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Horns Rev

Managed by

Data Provider: 

Kurt S. Hansen (DTU)

Data accesibility: 

The test case is offered to participants of the IEA Task 31 Wakebench and EU project EERA-DTOC Work Package 1.

Site Description: 

The Horns Rev wind farm (HR) has a shared ownership by Vattenfall AB (60%) and DONG Energy AS (40%). It is located 14 km from the west coast of Denmark, with a water depth of 6-14 m. The wind farm has a rated capacity of 160 MW comprising 80 wind turbines, which are arranged in a regular array of 8 by 10 turbines, with a spacing of 560 m in both directions covering an area of 5x3.8 km2. 

Figure1: Horns Rev wind farm, DK; Photographer: Christian Steiness. 12 February 2008 at 13.00 

(Hassager et al., 2013)

The layout of the wind farm (Figure 2) is not completely rectangular, while the direction of the N-S columns is 353°. The wind turbines are installed with an internal spacing along the main directions of 7D. The diagonal wind turbine spacing is either 9.4 D or 10.4 D. Figure 2 illustrates the location of the three offshore meteorological masts associated with the wind farm. Mast M2, with a height of 62 m, was installed prior to the wind farm installation to document the wind conditions. Two identical masts M6 and M7 were installed as part of the Horns Rev wind farm wake measurements program with a height equal to the hub height of 70 m. The wind farm comprises VESTAS V80 turbines, which are 2 MW pitch controlled, variable speed wind turbines with a diameter of 80 m and 70 m hub height. The wind farm has been in operation since 2004 and the SCADA statistics from 2005 – 2007 are available for the wake analysis described by Hansen et al. (2011a).

Figure 2: Layout of the Horns Rev offshore wind farm.

Instrumentation: 

The Horns Rev measurement systems have been in operation for several years, unfortunately not all instruments have been calibrated or quality controlled regularly.  A signal quality control has been necessary and some of the procedures presented in Hansen et al. (2011b) have been implemented to qualify the dataset. M2 has only been partly in operation after the wind farm installation.

Mast M6 & M7, height 70m: The instrumentation consists of high quality cup anemometers, vanes and thermometers for measuring wind speeds, wind directions and air and water temperatures. The instrumentation has been in operation since 2004 with annual calibration and inspections.

A number of channels have been extracted from the wind farm SCADA system and for categorizing the operational conditions and have been combined with the meteorological observations. The operational conditions for each wind turbine are described through: electrical power, rotor speed, pitch angle, yaw position, yaw misalignment and nacelle wind speed. The SCADA signals are supervised as part of the ordinary wind turbine supervision, but SCADA signal quality has never been addressed.

The meteorological measurements were recorded with stand-alone data acquisition systems and merged with the SCADA data. A number of derived signals have been determined including a classification of the atmospheric stability, based on wind speed and temperature measurements from M7 and the method described in Hansen et al. (2011c).

Measurement Campaign: 

The dataset for the current wake analysis was limited to three years, from 2005 to 2007, and comprises the SCADA data from the 80 wind turbines and the two downstream wake masts (M6 & M7). Due to the local wind rose, the wake analysis shall be concentrated to westerly and easterly inflow sectors centered at 270° and 90° respectively. Because M6 & M7 are located inside the wind farm wake for the 270° sector, a flow reference has been establish based on wt07 (located in the most western row of the wind farm) in terms of wind speed derived from electrical power and wind direction derived from the calibrated wind turbine yaw position.

For the western flow sector, the power curve of wt07 has been validated with wind speed measurements from M2, 62 m level (Hansen et al., 2011a). None of the wind turbine yaw position sensors have been calibrated while these are not used in the wind turbine control, but the yaw position offset for wt07 has been calibrated and found to be constant during the period, according to the guidelines in Hansen et al. (2011b). The estimated uncertainty of the wind direction is 5°.

For the eastern flow sector, the measured wind speed and wind directions have been recorded at 70 m level on both mast M6 or M7.

Signals used for the wake analysis in westerly sectors

  • Wind direction, h =70 m, for a westerly sector: is derived from the wind turbine wt07 yaw position.
  • Wind speed, h = 70 m, for a westerly sector: is derived from power signal of wind turbine wt07 combined with the verified power curve based on “a point” measurement of the wind speed.
  • Turbulence intensity, h = 70 m, for a westerly sector refers to mast M2 (h = 62 m) and has been measured during three years, prior to the wind farm installation as listed in Hansen et al. (2011a).

Both mean wind speed and turbulence are measured with a cup anemometer.

Definition of power deficit

  • For westerly inflow, the power deficit is determined with respect to the reference wt07: Power Deficit = (Pwt07 - Pwt)/Pwt07
  • For easterly inflow, the power deficit is determined with respect to the reference wt95: Power Deficit = (Pwt95 - Pwt)/Pwt95

Calculation of power deficit along row of turbines

The inflow conditions is determined in accordance with the wind speed and wind direction defined above:

  • The mean power for each wind turbine in the wind farm is determined after taking the data filtering into account defined in Hansen et al. (2011b);
  • The deficit is determined with reference to the mean power of the reference turbine wt07;
  • The mean power deficit is determined by averaging the results for row #2 - #7 as function of spacing (Figure 3).

Figure 3: The power deficit is determined, with reference to wt07 for the 
group of wind turbines limited by wt02, wt07, wt92 and wt97 along the rows 2-7.

Determination of power deficit versus wind direction

The measured power deficit is determined between wt17 and wt07 for a 40-50° inflow sector as illustrated in Figure 4.

Figure 4: Determination of power deficit versus wind direction (7 < V < 9 m/s).

Classification of the stability

The atmospheric stability at Horns rev offshore wind has been classified based on the Monin-Obukov (M-O) length according to Table 1. The M-O length is determined according to the Bulk-RI method as described in Hansen et al. (2011c),  by using the wind speed at 20 m level, absolute temperature at 16 m and water temperature at mast M7.

Table 1: Classification of atmospheric stability based on the Monin-Obukhov length.

Remarks:

Preliminary flow analysis of the Horns rev dataset has been reported as part of the EU-UPWINDproject (Hansen et al., 2011b).

References: 

EERA-DTOC; European Energy Research Alliance - Design Tool for Offshore Wind Farm Cluster 2012-2015; http://www.eera-dtoc.eu/

Hansen K., Barthelmie R.J., Jensen L., Sommer A., 2011a, The impact of turbulence intensity and atmospheric stability on power deficits due to wind turbine wakes at Horns Rev wind farm, Wind Energy, doe: 10.1002/we.512

Hansen K., et al., 2011b, Guideline to wind farm wake analysis. In UPWIND 1A2 Metrology, Final Report, Chapter 8, ECN-E--11-013, February 2011

Hansen K., et al., 2011c, Classification of atmospheric stability for offshore wind farms. In UPWIND 1A2 Metrology, Final Report, Chapter 10, ECN-E--11-013, February 2011

Hassager C.B., Rasmussen L., Peña A., Jensen L.E., Réthoré P.-E., 2013, Wind Farm Wake: The Horns Rev Photo Case. Energies 6(2): 696-716

NDA: 

The test case is offered to participants of the IEA Task 31 Wakebench and EU project EERA-DTOC Work Package 1.