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Horns Rev Stratified

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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

Determine the power deficit along a single row of 10 turbines, with an internal spacing of 7D, inside a wind farm of regular layout. Evaluate the sensitivity of the model performance for three atmospheric stratifications, which can be categorized as stable, neutral or unstable.

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;
  • Inflow wind direction sector 270 ± 5°.

Validation data

The power deficit has been extracted from the SCADA dataset and averaged for rows 2-7 with reference to the operational conditions of wind turbine wt07. The inflow wind conditions have been obtained by ensemble averaging within a velocity bin of ± 0.5 m/s combined with three stability classes. Hence, validation data is composed of averages and standard deviations of the ensemble of binned observations. The classification of the atmospheric stratification is based on a derived Monin-Obukhov length and Table 1. The stratification groups used for the validations are: stable=vs-s; neutral=ns-n-nu & unstable=u-vu.

Model runs

Three principal cases have been defined to validate the influence of the atmospheric stability (3).

  • Run 1: atmospheric stratification =stable (2 ≤ cL ≤ 3);
  • Run 2: atmospheric stratification =neutral (-1 ≤ cL ≤ 1);
  • Run 3: atmospheric stratification =unstable (-3 ≤ cL ≤ -2);

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

The validation profile consist on mean power deficit along the rows 2 to 7, obtained by averaging the power output from wind turbines wt02 to wt97 within each row. 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 the atmospheric stratification 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.

Terms andConditions

Not applicable.