Articles | Volume 6, issue 3
Wind Energ. Sci., 6, 841–866, 2021
https://doi.org/10.5194/wes-6-841-2021
Wind Energ. Sci., 6, 841–866, 2021
https://doi.org/10.5194/wes-6-841-2021

Research article 07 Jun 2021

Research article | 07 Jun 2021

Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals

Davide Conti et al.

Related authors

Calibration and validation of the Dynamic Wake Meandering model Part I: Bayesian estimation of model parameters using SpinnerLidar-derived wake characteristics
Davide Conti, Nikolay Dimitrov, Alfredo Peña, and Thomas Herges
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2020-135,https://doi.org/10.5194/wes-2020-135, 2021
Revised manuscript accepted for WES
Short summary
Aeroelastic load validation in wake conditions using nacelle-mounted lidar measurements
Davide Conti, Nikolay Dimitrov, and Alfredo Peña
Wind Energ. Sci., 5, 1129–1154, https://doi.org/10.5194/wes-5-1129-2020,https://doi.org/10.5194/wes-5-1129-2020, 2020
Short summary
The fence experiment – full-scale lidar-based shelter observations
Alfredo Peña, Andreas Bechmann, Davide Conti, and Nikolas Angelou
Wind Energ. Sci., 1, 101–114, https://doi.org/10.5194/wes-1-101-2016,https://doi.org/10.5194/wes-1-101-2016, 2016
Short summary

Related subject area

Wind and turbulence
Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data
Janna Kristina Seifert, Martin Kraft, Martin Kühn, and Laura J. Lukassen
Wind Energ. Sci., 6, 997–1014, https://doi.org/10.5194/wes-6-997-2021,https://doi.org/10.5194/wes-6-997-2021, 2021
Short summary
New methods to improve the vertical extrapolation of near-surface offshore wind speeds
Mike Optis, Nicola Bodini, Mithu Debnath, and Paula Doubrawa
Wind Energ. Sci., 6, 935–948, https://doi.org/10.5194/wes-6-935-2021,https://doi.org/10.5194/wes-6-935-2021, 2021
Short summary
A pressure-driven atmospheric boundary layer model satisfying Rossby and Reynolds number similarity
Maarten Paul van der Laan, Mark Kelly, and Mads Baungaard
Wind Energ. Sci., 6, 777–790, https://doi.org/10.5194/wes-6-777-2021,https://doi.org/10.5194/wes-6-777-2021, 2021
Short summary
Design and analysis of a wake model for spatially heterogeneous flow
Alayna Farrell, Jennifer King, Caroline Draxl, Rafael Mudafort, Nicholas Hamilton, Christopher J. Bay, Paul Fleming, and Eric Simley
Wind Energ. Sci., 6, 737–758, https://doi.org/10.5194/wes-6-737-2021,https://doi.org/10.5194/wes-6-737-2021, 2021
Short summary
Evaluation of tilt control for wind-turbine arrays in the atmospheric boundary layer
Carlo Cossu
Wind Energ. Sci., 6, 663–675, https://doi.org/10.5194/wes-6-663-2021,https://doi.org/10.5194/wes-6-663-2021, 2021
Short summary

Cited articles

IEC: International Standard IEC61400-13: Wind turbines – Part 13: Measurement of mechanical loads, Standard, IEC, 2015. a, b, c
IEC: International Standard IEC61400-1: wind turbines – Part 1: design guidelines, Fourth; 2019, Standard, IEC, 2019. a, b, c, d, e
Achen, C. H.: Interpreting and Using Regression, Sage Publications, Beverly Hills, https://doi.org/10.4135/9781412984560, 1982. a
Ainslie, J.: Calculating the flow field in the wake of wind turbines, J. Wind Eng. Ind. Aerod., 27, 213–224, https://doi.org/10.1016/0167-6105(88)90037-2, 1988. a
Ainslie, J. F.: Wake modelling and the prediction of turbulence properties, in: Proceedings of the Bwea Wind Energy Conference, british Wind Energy Association, 20–24 October 1986, Cambridge, 115–120, 1986. a
Download
Short summary
We define two lidar-based procedures for improving the accuracy of wind turbine load assessment under wake conditions. The first approach incorporates lidar observations directly into turbulence fields serving as inputs for aeroelastic simulations; the second approach imposes lidar-fitted wake deficit time series on the turbulence fields. The uncertainty in the lidar-based power and load predictions is quantified for a variety of scanning configurations and atmosphere turbulence conditions.