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Norrekaer Enge Data Qualification

Scope

The benchmark is open to participants of Wakebench who want to qualify wind farm measurements for wake model validation.

Objectives

The main objective is to qualify wind farm measurements before data analysis can be performed. The qualification includes an analysis of the wind farm surroundings to identify potential terrain effects and obstacles, which can influence the local flow conditions. The data qualification includes basic quality screening, identification of outliers, and qualification of power values for each wind turbine. This process is used to eliminate sequences where the wind turbines have been stopped or been in an idling mode, start sequence, stop sequence or failure mode.  The data qualification analysis includes to definition of quality-checked references of wind speed and direction.

Data Accessibility

The benchmark is offered to all participants of the IEA Task 31 Wakebench.

Input data

Approximately one year of 10-minute statistics for power and wind measurements recorded in a 42 x 300 kW wind farm have been made available for this benchmark.

The recordings are available in three different formats:

1)       Stored in a MySQL database made accessible through the Internet;
2)       Stored in MS-EXCEL tables or
3)       Stored in a MS-DBASE database.

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Norrekaer Enge Power Deficit 1

Scope

The benchmark is open to participants of Wakebench who want to analyze wind farm measurements for wake model validation.

Objectives

Determination of power deficit between pairs of turbines in the wind farm as function of flow direction.

Data Accessibility

The benchmark is offered to all participants of the IEA Task 31 Wakebench.

Input data

Approximately one year of 10-minute statistics for power and wind measurements recorded in a 42 x 300 kW wind farm have been made available for this benchmark.

Validation data

  1. Determine the power deficit between a pair of wind turbines with 6.3 D spacing for a 20 deg inflow sector. The deficit between turbines A2 and A1 is determined for the inflow sector 155-175 deg for a 5° moving window and wind speed interval of 6 – 12 m/s with reference to M1. Power deficit = 1 - Power(A2)/Power(A1)

Model runs

Not applicable 

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Norrekaer Enge Power Deficit 2

Scope

The benchmark is open to participants of Wakebench who want to analyze wind farm measurements for wake model validation. 

Objectives

is to determine power deficit along straight rows of turbines in the wind farm. The turbines in flow sector 165 deg  has a constant spacing of 6.3D, while the spacing in direction 257 deg is constant and equal to 8.2D except for a large gap of 26.7D where speed recovery is to be expected.

Data Accessibility

The benchmark is offered to all participants of the IEA Task 31 Wakebench.

Input data

Approximately one year of 10-minute statistics for power and wind measurements recorded in a 42 x 300 kW wind farm have been made available for this benchmark. The following inflow conditions will be considered:

  • Wind speed interval: 9 – 11 m/s;
  • Turbulence intensity: all
  • Flow sectors: 155-175º and 247-267º

Validation data

  1. Power deficit along 6 distinct rows (A, B, C, D, E & F) determined as function of spacing for a direction of 165º with reference to M1.
  2. Power deficit along 7 distinct rows (A1-F1, A2-F2, A3-F3, A4-F4, A5-F5, A6-F6 & A6-F6) determined as function of internal spacing for a direction 257º with reference to M1.

Power deficit = 1 - Power(A2)/Power(A1)

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NTUA18_VGs

Scope

Tests concern the flow past VGs on an airfoil at Re = 0.87e6. Test details are given in the relevant Test Case. The input data are the airfoils and VG geometries as well as the test conditions. )

Data Accessibility

Data are freely available to everyone under a Creative Commons Attribution 4.0 International License.

Objectives

The objective of this benchmark is to validate different VG modelling approaches against experimental data.

Input data

Tests concern the flow past VGs on an airfoil at Re = 0.87e6. Test details are given in the relevant Test Case. The input data are the airfoils and VG geometries as well as the test conditions.

Validation data

The validation data are:

  1. Pressure distribution along the wing chord for the examined incidence range for the cases with and without VGs

  2. Force and drag coefficient polars for the cases with and without VGs

  3. Velocity, vorticity and Re stress data on three planes normal to the flow and five planes normal to the wing span for the case without VGs, as shown in Figure 1, for the α = 10° case.

  4. Velocity, vorticity and Re stress data on three planes normal to the flow for the case with VGs as shown in Figure 2, for the α = 10° case.

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NTUA18_VGs

Site Description: 

All experiments were carried out at the small test section (1.4mx1.8m) of the National Technical University of Athens (NTUA) wind tunnel [1]. The wind tunnel is of the closed single-return type with a total circuit length of 68.81 m. The circuit has a contraction ratio of 6.45 to 1. The free-stream turbulence level in the 3.75 m long octagonal test section is 0.2% with a maximum test section velocity of about 60 m/s. Energy to the flow is given by a 2.67 m diameter eight-bladed fan driven by a 300 bhp DC motor.

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Offshore design codes

This section is focused on benchmarks of integrated codes for the analysis of offshore wind turbines. The substructure of an offshore wind turbine can be fixed or floating. The expression ”integrated codes” refers to codes that are able to model all the different effects that influence the dynamics of an offshore wind turbine in a coupled manner. The use of integrated codes for the analysis of offshore wind turbines is a physical requirement, because the different effects: aerodynamics, hydrodynamics, structural dynamics, control, are interrelated.

Figure 1: Schematic of top-level building level building-block models for offshore design codes (from IEA Task 30 OC4, Phase II Results Regarding a Floating Semisubmersible Wind System)

Based on "Model evaluation protocol for offshore design codes. Version 1" IRPWind WP6.2 2005

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Projects

If you want to add you project here, please contact the administrator.

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Riso Wake Lidar

Data Provider: 

DTU Wind Energy / Stuttgart University, Department of Wind Energy (SWE)

Data accesibility: 

The test case is offered to participants of the IEA Task 31 Wakebench

Site Description: 

Wake velocity measurements have been recorded by a pulsed lidar system as part of a measurement campaign conducted from June 2011 to early January 2012 at the DTU Wind Energy, Risø Campus test site located on the south-east side of Roskilde Fjord in Denmark. It is a fairly flat  and homogeneous onshore terrain mainly characterized by grassland. This test site is made of 3 stall regulated turbines: a Tellus 95kW, a Vestas V27 and a Nordtank 500kW. A satellite picture of the terrain with nearby obstacles, and centered on the lidar mounted Nordtank 500kW is  shown in Fig. 1.

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Risø Wake Lidar Single Wake

Scope

The benchmark is open to participants of WakeBench who want to validate the near-wake models in horizontally homogemeous terrain using lidar cross-sectional scans from 1 to 5 rotor diameter downstream.

Objectives

Determination of mean wake velocity ratio at hub height as function of downstream position for a Nordtank 500 kW stall regulated turbine in flat and horizontally homogeneous terrain at different atmospheric stabilities and wind conditions.

Data Accessibility

The benchmark is offered to participants of the IEA Task 31 Wakebench.

Input data

The necessary input parameters related to the turbine, the terrain and the ambient flow are:

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San Gregorio

Data Provider: 

Sorgenia Green s.r.l.

Data accesibility: 

Site Description: 

The wind farm is placed in southern Italy on a very complex terrain area; prior the installation of the turbines site assessment was done using met-mast measurements.

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San Gregorio Freeflow

Scope

Participants of the Wakebench projects are invited to join the benchmark for flow models over topography in neutral conditions. Simulations need to be performed to ensure an exhaustive characterization of the wind on the main directions. Reliability of the models will be investigated using the anemometric measurements from the available met-masts.

Objectives

Produce the best estimate of the flow field in neutral conditions above the San Gregorio Magno site for the 240°, 270° and 30° wind directions.

Data Accessibility

The benchmark is offered to participants of the IEA Task 31 Wakebench who has signed the NDA attached to the test case guide.

Input data

The following input data are at disposal for simulating San Gregorio Magno flow field in neutral conditions:

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San Gregorio Wakes

Scope

The benchmark is open to the participants of the Wakebench project using flow and wake models for complex terrains. 

Objectives

The main goal of this benchmark is to assess flow and wake models behaviour on a very complex terrain environment.

Simulations need to be performed to ensure an exhaustive characterization of the wind on the main direction sector (270°) for the wind farm sub-cluster T10, T11, T12, T13. Reliability of the models will be investigated using the anemometric and SCADA measurements.

Data Accessibility

Brief description about the accessibility of the data

Input data

The ASTER digital terrain, the roughness model (winter and summer retrieved fromwww.dataforwind.com), as well as the layout of the sub-cluster shall be provided to the participants (the coordinate system used is UTM-WGS84-33N).

The wind turbines are Siemens SWT-93 with a nominal power of 2300 kW and a hub height of 80 m; the nominal thrust and power curves shall be available.

The conditions for simulating the wind farm flow are the anemometric conditions at reference met-mast position at hub-height.

 

Mean velocity at hub height (80 m) at met-mast position:         from 5 to 9 m/s

Mean direction at hub height (80 m) at met-mast position:       from 260 to 280°

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Sexbierum

Data Provider: 

The data has been extracted from Cleijne (1993, 1992).

Data accesibility: 

The test case is offered to participants of the IEA Task 31 Wakebench.

Site Description: 

The measurements were carried out in 1992 at the Dutch Experimental Wind Farm at Sexbierum, which is in the northern part of The Netherlands about 4 km from the shore.  The wind farm is in flat, homogeneous terrain characterized by grassland.  The wind farm contains 18 HOLEC turbines each producing 310 kW rated power and with a rotor diameter of 30 m and a hub height of 35 m.  The turbines are arranged in a 3 × 6 array as shown in Figure 1.

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Sexbierum Double Wake Neutral

Scope

The benchmark is open to participants of the Wakebench project using wake and, possibly, atmospheric boundary layer models. This is a realistic wake case measured at the Dutch Experimental Wind Farm at Sexbierum that has the added complexity of multiple wake interaction. It should test a wake model’s ability to reproduce the wake merging process.

This benchmark follows the single-wake case (Sexbierum_SingleWakeNeutral). Participants are strongly encouraged to participate in both exercises for a more complete model evaluation.

Objectives

Demonstrate how wake models perform and capture the wake merging process in the presence of atmospheric shear and turbulence.

Data Accessibility

The benchmark is offered to participants of the IEA Task 31 Wakebench.

Input data

The conditions for simulating the Sexbierum double wake are:

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Sexbierum Single Wake Neutral

Scope

The benchmark is open to participants of the Wakebench project using wake and, possibly, atmospheric boundary layer models. This is a realistic wake case measured at the Dutch Experimental Wind Farm at Sexbierum.  It focuses on the single wake case, which is a good “building-block” to the double wake case (Sexbierum_DoubleWakeNeutral).

Objectives

Demonstrate how wake models perform and capture the wake formation and evolution process in the presence of atmospheric shear and turbulence.

Data Accessibility

The benchmark is offered to participants of the IEA Task 31 Wakebench.

Input data

The conditions for simulating the Sexbierum double wake are:

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