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Horns Rev Turbulence

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Scope

The benchmark is open to participants of both Wakebench and EERA-DTOC for wake model validation on wind farms with regular layout under neutral atmospheric conditions.

Objectives

Evaluate park models on a wind farm with well defined boundary conditions to determine the power deficit. The power deficit is determined between two nearby turbines. The power deficit is determined for 8 m/s hub height wind speed as function of turbulence intensity.

Data Accessibility

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

Input data

The conditions for simulating the wind farm flow are:

  • Wind farm layout and coordinates of the wind turbine positions (1);
  • V80-2MW turbine specifications (1);
  • Roughness length: z0 = 0.0001 m;
  • Inflow mean velocity at hub height (70 m): 8 m/s.

Validation data

a) The power deficit has been extracted from the SCADA dataset and averaged for wt17 and wt07 with reference to the operational conditions of wind turbine wt07.

b) The power deficit has been extracted from the SCADA dataset and averaged for wt85 and wt95 with reference to the mean wind speed and turbulence intensity from M7, 70 m.

c) The power deficit has been extracted from the SCADA dataset and averaged for wt84 and wt95 with reference to the mean wind speed and turbulence intensity from M7, 70 m. The inflow wind conditions have been obtained by ensemble averaging within a velocity bin of ± 3.0 m/s and under neutral conditions (|L| > 500 m). Hence, validation data is composed of averages and standard deviations of the ensemble of binned observations.

Model runs

1) One principal cases have been defined to validate the power deficit as function of  inflow  direction; 2-3) two principal cases has been defined to validate the maximum power deficit for two different spacing as function of turbulence intensity.

  • Run 1: Flow sector = 250 - 290°, 7D spacing and 7% turbulence intensity;
  • Run 2: Turbulence intensity 2-14%;  flow sector = 270 ± 2.5° and  8 ± 1 m/s and 7D spacing;
  • Run 3: Turbulence intensity 2-14%;  flow sector = 312 ± 2.5° and  8 ± 1 m/s and 10.4D spacing;

The origin of the coordinate system should be placed at the wt08 position with X aligned with the incoming wind direction, Z pointing up and Y perpendicular to the XZ plane in a right-handed system (2).

Output data

1) The validation profile consist on mean power deficit obtained by averaging the power output from wind turbines wt17 and wt07, using a 5 degrees moving window technique (Figure 4).

2) the validation profile consist on mean power deficit obtained by averaging the power output from 6 rows, each consisting of 10 wind turbines in the direction 90° with a spacing of 7D (Figure 5).

3) the validation profile consist on mean power deficit obtained by averaging the power output from 7 rows, each consisting of 6 wind turbines in the direction 132° with a spacing of 10.4D (Figure 5).

Additionally, horizontal profiles from inlet to outlet of wind conditions along the line wtX7 at 70 m height above ground level will be analyzed. Use the file naming and format convention described in the Windbench user's guide with; profID = pow7D with variables {Name, X(m), P(kW)}; and profID = wind7D with variables {X(m), U(m/s), V(m/s), tke(m2/s2), nu_t(m2/s)}.

Remarks

(1) Both the turbine specifications for V80-2MW and the wind farm coordinates are collected in the HornsRev_V80.pdf file. It gathers information publically available from the manufacturer's specs sheet as well as reengineered parameters obtained by NREL using a generic wind turbine model.

(2) There are no guidelines on the definition of the computational mesh so please describe how you integrate grid dependency in the evaluation process. 

(3) The sensitivity of the power deficit ensemble mean and spread with spacing can be related to a number of factors, notably: uncertainties in the reference wind direction, presence of large-scale fluctuations that modulate the 10-min samples and spatial variations of the wind direction within the wind farm that deviate from the reference. It is up to the user to make the best use of the model capabilities to reproduce the variability of the power deficit profiles with the sector width. Please describe thoroughly the methodology adopted to reproduce the validation profiles.   

 (4) Ad run 2 and run 3; the validation dataset has been recorded in the easterly flow sector for wind speeds ranging from 6-11 m/s, resulting in a turbulence intensity range from 4 – 10%.

Terms andConditions

Not applicable.