Yawing and performance of an offshore wind farm

Similar documents
Yawing and performance of an offshore wind farm

Power curves - use of spinner anemometry. Troels Friis Pedersen DTU Wind Energy Professor

Measurement of rotor centre flow direction and turbulence in wind farm environment

Improvement of Wind Farm Performance by Means of Spinner Anemometry

Spinner Anemometry Pedersen, T.F.; Sørensen, Niels; Madsen, H.A.; Møller, R.; Courtney, M.; Enevoldsen, P.; Egedal, P.

Wake measurements from the Horns Rev wind farm

Study on wind turbine arrangement for offshore wind farms

WIND DIRECTION ERROR IN THE LILLGRUND OFFSHORE WIND FARM

Wake effects at Horns Rev and their influence on energy production. Kraftværksvej 53 Frederiksborgvej 399. Ph.: Ph.

Evaluation of wind flow with a nacelle-mounted, continuous wave wind lidar

Calibration of a spinner anemometer for wind speed measurements

THE HORNS REV WIND FARM AND THE OPERATIONAL EXPERIENCE WITH THE WIND FARM MAIN CONTROLLER

MULTI-WTG PERFORMANCE OFFSHORE, USING A SINGLE SCANNING DOPPLER LIDAR

Summary of the steps involved in the calibration of a Spinner anemometer

Determination of optimal wind turbine alignment into the wind and detection of alignment changes with SCADA data

Executive Summary of Accuracy for WINDCUBE 200S

Analysis of Traditional Yaw Measurements

A NOVEL FLOATING OFFSHORE WIND TURBINE CONCEPT: NEW DEVELOPMENTS

Calibration of a spinner anemometer for wind speed measurements

EERA DTOC wake results offshore

Control Strategies for operation of pitch regulated turbines above cut-out wind speeds

CORRELATION EFFECTS IN THE FIELD CLASSIFICATION OF GROUND BASED REMOTE WIND SENSORS

European wind turbine testing procedure developments. Task 1: Measurement method to verify wind turbine performance characteristics

Impact on wind turbine loads from different down regulation control strategies

Wakes in very large wind farms and the effect of neighbouring wind farms

3D Turbulence at the Offshore Wind Farm Egmond aan Zee J.W. Wagenaar P.J. Eecen

Increased Project Bankability : Thailand's First Ground-Based LiDAR Wind Measurement Campaign

WESEP 594 Research Seminar

THE CORRELATION BETWEEN WIND TURBINE TURBULENCE AND PITCH FAILURE

Modelling of Wind Turbine Loads nearby a Wind Farm

The DAN-AERO MW Experiments Final report

An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects

Measured wake losses By Per Nielsen

Influence of the Number of Blades on the Mechanical Power Curve of Wind Turbines

Analyses of the mechanisms of amplitude modulation of aero-acoustic wind turbine sound

Modeling large offshore wind farms under different atmospheric stability regimes with the Park wake model

Measurement and simulation of the flow field around a triangular lattice meteorological mast

Nanortalik A preliminary analysis of the wind measurements rev 1

Comparing the calculated coefficients of performance of a class of wind turbines that produce power between 330 kw and 7,500 kw

Wind turbine power performance verification in complex terrain and wind farms

Wind Farm Blockage: Searching for Suitable Validation Data

2 Asymptotic speed deficit from boundary layer considerations

Deep Sea Offshore Wind Power R&D Seminar Trondheim, Jan. 2011

Supplement of Wind turbine power production and annual energy production depend on atmospheric stability and turbulence

Torrild - WindSIM Case study

LIDAR Correlation to Extreme Flapwise Moment : Gust Impact Prediction Time and Feedforward Control

Measuring power performance with a Wind Iris 4- beam in accordance with EUDP procedure

3D Nacelle Mounted Lidar in Complex Terrain

Meteorological Measurements OWEZ

Influence of wind direction on noise emission and propagation from wind turbines

Meteorological Measurements OWEZ

VINDKRAFTNET MEETING ON TURBULENCE

BENCHMARKING OF WIND FARM SCALE WAKE MODELS IN THE EERA - DTOC PROJECT

Correlation of amplitude modulation to inflow characteristics

Energy from wind and water extracted by Horizontal Axis Turbine

Computationally Efficient Determination of Long Term Extreme Out-of-Plane Loads for Offshore Turbines

Flow analysis with nacellemounted

DAN-AERO MW: Detailed aerodynamic measurements on a full scale MW wind turbine

Wind farm production estimates

Steady State Comparisons HAWC2 v12.5 vs HAWCStab2 v2.14: Integrated and distributed aerodynamic performance

Concept Testing of a Simple Floating Offshore Vertical Axis Wind Turbine

PROJECT CYCLOPS: THE WAY FORWARD IN POWER CURVE MEASUREMENTS?

7. Project summary. Doc. nr file 10/3240 2/13

Windar Photonics Wind Sensor. Great at Control

Wind Turbine Noise Measurements How are Results influenced by different Methods of deriving Wind Speeds? Sylvia Broneske

Pressure distribution of rotating small wind turbine blades with winglet using wind tunnel

7 th International Conference on Wind Turbine Noise Rotterdam 2 nd to 5 th May 2017

APPLICATION OF RESEARCH RESULTS AT LM WIND POWER

Analysis of long distance wakes of Horns Rev I using actuator disc approach

EERA DTOC wake results offshore

FINO1 Mast Correction

Available online at ScienceDirect. Energy Procedia 53 (2014 )

Wind Resource Assessment for FALSE PASS, ALASKA Site # 2399 Date last modified: 7/20/2005 Prepared by: Mia Devine

Wind Resource Assessment Østerild National Test Centre for Large Wind Turbines

Load validation and comparison versus certification approaches of the Risø Dynamic Wake Meandering model implementation in GH Bladed

COMPARISON OF ZEPHIR MEASUREMENTS AGAINST CUP ANEMOMETRY AND POWER CURVE ASSESSMENT

Rotor equivalent wind speed for power curve measurement comparative exercise for IEA Wind Annex 32

The Park2 Wake Model - Documentation and Validation

Validation of long-range scanning lidars deployed around the Høvsøre Test Station

Why does T7 underperform? Individual turbine performance relative to preconstruction estimates.

TOPICS TO BE COVERED

Full scale experimental analysis of extreme coherent gust with wind direction changes (EOD)

Wind turbine noise at neighbor dwellings, comparing calculations and measurements

PRESSURE DISTRIBUTION OF SMALL WIND TURBINE BLADE WITH WINGLETS ON ROTATING CONDITION USING WIND TUNNEL

Comparison of upwind and downwind operation of the NREL Phase VI Experiment

LES* IS MORE! * L ARGE E DDY S IMULATIONS BY VORTEX. WindEnergy Hamburg 2016

The EllipSys2D/3D code and its application within wind turbine aerodynamics

Calibration of wind direction sensors at Deutsche WindGuard Wind Tunnel Services GmbH

Wind Regimes 1. 1 Wind Regimes

Bankable Wind Resource Assessment

Characterisation and Classification of RISØ P2546 Cup Anemometer

Evaluation of the wind direction uncertainty and its impact on wake modeling at the Horns Rev offshore wind farm

Accounting for the speed shear in wind turbine power performance measurement

Effect of wind flow direction on the loads at wind farm. Romans Kazacoks Lindsey Amos Prof William Leithead

Rotor Average wind speed for power curve performance. Ioannis Antoniou (LAC), Jochen Cleve (LAC), Apostolos Piperas (LAC)

Wind Farm Power Performance Test, in the scope of the IEC

Wind shear and its effect on wind turbine noise assessment Report by David McLaughlin MIOA, of SgurrEnergy

Alstom Ocean Energy Path towards Industrailsation. Ken Street 18 th April 2013

REMOTE SENSING APPLICATION in WIND ENERGY

Deepwind - an innovative wind turbine concept for offshore

Transcription:

Yawing and performance of an offshore wind farm Troels Friis Pedersen, Julia Gottschall, Risø DTU Jesper Runge Kristoffersen, Jan-Åke Dahlberg, Vattenfall Contact: trpe@risoe.dtu.dk, +4 2133 42 Abstract Optimization of yaw misalignment may improve energy output of wind farms. An analysis was made of the potential power loss of the Horns Reef wind farm due to yaw error. The method for the estimate was to measure the yaw error on an identical V8 onshore wind turbine and to extrapolate these findings to all turbines in the wind farm. The yaw errors were measured to be significant, and in average about 1 on the onshore V8 turbine. The flow inclination angle was measured to be significantly influenced by wake rotation from the neighboring wind turbines. The average power loss factor in the wind speed range 3-1m/s was found to be,971. Adjusting for a realistic yaw error interval the estimated power loss was 2,7%. When considering the wind distribution at the Horns Reef site and only considering the power below rated wind speed we end up with an estimated power loss of 1,6%, which corresponds to the production from 1,3 wind turbines in the Horns Reef wind farm. Objectives The objectives of this paper are to estimate the yawing errors and performance losses of the wind turbines in a wind farm. The target wind farm is the offshore Horns Rev wind farm west of Esbjerg, which consists of 8 Vestas V8 2MW wind turbines that have been in operation since 22. Methods The method for estimation of yaw errors and performance losses on Horns Rev wind farm are based on measurements and analysis on one onshore V8 wind turbine, configured exactly like the wind turbines at Horns Rev wind farm. The onshore wind turbine is located as turbine no in a small wind farm of 8 wind turbines at Tjæreborg, see Figure 2, all of the same size as the V8 wind turbine. Coordinates of the wind farm together with the met mast 1,D southwest of the V8 wind turbine are shown in Figure 3, and data for the wind farm are shown in Table 1. The inflow to the rotor centre is measured with a spinner anemometer [1-4], see Figure 1, on V8 wind turbine no. The output of the spinner anemometer is the local wind speed at the spinner nose, the yaw error and the flow inclination angle. The yaw error was calibrated by yawing the wind turbine in and out of the wind ±6. The wind speed was calibrated relative to the met mast with a stopped rotor. In this way the spinner anemometer measures the actual flow wind speed and direction at the spinner. During operation the rotor induces a wind speed at the spinner, so that the spinner anemometer no longer measures the free wind speed. Figure 4 shows the spinner anemometer wind speed relative to the met mast cup anemometer on the boom in the 247 wind direction from the open sector 212-22 during operation. It is clearly seen that the spinner anemometer wind speed is reduced in the range 4-12m/s. The induced wind speed in the rotor centre is quantified by the induction factor as shown in Figure. The induction factor is seen to have a maximum value of about 12%. The ratio between the spinner anemometer and the hub height cup anemometer is shown in Figure 6 for all directions for half a year of measurements. In this figure the wakes of the 1

turbines on the mast measurements and on the spinner anemometer measurements are indicated by the colored labels. Two open sectors, where both turbine and the met mast see free flow, are identified: 212-22 and 32-3. The wakes of the closest turbine no 6 on turbine in the direction 21 and on the mast in the direction 173 is clearly seen, as well as the wakes from the other turbines. Figure 1 Spinner anemometer mounted on V8 turbine no Figure 2 Tjæreborg wind farm site 6143 Tjareborg site layout Table 1 Relative distances and directions North coordinate 6141 1 3 61449 2 61447 4 6144 61443 61441 61439 mast 7 6 8 4732 4734 4736 4738 474 4742 4744 4746 4748 East coordinate Figure 3 Positions of turbines and mast Turb Mast WT # Distance to WT # (xd of V8) Direction to WT # (deg) 1 1,9 291 2 11,3 27 3 6,3 291 4 7, 26, - 6 3,2 21 7 4,3 11 8,4 147 Distance to met mast (xd of V8) Direction to met mast 1 9,8 297 2 1, 279 3,3 32 4,6 27 1, 67 6 2,3 173 7, 1 8,8 132 2 Spinner anemometer vs cup, operation in sector 212-22deg,3 Wind speed induction factor at rotor centre 212-22deg 18,2 Spinner anemometer (m/s) 16 14 12 1 8 6 4 Induction (Cup-Spinner/Cup),2,1,1,, 2 -, 2 4 6 8 1 12 14 16 18 2 Cup247 (m/s) -,1 2 4 6 8 1 12 14 16 18 2 Cup247 (m/s) Figure 4 Spinner wind speed relative to cup Figure Induction factor at rotor centre 2

Results of yaw error and flow inclination angle measurements The yaw error measurements for a two month period with the spinner anemometer are shown in Figure 7. The average yaw error is almost 1 and the spreading of data is about. Only for one wind direction, which is in the wake of turbine 6, the yaw error is spreading more, from -1 to 14. Ratio Spin-anem/Cup247 Wind speed ratio Spin-anem/Cup247 3, 2,8 2,6 2,4 2,2 2, 1,8 1,6 1,4 1,2 1,,8,6,4,2, 3 6 9 12 1 18 21 24 27 3 33 36,891868621 wt 1 to wt wt 2 to wt wt 3 to wt wt 4 to wt wt 6 to wt wt 1 to mast wt 2 to mast wt 3 to mast wt 4 to mast wt to mast wt 6 to mast wt 7 to mast wt 8 to mast Figure 6 Spinner anemometer wind speed relative to cup wind speed from various directions 2 Yaw error 1 Yaw error (deg) 1 - -1 Yaw error wt 1 to wt wt 2 to wt wt 3 to wt wt 4 to wt wt 6 to wt -1-2 3 6 9 12 1 18 21 24 27 3 33 36 Figure 7 Yaw error measurements from various directions 3

2 Flow inclination angle 1 Flow inclination angle (deg) 1 - -1-1 Flow inc angle wt 1 to wt wt 2 to wt wt 3 to wt wt 4 to wt wt 6 to wt -2 3 6 9 12 1 18 21 24 27 3 33 36 Figure 8 Flow inclination measurements from various directions The flow inclination angle is shown in Figure 8. From most of the directions the flow inclination angle is between and. A dramatic change of inflow angle is seen in the wake of turbine 6. At 192 the inflow angle is almost 14 while at 27 the inflow angle is -13. Between these points there is a linear change of inflow angle. This inflow angle pattern is due to the rotation of the wake of turbine 6. The wake rotation from turbine 6 is opposite the rotation direction of the rotor. This corresponds well with the measurements. Power loss estimate of onshore V8 turbine The estimate of the power loss due to yaw error is estimated using the following assumptions. First, it is assumed that the power is proportional to the cosine squared of the yaw angle. Second, the power loss is only considered relevant in the wind speed range from 4m/s to 12m/s. Above 12m/s the power is regulated down so a power loss is taking place anyway. Third, it is assumed the power can be improved by better yawing having zero yaw error. This is, however, not a realistic assumption. In practice the yaw error can be targeted to be within ±, in which case the power loss is maximum,4%, and if it is spreading equally over the range the average is,2%. The power loss factor is calculated from the yaw error measurements in Figure 8 and is shown in Figure 9. The power loss factor is seen to vary from 1. down to about.93. The average power loss factor of all data is,971. This corresponds to a power loss due to yaw error of 2,9%. If we extract the,2% due to the targeted yaw error range we get 2,7% power loss. 4

1,2 Power loss factor 1,,98 Power loss factor,96,94,92,9,88,86,84 Ploss factor wt 1 to wt wt 2 to wt wt 3 to wt wt 4 to wt wt 6 to wt,82,8 3 6 9 12 1 18 21 24 27 3 33 36 Figure 9 Power loss factor of onshore V8 turbine in the wind speed range 4-12m/s Power loss estimate of Horns Reef wind farm The Horns Reef wind farm has been operated for several years and a database of SCADA data has been gathered. These data consists of power data, nacelle wind speed and wind direction data, and yawing direction data. A parametric analysis was made based on yawing directions, and position of the turbines in the wind farm. The yawing directions showed quite large variations, indicating that yaw errors could be significant. For one whole day of production with a good wind from the west (26/8-2) the average power and yaw direction of each of the 8 turbines was determined. The average power of each turbine is shown if Figure 1 as function of the deviation in yaw direction from the overall average yaw direction. The front row turbines in the top of the plot are seen to have a significant higher production than the rest. If the rest of the turbines were having yaw errors corresponding to these variations then the power would be visibly reduced, following the cos 2 law, for the turbines having large yaw errors (apparent yaw error). From Figure 1 it can be seen that this is not the case. The large variations in yaw direction are not due to yaw errors. It may be assumed that they are due to the yaw direction sensors not being calibrated relative to each other. This is confirmed when looking at longer term statistics. 14 Average power versus apparent yaw error 26/8-2 data 12 Average power (kw) 1 8 6 4 Turbine cos 2-3 -2-1 1 2 3 Apparent yaw error (deg) Figure 1 One day average power versus apparent yaw error in Horns Reef wind farm

In estimating the power loss of the Horns Reef wind farm due to yawing error the V8 onshore measurements can be used. We then have to make further assumptions. First, we assume all turbines to have the same amount of yaw error as the V8 onshore turbine. Second, we assume that power losses are only relevant for the 3-1m/s wind speed range. For the wind distribution at Horns Reef we can assume that about 6% of the power production should be considered in the power loss model. We thus end up with an estimate of 1,6% power loss of the wind farm due to yaw errors. This corresponds to the production from 1,3 wind turbines. Conclusions An analysis was made of the potential power loss of the Horns Reef wind farm due to yaw error. The yaw errors on an identical V8 onshore wind turbine were measured to be significant, and in average about 1. The flow inclination angle was measured to be significantly influenced by wake rotation from the neighboring wind turbines. The average power loss factor in the wind speed range 3-1m/s was found to be,971. Adjusting for a realistic yaw error interval the estimated power loss for the wind speed range was found to 2,7%. Considering the wind distribution at the Horns Reef site and only considering power below rated wind speed then an estimated power loss of 1,6% was found. This corresponds to the production from 1,3 wind turbines. References 1. Pedersen TF, Madsen HA, Møller R, Courtney, M, Sørensen NN, Enevoldsen P, Egedal P, Spinner Anemometry An Innovative Wind Measurement Concept, EWEC27 Milan 2. Pedersen TF, Sørensen N, Enevoldsen P, "Aerodynamics and Characteristics of a Spinner Anemometer", International conference: The science of making torque from wind, Lyngby (DK), 28-31 Aug 27J. Phys.: Conf. Ser. 7 1218 (9pp) 3. Pedersen TF, Vita L, Sørensen NN, Enevoldsen P, Operational Experiences with a Spinner Anemometer on a MW Size Wind Turbine, EWEC28, Bruxelles 4. Pedersen TF, Vita L, Sørensen NN, Enevoldsen P, Optimization of Wind Turbine Operation by Use of Spinner Anemometer, Risø-R-164(EN), 28 6