Wind Plant Power Optimization through Yaw Control using a Parametric Model for Wake Effects -- A CFD Simulation Study

Gebraad, P. M. O.; Teeuwisse, F. W.; van Wingerden, J. W.; Fleming, Paul A.; Ruben, S. D.; Marden, J. R.; Pao, L. Y.

doi:10.1002/we.1822

Title: Wind Plant Power Optimization through Yaw Control using a Parametric Model for Wake Effects -- A CFD Simulation Study

Journal Article · Fri Jan 01 00:00:00 EST 2016 · Wind Energy

DOI:https://doi.org/10.1002/we.1822· OSTI ID:1238764

Gebraad, P. M. O. ^[1]; Teeuwisse, F. W. ^[1]; van Wingerden, J. W. ^[1]; Fleming, Paul A. ^[2]; Ruben, S. D. ^[3]; Marden, J. R. ^[3]; Pao, L. Y. ^[3]

Delft Univ. of Technology (Netherlands). Delft Center for Systems and Control
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Univ. of Colorado, Boulder, CO (United States)

This article presents a wind plant control strategy that optimizes the yaw settings of wind turbines for improved energy production of the whole wind plant by taking into account wake effects. The optimization controller is based on a novel internal parametric model for wake effects, called the FLOw Redirection and Induction in Steady-state (FLORIS) model. The FLORIS model predicts the steady-state wake locations and the effective flow velocities at each turbine, and the resulting turbine electrical energy production levels, as a function of the axial induction and the yaw angle of the different rotors. The FLORIS model has a limited number of parameters that are estimated based on turbine electrical power production data. In high-fidelity computational fluid dynamics simulations of a small wind plant, we demonstrate that the optimization control based on the FLORIS model increases the energy production of the wind plant, with a reduction of loads on the turbines as an additional effect.

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Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1238764

Report Number(s):: NREL/JA-5000-61823

Journal Information:: Wind Energy, Vol. 19, Issue 1; ISSN 1095-4244

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 305 works

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Optimization of turbine design in wind farms with multiple hub heights, using exact analytic gradients and structural constraints Stanley, Andrew P. J.; Ning, Andrew; Dykes, Katherine Wind Energy, Vol. 22, Issue 5 https://doi.org/10.1002/we.2310	journal	January 2019
The aerodynamics of the curled wake: a simplified model in view of flow control Martínez-Tossas, Luis A.; Annoni, Jennifer; Fleming, Paul A. Wind Energy Science, Vol. 4, Issue 1 https://doi.org/10.5194/wes-4-127-2019	journal	January 2019
Low-level jets over the North Sea based on ERA5 and observations: together they do better Kalverla, Peter C.; Duncan, Jr., James B.; Steeneveld, Gert-Jan Wind Energy Science Discussions https://doi.org/10.5194/wes-2018-79	journal	January 2019
Development of a parameterized reduced-order vertical-axis wind turbine wake model Tingey, Eric B.; Ning, Andrew Wind Engineering, Vol. 44, Issue 5 https://doi.org/10.1177/0309524x19849864	journal	June 2019
Wind turbine wake position detection and rotor speed-based wake steering validation in a wind tunnel wake simulator Castillo, Ricardo; Bayne, Stephen; Pol, Suhas Wind Engineering, Vol. 44, Issue 5 https://doi.org/10.1177/0309524x19852350	journal	June 2019
Numerical and Experimental Methods for the Assessment of Wind Turbine Control Upgrades Astolfi, Davide; Castellani, Francesco; Berno, Francesco Applied Sciences, Vol. 8, Issue 12 https://doi.org/10.3390/app8122639	journal	December 2018

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