Letizia, L Zhan, LY Al-Hamidi, GV Iungo
2018 Wind Energy Symposium, 2018, 2018
52018
Wind LiDAR measurements of wind turbine wakes evolving over flat and complex terrains: ensemble statistics of the velocity field
L Zhan, S Letizia, GV Iungo
Journal of Physics: Conference Series 1452 (1), 012077, 2020
42020
LiSBOA: LiDAR Statistical Barnes Objective Analysis for optimal design of LiDAR scans and retrieval of wind statistics. Part II: Applications to synthetic and real LiDAR data …
S Letizia, L Zhan, GV Iungo
Atmospheric Measurement Techniques Discussions 2020, 1-40, 2020
22020
Assessment of wake superposition models through wind tunnel tests and LiDAR measurements
S Letizia, L Zhan, E Nanos, C Bottasso, MA Rotea, GV Iungo, TUM Team, ...
APS Division of Fluid Dynamics Meeting Abstracts, G42. 006, 2019
12019
Impact of Fog Particles on 1.55 μm Automotive LiDAR Sensor Performance: An Experimental Study in an Enclosed Chamber
L Zhan, WF Northrop
SAE Technical Paper, 2021
2021
An Experimental Study of Lateral Wake Interactions within a Wind Farm
EM Nanos, S Letizia, L Zhan, MA Rotea, CL Bottasso, GV Iungo
Wind Energy Science Conference 2019, 2019
2019
LiDAR measurements and modeling of onshore wind farms on flat and complex terrains
S Letizia, L Zhan, GV Iungo
Bulletin of the American Physical Society 63, 2018
2018
RANS simulations of wind turbine wakes: optimal tuning of turbulence closure and aerodynamic loads from LiDAR and SCADA data
S Letizia, M Puccioni, L Zhan, F Viola, S Camarri, GV Iungo
APS Division of Fluid Dynamics Meeting Abstracts, D17. 008, 2017
2017
Weather Research and Forecasting model simulation of an onshore wind farm: assessment against LiDAR and SCADA data
C Santoni, EJ Garcia-Cartagena, L Zhan, GV Iungo, S Leonardi
APS Division of Fluid Dynamics Meeting Abstracts, D17. 001, 2017
2017
Proactive monitoring of a wind turbine array with lidar measurements, SCADA data and a data-driven RANS solver
G Iungo, EA Said, V Santhanagopalan, L Zhan
AGU Fall Meeting Abstracts 2016, GC54B-08, 2016
2016
Proactive monitoring of an onshore wind farm through lidar measurements, SCADA data and a data-driven RANS solver
GV Iungo, S Camarri, U Ciri, S El-Asha, S Leonardi, MA Rotea, ...
Bulletin of the American Physical Society 61, 2016
2016
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Artículos 1–18