farmopt: wind turbine wake measurement in complex … · dtu wind energy, technical university of...

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


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.


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



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


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


25 wind turbines - in complex terrain



Inflow from N is not complex – but!

Photos from a site visit


SE

S

SW


Wind turbines


Type: 25 x H93/CSIC

Rated power: 2.0 MW

Diameter: 93 m

Hub height: 67 m

Control: VS & VP

Info: Power & CT curves


Tower bending


Preferred Theoretical Backup Iterative


Calibration of CT-coefficient



Thrust for westerly inflow (slope sector)



Tower bending


Free inflow

Free inflow

Slope inflow

Slope inflow


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



Inflow conditions (speed,direction)


• 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.


Benchmarks


Wind farm layout, spacing 4 - 8 Diameters


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

Other pairs with viz. wake deficit.


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

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


Maximum deficit


wt10/wt08

wt25/wt21


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.



Single wind turbine wake analysis (wt14)


Single wind turbine wake analysis (wt14)


SN

2.2D 1.4 D

M1

M3

wt14


SWSE

Spacing 2.2D

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


Turbulence in wake (wt14)


Measured on mast

Ti calculated with reference to ambient wind speed


NW NE

Spacing 1.4D

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


Deficit & turbulence in double wakes


TI

TIM1

M3

wt12 wt14


Deficit in double wakes


~5D spacing

~1.4D spacing


Turbulence in double wakes


~5D spacing

~1.4D spacing


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.



Literature


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


Acknowledgements


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).


Perdigão experiment


2 MW Wind turbine

Location of 40m mast Jan 2002–Dec 2004


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).


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)


Perdigão site: wind turbine located on a ridge.


Summit heights 500-550 m

Terrain flats out towards SW and NE

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

SW NE


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



LR Windscanner examples


LONGwake

SHORT wake


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


WakeDOWN

WakeUP


Diurnal cycle analysis of identified wake cases.



Example of wake speed ratio distributions


Summary of the single wake analysis


• 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);


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.



Literature


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


Acknowledgements - Perdigão experiment


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.

farmopt: wind turbine wake measurement in complex … · dtu wind energy, technical university of...

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