Articles | Volume 11, issue 4
https://doi.org/10.5194/wes-11-1251-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-1251-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Biases in preconstruction estimates of wind plant annual energy production
National Wind Technology Center, National Laboratory of the Rockies, Golden, CO 80401, USA
Eric Simley
National Wind Technology Center, National Laboratory of the Rockies, Golden, CO 80401, USA
Related authors
Lu-Jan Huang, Simone Mancini, Daniel Mulas Hernando, and Rob Hammond
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-279, https://doi.org/10.5194/wes-2025-279, 2026
Preprint under review for WES
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This study shows how different modelling assumptions made in discrete-event simulation models can change predictions of maintenance costs and power losses for floating offshore wind farms. By testing two models under the same conditions, we identify which assumptions matter most and how they shape results. The findings help improve the reliability of future models and support better planning of maintenance strategies for floating wind projects.
Lu-Jan Huang, Simone Mancini, Daniel Mulas Hernando, and Rob Hammond
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-279, https://doi.org/10.5194/wes-2025-279, 2026
Preprint under review for WES
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This study shows how different modelling assumptions made in discrete-event simulation models can change predictions of maintenance costs and power losses for floating offshore wind farms. By testing two models under the same conditions, we identify which assumptions matter most and how they shape results. The findings help improve the reliability of future models and support better planning of maintenance strategies for floating wind projects.
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This paper presents one half of a companion paper series that studies strategies to reduce negative aerodynamic interference (i.e., wake effects) between nearby wind turbines in a wind farm. The approach leverages high-fidelity flow simulations of an open-source design for a wind turbine. Complimenting the companion paper’s analysis of the power and loading effects of the wake-control strategies, this article uncovers the underlying fluid-dynamic causes for these effects.
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Balthazar Arnoldus Maria Sengers, Andreas Rott, Eric Simley, Michael Sinner, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 8, 1693–1710, https://doi.org/10.5194/wes-8-1693-2023, https://doi.org/10.5194/wes-8-1693-2023, 2023
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Liang Dong, Wai Hou Lio, and Eric Simley
Wind Energ. Sci., 6, 1491–1500, https://doi.org/10.5194/wes-6-1491-2021, https://doi.org/10.5194/wes-6-1491-2021, 2021
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This paper suggests that the impacts of different turbulence models should be considered as uncertainties while evaluating the benefits of lidar-assisted control (LAC) in wind turbine design. The value creation of LAC, evaluated using the Kaimal turbulence model, will be diminished if the Mann turbulence model is used instead. In particular, the difference in coherence is more significant for larger rotors.
Eric Simley, Paul Fleming, Nicolas Girard, Lucas Alloin, Emma Godefroy, and Thomas Duc
Wind Energ. Sci., 6, 1427–1453, https://doi.org/10.5194/wes-6-1427-2021, https://doi.org/10.5194/wes-6-1427-2021, 2021
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Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to deflect their low-velocity wakes away from downstream turbines, increasing overall power production. Here, we present results from a two-turbine wake-steering experiment at a commercial wind plant. By analyzing the wind speed dependence of wake steering, we find that the energy gained tends to increase for higher wind speeds because of both the wind conditions and turbine operation.
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Jennifer King, Paul Fleming, Ryan King, Luis A. Martínez-Tossas, Christopher J. Bay, Rafael Mudafort, and Eric Simley
Wind Energ. Sci., 6, 701–714, https://doi.org/10.5194/wes-6-701-2021, https://doi.org/10.5194/wes-6-701-2021, 2021
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This paper highlights the secondary effects of wake steering, including yaw-added wake recovery and secondary steering. These effects enhance the value of wake steering especially when applied to a large wind farm. This paper models these secondary effects using an analytical model proposed in the paper. The results of this model are compared with large-eddy simulations for several cases including 2-turbine, 3-turbine, 5-turbine, and 38-turbine cases.
Cited articles
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Short summary
Estimating the energy production of a wind plant before construction is a historically difficult task. We build on prior research comparing the actual energy production of wind plants and their estimated energy production using owner-provided energy data. Similar to prior studies, we found an increasing bias of overestimating annual energy production. In general, estimates before construction are not conservative enough, suggesting room for improvements in the energy yield assessment process.
Estimating the energy production of a wind plant before construction is a historically difficult...
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