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Horns Rev Turbulence

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.

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IEA Wind Task 37 Systems Engineering

The purpose of IEA Wind Task 37 is to coordinate international research activities, towards the analysis of wind power plants as holistic systems.  To fully assess how a change, or an uncertainty, in a design parameter affects the myriad of objectives in system performance and cost, a holistic and integrated approach is needed. Integrated systems research, design and development (RD&D) can provide opportunities for improvements in overall system performance, and reduction in the levelized cost of energy. However,  there are significant challenges to developing such integrated approaches, both within and across organizations. There is a need to explore both the opportunities and the challenges for applying systems engineering to integrated wind energy RD&D across the entire wind energy system. This need surfaces both in the tools and methods used in wind plant RD&D.

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IEA-Wind Task 31 WAKEBENCH (2011-2014)

IEA-Wind Task 31 "WAKEBENCH": Benchmarking of Wind Farm Flow Models. The main objective of this IEA Task is to provide a forum for industrial, governmental and academic partners to develop, evaluate and improve atmospheric boundary layer and wind turbine wake models for use in wind energy.

The Annex aims at defining quality-checked procedures for the simulation of wind and wakes. The working methodology is based on the benchmarking different wind and wake modeling techniques in order to identify and quantify best practices for using these models under a wide range of conditions: from onshore to offshore, from flat to complex terrain and from single wind turbines to large wind farms. These benchmarks involve model intercomparison versus experimental data.

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IEA-Wind Task 31 WAKEBENCH 2 (2015-2018)

Verification, Validation and Uncertainty Quantification (VV&UQ) of wind farm flow models. The purpose of the project is to improve wind farm modeling techniques and provide a forum for industrial, governmental and academic partners to develop, evaluate and improve wind farm models. While Task 31 Phase 1 was limited to the wind farm (microscale) scale, Phase 2 will extend the scope to mesoscale and near-wake modeling in order to cover all the relevant atmospheric scales related to wind power meteorology. This will allow a more comprehensive approach to the wind farm integrated design process, facilitating the exchange of knowledge among various research communities: meteorologists, resource/site wind engineers and wind farm/rotor aerodynamicists. The focus will still be placed on wind resource assessment, site suitability and wind farm design but allowing for a larger variety of modeling approaches. Some benchmarks will also be explored in finer detail to better quantify the uncertainty of a range of models for different phenomena.       

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Infinite Wind Farm

Data Provider: 

Not applicable

Data accesibility: 

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

Remarks: 

The goal of this test case is to investigate the number of turbines that is necessary for an asymptotic deficit state to be reached depending on different parameters, as well as on the flow characteristics associated to this state.

Two cases will be modeled for this study:

a) a large (but finite) number of turbines

b) an idealized case with an “infinite” number of turbines, where simulations are made either considering periodic boundary conditions in the streamwise direction, or using analytical models (see e.g. Peña and Rathmann 2013 [1]) to predict the flow in the limit of an infinite number of turbines.

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Infinite Wind Farm Neutral

Scope

The benchmark is opened to participants of the Wakebench project using flow models to model wakes of wind turbines aligned in a row in search for an asymptotic deficit state. Two cases are suggested to be modeled:

a) a large (but finite) number of turbines

b) an idealized case with an “infinite” number of turbines, where simulations are made either considering periodic boundary conditions in the streamwise direction, or using analytical models (see e.g. Peña and Rathmann 2013 [1]) to predict the flow in the limit of an infinite number of turbines.

Case a) is compared to case b) to determine how many turbines are needed to reach an asymptotic wake state (and to verify that the same final converged wake state is reached).

Objectives

Completion of the benchmark will inform on the number of turbines necessary for an asymptotic deficit state to be reached (which might depend on the quantity that is analyzed), as well as on the flow characteristics associated to this state. The dependency on the distance between the turbines as well as the ambient level of turbulence intensity will be investigated.

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IRPWind (2014-2018)

The IRPWIND (Wind Energy Integrated Research Programme) comprises 24 partners, who are all European research institutions and universities working in the area of wind energy research. All partners are part of the European Energy Research Alliance (EERA) Joint Programme on Wind Energy, except for The European Wind Energy Association (EWEA). The IRPWIND project and the EERA JP Wind are highly interlinked in its partners, objectives, strategy and organization. In short the EERA JP Wind has been working for 4 years on voluntary basis, but with the IRPWIND project the European Commission has made it possible to accelerate the collaboration and ambitions in order to form a European Integrated Programme on Wind Energy Research.

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Leipzig

Data Provider: 

The data have been extracted from Lettau (1950).

Data accesibility: 

The test case is offered to participants of the IEA Task 31 Wakebench. In the future it will be open for public access.

Site Description: 

The measurements were done on a grass-covered airfield with flat surroundings. Upstream, the air passes over the city of Leipzig.

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Leipzig Neutral

Scope

The benchmark is open to participants of the Wakebench project using atmospheric boundary layer models. This is the first element of the building-block approach in this range, so it should be mandatory if you intend to participate with this model in other test cases down the line.

Objectives

Demonstrate how ABL models reproduce the characteristic Ekman spiral in neutral conditions represented by prescribed Leipzig profile conditions.

Data Accessibility

The benchmark is offered to participants of the IEA Task 31 Wakebench. In the future it will be open for public access.

Input data

The conditions for simulating the Leipzig wind profile in neutral conditions are:

  • Geostrophic wind: Ug = 17.5 m/s, Vg=0
  • Coriolis parameter: fc = 1.13e-4 s-1
  • Roughness length: z0 = 0.3 m
  • Obukhov length: L = ∞
  • Use dry air with a density ρ = 1.225 kg/m3 and dynamic viscosity μ = 1.73e-5 kg/ms

Validation data

The validation data consists on vertical profiles of velocity components and eddy viscosity as estimated by Lettau (1950).

Model runs

A 3 km high domain should be used, sufficient to fit the boundary layer height with some margin.

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Leipzig Stratified

Scope

The benchmark is open to participants of the Wakebench project using atmospheric boundary layer models that include thermal stratification.

Objectives

Parameterize the ABL to obtain the best fit to the Leipzig profile and report on the resulting boundary layer characteristics.

Data Accessibility

The benchmark is offered to participants of the IEA Task 31 Wakebench. In the future it will be open for public access.

Input data

The conditions for simulating the Leipzig wind profile in stable conditions are:

  • Inlet profiles of velocity components and turbulent viscosity
  • Coriolis parameter: fc =1.3e-4 s-1
  • Use dry air with a density ρ = 1.225 kg/m3 and dynamic viscosity μ = 1.73e-5 kg/ms

Validation data

The validation profiles are the same as the inlet profiles, as obtained from Lettau (1950). The participant is asked to provide the best fit of the ABL model to these input data profiles.

Model runs

A 3 km high domain should be used, sufficient to fit the boundary layer height with some margin.

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Lillgrund

Data Provider: 

Kurt S. Hansen (DTU), licensed by Vattenfall

Data accesibility: 

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

Site Description: 

The measurements were carried out from January 01, 2008 to Dedember 31, 2012 at Lillgrund offshore wind farm in Öresund, the body of water between Malmö, Sweden and Copenhagen, Denmark.  The farm consists of 48 Siemens SWT-2.3-93 wind turbines (Figure 1), each producing a rated power of 2.3 MW at around 12 m/s with a rotor diameter of 93 m and a hub height of 65 m.  The turbines are arranged in a dense array with separation of 3.3 rotor diameters (D) within a row and 4.3 D between rows.

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Lillgrund 360 Efficiency

Scope

The benchmark is open to participants of the Wakebench project using wake and, possibly, atmospheric boundary layer models. This is a case based on the actual operational Lillgrund wind farm in which there are multiple turbines interacting within an array.  This benchmark aims to test a wake/atmospheric model to reproduce the wind plant efficiency observed at Lillgrund over the full wind rose.

Objectives

Demonstrate how wake models perform and capture the wake formation and merging process in the presence of atmospheric shear and turbulence within a large modern wind farm composed of modern multimegawatt turbines. 

Data Accessibility

Brief description about the accessibility of the data

Input data

The conditions for simulating the Lillgrund_360_Efficiency case are:

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Lillgrund Direction

Scope

This document outlines three separate components of this benchmark.  It is the hope that the participant will simulate all three components, but the participant is free to simulate any or all of the components.

This benchmark is open to participants of the Wakebench project using wake and, possibly, atmospheric boundary layer models. This is based on the actual operational Lillgrund wind farm in which there are multiple turbines interacting within an array.  The benchmark aims to test a wake/atmospheric model to reproduce the power production observed at Lillgrund when wind is from a southwesterly, southeasterly, and northwesterly sector. 

For the Southwest case, the sector is centered upon 222° aligned with rows A-H in which there is 4.3 rotor diameter (D) spacing.  For the Southeast case, the sector is centered upon 120° aligned with rows 1-8 in which there is a 3.3 D spacing.  For the Northwest case, the sector is centered upon the 300° direction aligned again with rows 1-8, with flow coming from the opposite direction of the Southeast case, with a 3.3 D spacing.

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Lillgrund TI Spacing

Scope

The benchmark is open to participants of the Wakebench project using wake and, possibly, atmospheric boundary layer models. This is a case based on the actual operational Lillgrund wind farm in which there are multiple turbines interacting within an array.  This benchmark aims to test a wake/atmospheric model to reproduce the maximum power deficit of the second turbine in a row as a function of spacing and turbulence intensity.

Objectives

Demonstrate how wake models perform and capture the wake formation and merging process in the presence of atmospheric shear and turbulence within a large modern wind farm composed of modern multimegawatt turbines. 

Data Accessibility

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

Input data

The conditions for simulating the LillgrundTISpacing case are:

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MARINTEK

Site Description: 

NOWITECH, ReaTHM (Real Time Hybrid Model testing) in MARINTEK ocean basin. A semisubmersible wind turbine will be tested in the ocean basin of MARINTEK, Trondheim, Norway. The model of the floating wind turbine will be anchored in the center of the basin. The mooring system is a spread mooring and the water depth is selected to be 200m. The wind will be modeled in the experiments by use of Hardware in the Loop setup where the wind is simulated in real time by use of Aerodyn. The aerodynamic loads in surge, roll, and yaw are then applied on the model by use of 6 actuators. The actuators apply forces by use of a motor-spring assembly. The model scale is 1:30. This scale will be suitable with respect to the quality of the waves, the model size and the handling of the models in the test set-up. The model tests with the floating offshore wind turbine are intended to take place during weeks 39 and 40 (i.e. by the end of September).
Contact: Dr Madjid Karimirad Madjid.Karimirad@marintek.sintef.no
The test will be performed in the ocean basin of MARINTEK, Trondheim, Norway.

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