ZONG H H, SUN E B. Reivew of active wake control for horizontal-axis wind turbines[J]. Acta Aerodynamica Sinica, 2022, 40(4): 51−68. DOI: 10.7638/kqdlxxb-2021.0249
Citation: ZONG H H, SUN E B. Reivew of active wake control for horizontal-axis wind turbines[J]. Acta Aerodynamica Sinica, 2022, 40(4): 51−68. DOI: 10.7638/kqdlxxb-2021.0249

Reivew of active wake control for horizontal-axis wind turbines

More Information
  • Received Date: September 12, 2021
  • Revised Date: October 05, 2021
  • Accepted Date: November 21, 2021
  • Available Online: December 26, 2021
  • Large-scale wind farms with multiple rows of horizontal-axis wind turbines suffer from significant power losses (30%-40%) due to wake interactions. To deal with this situation, the yaw-based active wake control (AWC) has been proposed. The principle of AWC is to yaw the upstream wind turbines so that the wake can be deflected away from the turbine row, which hopefully will lead to a net gain of the total wind farm power production. In this paper, the progress of the AWC technique in the past decade is reviewed from four aspects: wake models of single non-yawed wind turbine, wake models of single yawed wind turbine, wake superposition methods for multiple wind turbines, and wind farm power optimization. Meanwhile, issues needed to be addressed before being applied to engineering are summarized. Based on these reviews, it is fair to conclude that the AWC technique is more or less mature now, in the sense that earlier laboratory results from analytical modeling, numerical simulations, and wind tunnel studies have been successfully applied to field tests of commercial wind farms, and significant improvement of the net power gain has been obtained. In terms of theoretical progress, EPFL Gaussian wake models, primary and secondary wake deflection models based on the vortex-induced cross-wind velocities, momentum-conserving wake superposition laws are increasingly becoming the standard in the wind farm power prediction. Regarding practical engineering, it has been found that a whole bunch of parameters such as turbine rows, streamwise turbine spacing, turbulence intensity, thermal instability of atmospheric boundary layer, wind speed, and direction variability can affect the magnitude of net power gain in the active wake control. According to recent field tests performed by National Renewable Energy Laboratory (NREL, US) and Stanford University, AWC is able to improve the total wind farm power production by 5%-15% if the wind direction is aligned with turbine rows, and when these net power gains are averaged over all wind directions, an increase of 1%-3% in the wind farm efficiency is expected.
  • [1]
    IEA. Global Energy Review 2021. Internatioanl Energy Agency 2021. Internatioanl Energy Agency 2021[EB/OL]. https://www.iea.org/reports/global-energy-review-2021
    [2]
    PORTÉ-AGEL F, BASTANKHAH M, SHAMSODDIN S. Wind-turbine and wind-farm flows: a review[J]. Boundary-Layer Meteorology, 2020, 174(1): 1-59. DOI: 10.1007/s10546-019-00473-0
    [3]
    RITCHIE H, ROSER M. Energy[EB/OL]. Published online at OurWorldInData. org. , 2021. https://ourworldindata.org/energy
    [4]
    JAGANMOHAN M. Installed wind power capacity worldwide 2001-2020[EB/OL]. Published online at www. statista. com, 2021. https://www.statista.com/statistics/268363/installed-wind-power-capacity-worldwide/
    [5]
    黎作武, 贺德馨. 风能工程中流体力学问题的研究现状与进展[J]. 力学进展, 2013, 43(5): 472-525.

    LI Z W, HE D X. Reviews of fluid dynamics researches in wind energy engineering[J]. Advances in Mechanics, 2013, 43(5): 472-525. (in Chinese)
    [6]
    STEVENS R J A M, MENEVEAU C. Flow structure and turbulence in wind farms[J]. Annual Review of Fluid Mechanics, 2017, 49(1): 311-339. DOI: 10.1146/annurev-fluid-010816-060206
    [7]
    BARTHELMIE R J, HANSEN K, FRANDSEN S T, et al. Modelling and measuring flow and wind turbine wakes in large wind farms offshore[J]. Wind Energy, 2009, 12(5): 431-444. DOI: 10.1002/we.348
    [8]
    BARTHELMIE R J, PRYOR S C, FRANDSEN S T, et al. Quantifying the impact of wind turbine wakes on power output at offshore wind farms[J]. Journal of Atmospheric and Oceanic Technology, 2010, 27(8): 1302-1317. DOI: 10.1175/2010jtecha1398.1
    [9]
    BARTHELMIE R J, JENSEN L E. Evaluation of wind farm efficiency and wind turbine wakes at the Nysted offshore wind farm[J]. Wind Energy, 2010, 13(6): 573-586. DOI: 10.1002/we.408
    [10]
    HASAGER C, RASMUSSEN L, PEÑA A, et al. Wind farm wake: the horns rev photo case[J]. Energies, 2013, 6(2): 696-716. DOI: 10.3390/en6020696
    [11]
    MEDICI D. Experimental studies of wind turbine wakes: power optimisation and meandering[D]. KTH, 2005.
    [12]
    ADARAMOLA M S, KROGSTAD P Å. Experimental investigation of wake effects on wind turbine performance[J]. Renewable Energy, 2011, 36(8): 2078-2086. DOI: 10.1016/j.renene.2011.01.024
    [13]
    WAGENAAR J W, MACHIELSE L A H, SCHEPERS J G. Controlling wind in ECN’s scaled wind farm[C]// EWEA 2012. https://www.researchgate.net/publication/264851319_Controlling_Wind_in_ECN's_Scaled_Wind_Farm
    [14]
    DAR Z, KAR K, SAHNI O, et al. Windfarm power optimization using yaw angle control[J]. IEEE Transactions on Sustainable Energy, 2017, 8(1): 104-116. DOI: 10.1109/TSTE.2016.2585883
    [15]
    WANG J, BOTTASSO C L, CAMPAGNOLO F. Wake redirection: comparison of analytical, numerical and experimental models[C]//Journal of Physics: Conference Series. IOP Publishing, 2016, 753(3): 032064. https://re.public.polimi.it/retrieve/handle/11311/1007400/163974/WANGJ01-16.pdf doi: 10.1088/1742-6596/753/3/032064
    [16]
    CAMPAGNOLO F, PETROVIĆ V, BOTTASSO C L, et al. Wind tunnel testing of wake control strategies[C]//2016 American Control Conference (ACC), Boston, MA, USA. IEEE, 2016: 513-518. doi: 10.1109/ACC.2016.7524965
    [17]
    HOWLAND M F, LELE S K, DABIRI J O. Wind farm power optimization through wake steering[J]. Proceedings of the National Academy of Sciences of the United States of America, 2019, 116(29): 14495-14500. https://www.pnas.org/content/pnas/116/29/14495.full.pdf doi: 10.1073/pnas.1903680116
    [18]
    BASTANKHAH M, PORTÉ-AGEL F. Wind farm power optimization via yaw angle control: a wind tunnel study[J]. Journal of Renewable and Sustainable Energy, 2019, 11(2): 023301. DOI: 10.1063/1.5077038
    [19]
    ZONG H H, PORTÉ-AGEL F. Experimental investigation and analytical modelling of active yaw control for wind farm power optimization[J]. Renewable Energy, 2021, 170: 1228-1244. DOI: 10.1016/j.renene.2021.02.059
    [20]
    NASH R, NOURI R, VASEL-BE-HAGH A. Wind turbine wake control strategies: a review and concept proposal[J]. Energy Conversion and Management, 2021, 245: 114581. DOI: 10.1016/j.enconman.2021.114581
    [21]
    NANOS E M, BOTTASSO C L, MANOLAS D I, et al. Vertical wake deflection for floating wind turbines by differential ballast control[J]. Wind Energy Science Discussions, 2021(Accepted). https://www.researchgate.net/publication/354010920_Vertical_wake_deflection_for_floating_wind_turbines_by_differential_ballast_control doi: 10.5194/wes-2021-79
    [22]
    NANOS E M, LETIZIA S, CLEMENTE D J B, et al. Vertical wake deflection for offshore floating wind turbines by differential ballast control[J]. Journal of Physics: Conference Series, 2020, 1618: 022047. DOI: 10.1088/1742-6596/1618/2/022047
    [23]
    KIMURA K, TANABE Y, MATSUO Y, et al. Forced wake meandering for rapid recovery of velocity deficits in a wind turbine wake[C]//AIAA Scitech 2019 Forum, San Diego, California. Reston, Virginia: AIAA, 2019: 2083. doi: 10.2514/6.2019-2083
    [24]
    WANG J, FOLEY S, NANOS E M, et al. Numerical and experimental study of wake redirection techniques in a boundary layer wind tunnel[J]. Journal of Physics: Conference Series, 2017, 854: 012048. DOI: 10.1088/1742-6596/854/1/012048
    [25]
    FLEMING P A, GEBRAAD P M O, LEE S, et al. Evaluating techniques for redirecting turbine wakes using SOWFA[J]. Renewable Energy, 2014, 70: 211-218. DOI: 10.1016/j.renene.2014.02.015
    [26]
    FLEMING P, GEBRAAD P M O, LEE S, et al. Simulation comparison of wake mitigation control strategies for a two-turbine case[J]. Wind Energy, 2015, 18(12): 2135-2143. DOI: 10.1002/we.1810
    [27]
    FLEMING P, ANNONI J, SHAH J J, et al. Field test of wake steering at an offshore wind farm[J]. Wind Energy Science, 2017, 2(1): 229-239. DOI: 10.5194/wes-2-229-2017
    [28]
    FLEMING P A, NING A, GEBRAAD P M O, et al. Wind plant system engineering through optimization of layout and yaw control[J]. Wind Energy, 2016, 19(2): 329-344.https://onlinelibrary.wiley.com/doi/am-pdf/ 10.1002/we.1836 DOI: 10.1002/we.1836
    [29]
    BENSASON D, SIMLEY E, ROBERTS O, et al. Evaluation of the potential for wake steering for US land-based wind power plants[J]. Journal of Renewable and Sustainable Energy, 2021, 13(3): 033303. DOI: 10.1063/5.0039325
    [30]
    SONG D R, YANG J, FAN X Y, et al. Maximum power extraction for wind turbines through a novel yaw control solution using predicted wind directions[J]. Energy Conversion and Management, 2018, 157: 587-599. DOI: 10.1016/j.enconman.2017.12.019
    [31]
    SØRENSEN J N. Aerodynamic aspects of wind energy conversion[J]. Annual Review of Fluid Mechanics, 2011, 43(1): 427-448. DOI: 10.1146/annurev-fluid-122109-160801
    [32]
    VERMEER L J, SØRENSEN J N, CRESPO A. Wind turbine wake aerodynamics[J]. Progress in Aerospace Sciences, 2003, 39(6-7): 467-510. DOI: 10.1016/S0376-0421(03)00078-2
    [33]
    MEDICI D, IVANELL S, DAHLBERG J Å, et al. The upstream flow of a wind turbine: blockage effect[J]. Wind Energy, 2011, 14(5): 691-697. DOI: 10.1002/we.451
    [34]
    BASTANKHAH M, PORTÉ-AGEL F. Wind tunnel study of the wind turbine interaction with a boundary-layer flow: Upwind region, turbine performance, and wake region[J]. Physics of Fluids, 2017, 29(6): 065105. DOI: 10.1063/1.4984078
    [35]
    DASARI T, WU Y, LIU Y, et al. Near-wake behaviour of a utility-scale wind turbine[J]. Journal of Fluid Mechanics, 2019, 859: 204-246. DOI: 10.1017/jfm.2018.779
    [36]
    HONG J R, TOLOUI M, CHAMORRO L P, et al. Natural snowfall reveals large-scale flow structures in the wake of a 2.5-MW wind turbine[J]. Nature Communications, 2014, 5: 4216. DOI: 10.1038/ncomms5216
    [37]
    CHAMORRO L P, PORTÉ-AGEL F. Effects of thermal stability and incoming boundary-layer flow characteristics on wind-turbine wakes: a wind-tunnel study[J]. Boundary-Layer Meteorology, 2010, 136(3): 515-533. DOI: 10.1007/s10546-010-9512-1
    [38]
    POPE S B. Turbulent flows[J]. Measurement Science and Technology, 2001, 12(11). DOI: 10.1088/0957-0233/12/11/705
    [39]
    BASTANKHAH M, PORTÉ-AGEL F. A new analytical model for wind-turbine wakes[J]. Renewable Energy, 2014, 70: 116-123. DOI: 10.1016/j.renene.2014.01.002
    [40]
    AINSLIE J F. Calculating the flowfield in the wake of wind turbines[J]. Journal of Wind Engineering and Industrial Aerodynamics, 1988, 27(1-3): 213-224. DOI: 10.1016/0167-6105(88)90037-2
    [41]
    FANG J N, PORTÉ-AGEL F. Large-eddy simulation of very-large-scale motions in the neutrally stratified atmospheric boundary layer[J]. Boundary-Layer Meteorology, 2015, 155(3): 397-416. DOI: 10.1007/s10546-015-0006-z
    [42]
    LARSEN T J, MADSEN H A, LARSEN G C, et al. Validation of the dynamic wake meander model for loads and power production in the Egmond aan Zee wind farm[J]. Wind Energy, 2013, 16(4): 605-624. DOI: 10.1002/we.1563
    [43]
    ESPAÑA G, AUBRUN S, LOYER S, et al. Wind tunnel study of the wake meandering downstream of a modelled wind turbine as an effect of large scale turbulent eddies[J]. Journal of Wind Engineering and Industrial Aerodynamics, 2012, 101: 24-33. DOI: 10.1016/j.jweia.2011.10.011
    [44]
    WU Y T, PORTÉ-AGEL F. Large-eddy simulation of wind-turbine wakes: evaluation of turbine parametrisations[J]. Boundary-Layer Meteorology, 2011, 138(3): 345-366. DOI: 10.1007/s10546-010-9569-x
    [45]
    JENSEN N O. A note on wind turbine interaction[R]. Riso-M-2411. Risoe National Laboratory, Roskilde, Denmark, 1983: 16. https://backend.orbit.dtu.dk/ws/portalfiles/portal/55857682/ris_m_2411.pdf
    [46]
    FRANDSEN S, BARTHELMIE R, PRYOR S, et al. Analytical modelling of wind speed deficit in large offshore wind farms[J]. Wind Energy, 2006, 9(1‐2): 39-53.https://onlinelibrary.wiley.com/doi/epdf/ 10.1002/we.189 DOI: 10.1002/we.189
    [47]
    HANSEN M. Aerodynamics of wind turbines[M]. Routledge, 2015. DOI: 10.4324/9781315769981
    [48]
    SHAMSODDIN S, PORTÉ-AGEL F. A model for the effect of pressure gradient on turbulent axisymmetric wakes[J]. Journal of Fluid Mechanics, 2018, 837: R3. DOI: 10.1017/jfm.2017.864
    [49]
    ABKAR M, SØRENSEN J, PORTÉ-AGEL F. An analytical model for the effect of vertical wind veer on wind turbine wakes[J]. Energies, 2018, 11(7): 1838. DOI: 10.3390/en11071838
    [50]
    BODINI N, ZARDI D, LUNDQUIST J K. Three-dimensional structure of wind turbine wakes as measured by scanning lidar[J]. Atmospheric Measurement Techniques, 2017, 10(8): 2881-2896. DOI: 10.5194/amt-10-2881-2017
    [51]
    ARCHER C L, VASEL-BE-HAGH A, YAN C, et al. Review and evaluation of wake loss models for wind energy applications[J]. Applied Energy, 2018, 226: 1187-1207. DOI: 10.1016/j.apenergy.2018.05.085
    [52]
    FLEMING P A, SCHOLBROCK A K, JEHU A, et al. Field-test results using a nacelle-mounted lidar for improving wind turbine power capture by reducing yaw misalignment[J]. Journal of Physics: Conference Series, 2014, 524: 012002. DOI: 10.1088/1742-6596/524/1/012002
    [53]
    ZONG H H, PORTÉ-AGEL F. A point vortex transportation model for yawed wind turbine wakes[J]. Journal of Fluid Mechanics, 2020, 890: A8. DOI: 10.1017/jfm.2020.123
    [54]
    BASTANKHAH M, PORTÉ-AGEL F. Experimental and theoretical study of wind turbine wakes in yawed conditions[J]. Journal of Fluid Mechanics, 2016, 806: 506-541. DOI: 10.1017/jfm.2016.595
    [55]
    HOWLAND M F, BOSSUYT J, MARTÍNEZ-TOSSAS L A, et al. Wake structure in actuator disk models of wind turbines in yaw under uniform inflow conditions[J]. Journal of Renewable and Sustainable Energy, 2016, 8(4): 043301. DOI: 10.1063/1.4955091
    [56]
    MARTÍNEZ-TOSSAS L A, ANNONI J, FLEMING P A, et al. The aerodynamics of the curled wake: a simplified model in view of flow control[J]. Wind Energy Science, 2019, 4(1): 127-138. DOI: 10.5194/wes-4-127-2019
    [57]
    MARTÍNEZ-TOSSAS L A, KING J, QUON E, et al. The curled wake model: a three-dimensional and extremely fast steady-state wake solver for wind plant flows[J]. Wind Energy Science, 2021, 6(2): 555-570. DOI: 10.5194/wes-6-555-2021
    [58]
    JIMÉNEZ Á, CRESPO A, MIGOYA E. Application of a LES technique to characterize the wake deflection of a wind turbine in yaw[J]. Wind Energy, 2010, 13(6): 559-572. DOI: 10.1002/we.380
    [59]
    SHAPIRO C R, GAYME D F, MENEVEAU C. Modelling yawed wind turbine wakes: a lifting line approach[J]. Journal of Fluid Mechanics, 2018, 841: R1. DOI: 10.1017/jfm.2018.75
    [60]
    QIAN G W, ISHIHARA T. A new analytical wake model for yawed wind turbines[J]. Energies, 2018, 11(3): 665. DOI: 10.3390/en11030665
    [61]
    BRUGGER P, DEBNATH M, SCHOLBROCK A, et al. Lidar measurements of yawed-wind-turbine wakes: characterization and validation of analytical models[J]. Wind Energy Science, 2020, 5(4): 1253-1272. DOI: 10.5194/wes-5-1253-2020
    [62]
    BRANLARD E, GAUNAA M. Cylindrical vortex wake model: skewed cylinder, application to yawed or tilted rotors[J]. Wind Energy, 2016, 19(2): 345-358. DOI: 10.1002/we.1838[LinkOut]
    [63]
    VOLLMER L, STEINFELD G, HEINEMANN D, et al. Estimating the wake deflection downstream of a wind turbine in different atmospheric stabilities: an LES study[J]. Wind Energy Science, 2016, 1(2): 129-141. DOI: 10.5194/wes-1-129-2016
    [64]
    LISSAMAN P B S. Energy effectiveness of arbitrary arrays of wind turbines[J]. Journal of Energy, 1979, 3(6): 323-328. DOI: 10.2514/3.62441
    [65]
    KATIC I, HØJSTRUP J, JENSEN N O. A simple model for cluster efficiency[C]//European wind energy association conference and exhibition. 1986, 1: 407-410. https://backend.orbit.dtu.dk/ws/portalfiles/portal/106427419/A_Simple_Model_for_Cluster_Efficiency_EWEC_86_.pdf
    [66]
    NIAYIFAR A, PORTÉ-AGEL F. Analytical modeling of wind farms: a new approach for power prediction[J]. Energies, 2016, 9(9): 741. DOI: 10.3390/en9090741
    [67]
    VOUTSINAS S, RADOS K, ZERVOS A. On the analysis of wake effects in wind parks[J]. Wind Engineering, 1990, 14(4): 204-219. https://www.jstor.org/stable/43749429
    [68]
    ZONG H H, PORTÉ-AGEL F. A momentum-conserving wake superposition method for wind farm power prediction[J]. Journal of Fluid Mechanics, 2020, 889: A8. DOI: 10.1017/jfm.2020.77
    [69]
    BASTANKHAH M, PORTÉ-AGEL F. A new miniature wind turbine for wind tunnel experiments. part I: design and performance[J]. Energies, 2017, 10(7): 908. DOI: 10.3390/en10070908
    [70]
    FLEMING P, ANNONI J, CHURCHFIELD M, et al. A simulation study demonstrating the importance of large-scale trailing vortices in wake steering[J]. Wind Energy Science, 2018, 3(1): 243-255. DOI: 10.5194/wes-3-243-2018
    [71]
    FLEMING P, KING J, DYKES K, et al. Initial results from a field campaign of wake steering applied at a commercial wind farm – Part 1[J]. Wind Energy Science, 2019, 4(2): 273-285. DOI: 10.5194/wes-4-273-2019
    [72]
    FLEMING P, KING J, SIMLEY E, et al. Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2[J]. Wind Energy Science, 2020, 5(3): 945-958. DOI: 10.5194/wes-5-945-2020
    [73]
    KING J, FLEMING P, KING R, et al. Control-oriented model for secondary effects of wake steering[J]. Wind Energy Science, 2021, 6(3): 701-714. DOI: 10.5194/wes-6-701-2021
    [74]
    KNUDSEN T, BAK T, SVENSTRUP M. Survey of wind farm control—power and fatigue optimization[J]. Wind Energy, 2015, 18(8): 1333-1351. DOI: 10.1002/we.1760
    [75]
    PARK J, LAW K H. A data-driven, cooperative wind farm control to maximize the total power production[J]. Applied Energy, 2016, 165: 151-165. DOI: 10.1016/j.apenergy.2015.11.064
    [76]
    KIRCHNER-BOSSI N, PORTÉ-AGEL F. Wind farm area shape optimization using newly developed multi-objective evolutionary algorithms[J]. Energies, 2021, 14(14): 4185. DOI: 10.3390/en14144185
    [77]
    GEBRAAD P M O, VAN WINGERDEN J W. Maximum power‐point tracking control for wind farms[J]. Wind Energy, 2015, 18(3): 429-447. DOI: 10.1002/we.1706
    [78]
    GEBRAAD P, THOMAS J J, NING A, et al. Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control[J]. Wind Energy, 2017, 20(1): 97-107. DOI: 10.1002/we.1993
    [79]
    BROGNA R, FENG J, SØRENSEN J N, et al. A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain[J]. Applied Energy, 2020, 259: 114189. DOI: 10.1016/j.apenergy.2019.114189
    [80]
    KIRCHNER-BOSSI N, PORTÉ-AGEL F. Realistic wind farm layout optimization through genetic algorithms using a Gaussian wake model[J]. Energies, 2018, 11(12): 3268. DOI: 10.3390/en11123268
    [81]
    STANFEL P, JOHNSON K, BAY C J, et al. Proof-of-concept of a reinforcement learning framework for wind farm energy capture maximization in time-varying wind[J]. Journal of Renewable and Sustainable Energy, 2021, 13(4): 043305. DOI: 10.1063/5.0043091
    [82]
    SONG D R, FAN X Y, YANG J, et al. Power extraction efficiency optimization of horizontal-axis wind turbines through optimizing control parameters of yaw control systems using an intelligent method[J]. Applied Energy, 2018, 224: 267-279. DOI: 10.1016/j.apenergy.2018.04.114
    [83]
    BERNARDONI F, CIRI U, ROTEA M A, et al. Identification of wind turbine clusters for effective real time yaw control optimization[J]. Journal of Renewable and Sustainable Energy, 2021, 13(4): 043301. DOI: 10.1063/5.0036640
    [84]
    OZBAY A, TIAN W, YANG Z F, et al. Interference of wind turbines with different yaw angles of the upstream wind turbine[C]//42nd AIAA Fluid Dynamics Conference and Exhibit, New Orleans, Louisiana. Reston, Virginia: AIAA, 2012. doi: 10.2514/6.2012-2719
    [85]
    HANSEN K S, BARTHELMIE R J, JENSEN L E, et al. The impact of turbulence intensity and atmospheric stability on power deficits due to wind turbine wakes at Horns Rev wind farm[J]. Wind Energy, 2012, 15(1): 183-196. DOI: 10.1002/we.512
    [86]
    CAMPAGNOLO F, PETROVIĆ V, SCHREIBER J, et al. Wind tunnel testing of a closed-loop wake deflection controller for wind farm power maximization[J]. Journal of Physics: Conference Series, 2016, 753: 032006. https://iopscience.iop.org/article/ 10.1088/1742-6596/753/3/032006/pdf doi: 10.1088/1742-6596/753/3/032006
    [87]
    LIN M, PORTÉ-AGEL F. Power maximization and fatigue-load mitigation in a wind-turbine array by active yaw control: an LES study[J]. Journal of Physics: Conference Series, 2020, 1618: 042036. DOI: 10.1088/1742-6596/1618/4/042036
    [88]
    FLEMING P, ANNONI J, SCHOLBROCK A, et al. Full-scale field test of wake steering[J]. Journal of Physics: Conference Series, 2017, 854: 012013. DOI: 10.1088/1742-6596/854/1/012013
    [89]
    GEBRAAD P M O, TEEUWISSE F W, VAN WINGERDEN J W, et al. Wind plant power optimization through yaw control using a parametric model for wake effects—a CFD simulation study[J]. Wind Energy, 2016, 19(1): 95-114. DOI: 10.1002/we.1822
    [90]
    ROTT A, DOEKEMEIJER B, SEIFERT J K, et al. Robust active wake control in consideration of wind direction variability and uncertainty[J]. Wind Energy Science, 2018, 3(2): 869-882. DOI: 10.5194/wes-3-869-2018
    [91]
    MENDEZ REYES H, KANEV S, DOEKEMEIJER B, et al. Validation of a lookup-table approach to modeling turbine fatigue loads in wind farms under active wake control[J]. Wind Energy Science, 2019, 4(4): 549-561. DOI: 10.5194/wes-4-549-2019
    [92]
    KANEV S. Dynamic wake steering and its impact on wind farm power production and yaw actuator duty[J]. Renewable Energy, 2020, 146: 9-15. DOI: 10.1016/j.renene.2019.06.122
    [93]
    KANEV S K, SAVENIJE F J, ENGELS W P. Active wake control: an approach to optimize the lifetime operation of wind farms[J]. Wind Energy, 2018, 21(7): 488-501. DOI: 10.1002/we.2173
    [94]
    PARK J, KWON S, LAW K H. Wind farm power maximization based on a cooperative static game approach[C]//Proceedings of the SPIE, 2013, 8688. http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid = 418924BF2676423839D98C004A37CDB7?doi = 10.1.1.300.3939&rep = rep1&type = pdf doi: 10.1117/12.2009618
    [95]
    PARK J, LAW K H. Cooperative wind turbine control for maximizing wind farm power using sequential convex programming[J]. Energy Conversion and Management, 2015, 101: 295-316. DOI: 10.1016/j.enconman.2015.05.031
    [96]
    PARK J, LAW K H. Bayesian ascent: a data-driven optimization scheme for real-time control with application to wind farm power maximization[J]. IEEE Transactions on Control Systems Technology, 2016, 24(5): 1655-1668. DOI: 10.1109/TCST.2015.2508007
    [97]
    BAY C J, KING J, FLEMING P, et al. Unlocking the full potential of wake steering: implementation and assessment of a controls-oriented model[J]. Wind Energy Science Discussions, 2019: 1-20. DOI: 10.5194/wes-2019-19
    [98]
    王浩, 柯世堂, 王同光. 台风过境全过程大型风力机风荷载特性[J]. 空气动力学学报, 2020, 38(5): 915-923. doi: 10.7638/kqdlxxb-2019.0108

    WANG H, KE S, WANG T. Wind loads characteristic of large wind turbine considering typhoon transit process[J]. ACTA AERODYNAMICA SINICA, 2020, 38(5): 915-923. doi: 10.7638/kqdlxxb-2019.0108
  • Related Articles

    [1]MAO Meiliang, BAI Jinwei, MIN Yaobing, MA Yankai, JIANG Dingwu. Review on weighting functions of high-order nonlinear weighted methods[J]. ACTA AERODYNAMICA SINICA, 2024, 42(6): 1-14. DOI: 10.7638/kqdlxxb-2023.0187
    [2]WANG Yibin, MA Chenyang, LI Tong, ZHAO Ning, ZHU Chunling. Review of numerical studies on ship-helicopter coupled flowfield[J]. ACTA AERODYNAMICA SINICA, 2023, 41(3): 45-66. DOI: 10.7638/kqdlxxb-2022.0066
    [3]CHEN Xin, WANG Gang, YE Zheng Yin, WU Xiaojun. A review of uncertainty quantification methods for Computational Fluid Dynamics[J]. ACTA AERODYNAMICA SINICA, 2021, 39(4): 1-13. DOI: 10.7638/kqdlxxb-2021.0012
    [4]YANG Hailin, LIN Jianzhong. Review of turbulent fluctuation effect on nano-particle two-phase flow system[J]. ACTA AERODYNAMICA SINICA, 2021, 39(3): 109-120. DOI: 10.7638/kqdlxxb-2021.0030
    [5]WU Qin, GUO Yimeng, LIU Yunqing, WANG Guoyu. Review on the cavitating flow-induced vibrations[J]. ACTA AERODYNAMICA SINICA, 2020, 38(4): 746-760. DOI: 10.7638/kqdlxxb-2019.0177
    [6]ZHANG Qingyun, WANG Zhenghua, WEI Meng, LIN Wenjie. Review of high-lift devices design for amphibious aircraft[J]. ACTA AERODYNAMICA SINICA, 2019, 37(1): 19-32. DOI: 10.7638/kqdlxxb-2017.0110
    [7]SHEN Junmou, CHEN Xing, BI Zhixian, MA Handong. Review on experimental technology of high enthalpy shock tunnel[J]. ACTA AERODYNAMICA SINICA, 2018, 36(4): 543-554. DOI: 10.7638/kqdlxxb-2017.0165
    [8]ZHAI Jian, ZHANG Weiwei, WANG Huanling. Reviews of forebody vortex control method at high angles of attack[J]. ACTA AERODYNAMICA SINICA, 2017, 35(3): 354-367. DOI: 10.7638/kqdlxxb-2017.0018
    [9]ZHAO Huiyong, YI Miaorong. Review of design for forced-transition trip of hypersonic inlet[J]. ACTA AERODYNAMICA SINICA, 2014, 32(5): 623-627. DOI: 10.7638/kqdlxxb-2014.0095
    [10]TANG Ji-wei, HU Yu, SONG Bi-feng. Advances in the aerodynamics research of cylcoidal propeller[J]. ACTA AERODYNAMICA SINICA, 2013, 31(5): 676-684. DOI: 10.7638/kqdlxxb-2013.0054

Catalog

    Article views (1292) PDF downloads (232) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return