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FARMOPT: WIND TURBINE WAKE MEASUREMENT IN COMPLEX TERRAIN Kurt S. Hansen et al. Mail: [email protected]

FARMOPT: WIND TURBINE WAKE MEASUREMENT IN COMPLEX … · 2020. 2. 5. · DTU Wind Energy, Technical University of Denmark Objectives FarmOpt 3 VindKraftnet meeting 13. May 2018 •Development

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  • FARMOPT: WIND TURBINE WAKE MEASUREMENT IN COMPLEX TERRAIN

    Kurt S. Hansen et al.

    Mail: [email protected]

  • DTU Wind Energy, Technical University of Denmark

    Outline

    • Objectives for FarmOpt;

    • Data overview, site description, windfarm layout and measurement setup;

    • Tower bending;

    – Calibration;

    – Thrust coefficient validation;

    – Fatigue loads;

    • SCADA data qualification;

    • 360 deg power polars;

    – Power deficits;

    – Discussion of terrain & wake effects;

    • Single near wake analysis

    – Wake identifications including visualizations;

    • Summary;

    • Acknowledgements;

    • Perdigao wake measurements

    2 13. May 2018VindKraftnet meeting

  • DTU Wind Energy, Technical University of Denmark

    Objectives FarmOpt

    3 VindKraftnet meeting 13. May 2018

    • Development of wind farm optimization tools for optimally placing wind turbines in wind farms located in complex terrain.

    • Requirement: full scale measurements from wind farms in complex terrain for software verification.

    • The focus are the SCADA data, wind and load measurements obtained from a wind farm - located in complex terrain.

  • DTU Wind Energy, Technical University of Denmark

    Field measurements from the wind farm – located in complex terrain

    • SCADA data from 25 wind turbines (12 months);

    – Difficult to qualify the data;

    – Icing problems during winter;

    – Determination of ambient inflow conditions;

    • 10-minute statistics from 2 x 70 m masts (12 months);

    – Cup, vanes, temp & pressure;

    • High simpled data (~7 months);

    – 3-D sonic data

    Vertical wind speed, turbulence;

    Atmospheric stability;

    – Tower bending (Thrust)Lack of calibration

    4 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark

    Location of Shaanxi wind farm, close to Jingbian (close to Inner Mongolia)

    5 VindKraftnet meeting 13. May 2018

    Shaanxi WF

    ~300 km N of Xi’an

    ~700 km SE of Beijing

  • DTU Wind Energy, Technical University of Denmark6 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark

    25 wind turbines - in complex terrain

    7 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark

    Inflow from N is not complex – but!

    Photos from a site visit

    8 VindKraftnet meeting 13. May 2018

    SE

    S

    SW

  • DTU Wind Energy, Technical University of Denmark

    Wind turbines

    9 VindKraftnet meeting 13. May 2018

    Type: 25 x H93/CSIC

    Rated power: 2.0 MW

    Diameter: 93 m

    Hub height: 67 m

    Control: VS & VP

    Info: Power & CT curves

  • DTU Wind Energy, Technical University of Denmark

    Tower bending

    10 VindKraftnet meeting 13. May 2018

    Preferred Theoretical Backup Iterative

  • DTU Wind Energy, Technical University of Denmark

    Calibration of CT-coefficient

    11 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark

    Thrust for westerly inflow (slope sector)

    12 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark

    Tower bending

    13 VindKraftnet meeting 13. May 2018

    Free inflow

    Free inflow

    Slope inflow

    Slope inflow

  • DTU Wind Energy, Technical University of Denmark

    Wind farm analysis – SCADA data

    • Data qualification (filtering)

    – Start/stop

    – Parked/idling

    – Curtailment

    – Calibration (yaw positions)

    – Calculate equivalent rotor wind speed (PC & PA vs U)

    • Park efficiency depends on

    – Inflow conditions (speed, direction)

    – Terrain complexity

    – Local wake effects

    14 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark

    Inflow conditions (speed,direction)

    15 VindKraftnet meeting 13. May 2018

    • Difficult to establish robust inflow conditions;

    • “Disturbing” turbines next to the wind farm;

    • Yaw position should be calibrated before use;

    • Assumption about the power curve validity.

  • DTU Wind Energy, Technical University of Denmark16 VindKraftnet meeting 13. May 2018

    Benchmarks

  • DTU Wind Energy, Technical University of Denmark17 VindKraftnet meeting 13. May 2018

    Benchmarks

  • DTU Wind Energy, Technical University of Denmark

    Wind farm layout, spacing 4 - 8 Diameters

    18 VindKraftnet meeting 13. May 2018

    Maximum wake deficit, for 4, 5, 6 & 7D spacing.

    Other pairs with viz. wake deficit.

  • DTU Wind Energy, Technical University of Denmark

    Definition of power deficit = 1 – power ratio = 1 – Pwake/Pfree

    Wake deficit distribution in-side the wind farm, winddir: W => E;

    19 VindKraftnet meeting 13. May 2018

    Maximum deficit

  • DTU Wind Energy, Technical University of Denmark20 VindKraftnet meeting 13. May 2018

    wt10/wt08

    wt25/wt21

  • DTU Wind Energy, Technical University of Denmark

    Discussion of wind farm park effects.

    • Western inflow:

    – Narrow sectors are characterized with low power variability;

    – Wake deficit distributions between pairs of single turbines can beidentified;

    – Wake effects can be identified in the power polars;

    • Eastern inflow:

    – No distinct wake deficit between turbines can be identified;

    – The large variability in the power signals seems to be causedby terrain effects;

    – More scada is needed before a firm conclusion can be made.

    21 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark22 VindKraftnet meeting 13. May 2018

    Single wind turbine wake analysis (wt14)

  • DTU Wind Energy, Technical University of Denmark

    Single wind turbine wake analysis (wt14)

    23 VindKraftnet meeting 13. May 2018

    SN

    2.2D 1.4 D

    M1

    M3

    wt14

  • DTU Wind Energy, Technical University of Denmark24 VindKraftnet meeting 13. May 2018

    SWSE

    Spacing 2.2D

    Wake analysis (wt14), WD=SE-S-SW

  • DTU Wind Energy, Technical University of Denmark

    Turbulence in wake (wt14)

    25 VindKraftnet meeting 13. May 2018

    Measured on mast

    Ti calculated with reference to ambient wind speed

  • DTU Wind Energy, Technical University of Denmark26 VindKraftnet meeting 13. May 2018

    NW NE

    Spacing 1.4D

    Wake analysis (wt14), WD=NW-N-NE

  • DTU Wind Energy, Technical University of Denmark

    Deficit & turbulence in double wakes

    27 VindKraftnet meeting 13. May 2018

    TI

    TIM1

    M3

    wt12 wt14

  • DTU Wind Energy, Technical University of Denmark

    Deficit in double wakes

    28 VindKraftnet meeting 13. May 2018

    ~5D spacing

    ~1.4D spacing

  • DTU Wind Energy, Technical University of Denmark

    Turbulence in double wakes

    29 VindKraftnet meeting 13. May 2018

    ~5D spacing

    ~1.4D spacing

  • DTU Wind Energy, Technical University of Denmark

    Summary

    • A database with 10-minute measurements representing 1 YR has been established.

    – Wind speed @ 3 different levels on 2 masts

    – Wind direction, temperatures and atmospheric pressure.

    • A database with 1 minute and 10-minute statistics of SCADA data for 25 wind turbines representing 1 YR of operation has been established.

    – Active power, Pitch, Rotor speed, Yaw position and Nacelle wind speed

    – Rotor equivalent wind speed

    • A database with 10-minute statistics for 35 Hz time series representing ½ YR has been established.

    – Signals and derived signal representing 3 x 3D sonics

    – Tower bending TBx, Tby, TBF-A and Thrust.

    30 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark

    Literature

    31 VindKraftnet meeting 13. May 2018

    CFD Simulations of Flows in a Wind Farm in Complex Terrain and Comparisons to Measurements

    Sessarego M, Shen WZ, Maarten PVL, Hansen KS, Zhu WJ.

    Appl. Sci. 2018, 8(5), 788; https://doi.org/10.3390/app8050788

  • DTU Wind Energy, Technical University of Denmark

    Acknowledgements

    32 VindKraftnet meeting 13. May 2018

    Co-authors

    Gunner C. Larsen1, Ju Feng1, Andrea Vignaroli1, Wei Jun Zhu1, Wei Liu2, Chang Xu3 and Wen Z. Shen1,1 Department of Wind Energy, Technical University of Denmark2 North West Survey and Design Institute Hydro China Consultant Corporation (NWI), Xi’an, China3 Hohai University, Nanjing, China

    Farmopt was funded by the Energy Technology Development and Demonstration Program in 2013 (EUDP).

  • DTU Wind Energy, Technical University of Denmark

    Perdigão experiment

    33 VindKraftnet meeting 13. May 2018

    2 MW Wind turbine

    Location of 40m mast Jan 2002–Dec 2004

  • DTU Wind Energy, Technical University of Denmark

    Objectives of the Perdigão experiment

    To perform an experimental investigation of the flow over a double ridge using two sets of synchronized LiDAR systems (SR & LR windscanners).

    34 VindKraftnet meeting 13. May 2018

    High quality field data for model validation is obtained for use to investigate:

    I. Wind resources in complex terrain and hazardous events (NEWA project)

    II. Inflow conditions for wind turbines in complex terrain (UniTTe & FarmOpt projects)

    III.Wind turbine wakes in complex terrain (FarmOptproject)

  • DTU Wind Energy, Technical University of Denmark

    Perdigão site: wind turbine located on a ridge.

    35 VindKraftnet meeting 13. May 2018

    Summit heights 500-550 m

    Terrain flats out towards SW and NE

    Terrain coverage irregular (forest patches of eucalyptus and pine trees)

    SW NE

  • DTU Wind Energy, Technical University of Denmark

    Diamond scan for a horizontal, inclined plane, (obtained by 2 x long-range (LR) windscanners)

    36 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark

    LR Windscanner examples

    37 VindKraftnet meeting 13. May 2018

    LONGwake

    SHORT wake

  • DTU Wind Energy, Technical University of Denmark

    Vertical near wake scanning at 1D spacing, (obtained with 3 x short-range (SR) wind scanners)

    38 VindKraftnet meeting 13. May 2018

    WakeDOWN

    WakeUP

  • DTU Wind Energy, Technical University of Denmark

    Diurnal cycle analysis of identified wake cases.

    39 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark40 VindKraftnet meeting 13. May 2018

    Example of wake speed ratio distributions

  • DTU Wind Energy, Technical University of Denmark

    Summary of the single wake analysis

    41 VindKraftnet meeting 13. May 2018

    • No overlapping periods for the SR & LR windscanners.

    • Limited number of interesting wake periods due to the narrow inflow sector (10⁰);

    • The wake behaviour seems to correlate with the vertical wind speed.

    • The stability effects seems to determine the wake characteristics (eg. extension, position, dissipation);

  • DTU Wind Energy, Technical University of Denmark

    Conclusion

    • Near wake behaviour can be derived from windscanner measurements;

    • The vertical position of the near wake seems to move:

    – Down-hill during nighttime (summer);

    – Up-hill during daytime (summer);

    • The terrain complexity combined with the ambient turbulence, determines the how the wind turbine wake dissipates.

    42 VindKraftnet meeting 13. May 2018

  • DTU Wind Energy, Technical University of Denmark

    Literature

    43 VindKraftnet meeting 13. May 2018

    Does the wind turbine wake follow the topography?

    A multi-lidar study in complex terrain.

    Menke R,Vasiljevic N,Hansen KS, Hahmann AH, Mann J

    Wind Energ. Sci., 3, 681–691, 2018

    https://doi.org/10.5194/wes-3-681-2018

  • DTU Wind Energy, Technical University of Denmark

    Acknowledgements - Perdigão experiment

    44 VindKraftnet meeting 13. May 2018

    Co-authors

    Gunner C. Larsen1, Robert Menke1, Nikola Vasiljevicv, Nikolas Angelou1

    1 Department of Wind Energy, Technical University of Denmark

    Farmopt was funded by the Energy Technology Development and Demonstration Program in 2013 (EUDP), UniTTe was supported by The Danish Council for Strategic Research (DSF) in 2013 and the New European Wind Atlas (NEWA) has been supported by the EUROPEAN COMMISSION.