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This paper presents final results from the EU project AVATAR in which aerodynamic models are improved and validated for wind turbines on a scale of 10 MW and more. Special attention is paid to the improvement of low fidelity engineering (BEM based) models with higher fidelity (CFD) models but also with intermediate fidelity free vortex wake (FVW) models. The latter methods were found to be a good basis for improvement of induction modelling in engineering methods amongst others for the prediction of yawed cases, which in AVATAR was found to be one of the most challenging subjects to model. FVW methods also helped to improve the prediction of tip losses. Aero-elastic calculations with BEM based and FVW based models showed that fatigue loads for normal production cases were over predicted with approximately 15% or even more. It should then be realised that the outcome of BEM based models does not only depend on the choice of engineering add-ons (as is often assumed) but it is also heavily dependent on the way the induced velocities are solved. To this end an annulus and element approach are discussed which are assessed with the aid of FVW methods. For the prediction of fatigue loads the so-called element approach is recommended but the derived yaw models rely on an annulus approach which pleads for a generalised solution method for the induced velocities.

This paper presents final results from the EU project AVATAR in which aerodynamic models are improved and validated for wind turbines on a scale of 10 MW and more. Special attention is paid to the improvement of low fidelity engineering (BEM based) models with higher fidelity (CFD) models but also with intermediate fidelity free vortex wake (FVW) models. The latter methods were found to be a good basis for improvement of induction modelling in engineering methods amongst others for the prediction of yawed cases, which in AVATAR was found to be one of the most challenging subjects to model. FVW methods also helped to improve the prediction of tip losses. Aero-elastic calculations with BEM based and FVW based models showed that fatigue loads for normal production cases were over predicted with approximately 15% or even more. It should then be realised that the outcome of BEM based models does not only depend on the choice of engineering add-ons (as is often assumed) but it is also heavily dependent on the way the induced velocities are solved. To this end an annulus and element approach are discussed which are assessed with the aid of FVW methods. For the prediction of fatigue loads the so-called element approach is recommended but the derived yaw models rely on an annulus approach which pleads for a generalised solution method for the induced velocities.

The current paper presents the effort, in the EU AVATAR project, to establish the necessary requirements to obtain consistent lift over drag ratios among seven CFD codes. The flow around a 2D airfoil case is studied, for both transitional and fully turbulent conditions at Reynolds numbers of 3 × 106 and 15 × 106. The necessary grid resolution, domain size, and iterative convergence criteria to have consistent results are discussed, and suggestions are given for best practice. For the fully turbulent results four out of seven codes provide consistent results. For the laminar-turbulent transitional results only three out of seven provided results, and the agreement is generally lower than for the fully turbulent case.

This paper presents the most recent results from the EU project AVATAR in which aerodynamic models are improved and validated for wind turbines on a scale of 10 MW and more. Measurements on a DU 00-W-212 airfoil are presented which have been taken in the pressurized DNW-HDG wind tunnel up to a Reynolds number of 15 Million. These measurements are compared with measurements in the LM wind tunnel for Reynolds numbers of 3 and 6 Million and with calculational results. In the analysis of results special attention is paid to high Reynolds numbers effects. CFD calculations on airfoil performance showed an unexpected large scatter which eventually was reduced by paying even more attention to grid independency and domain size in relation to grid topology. Moreover calculations are presented on flow devices (leading and trailing edge flaps and vortex generators). Finally results are shown between results from 3D rotor models where a comparison is made between results from vortex wake methods and BEM methods at yawed conditions.

A new integrated design tool for optimization of offshore wind farm clusters is under development in the European Energy Research Alliance – Design Tools for Offshore wind farm Cluster project (EERA DTOC). The project builds on already established design tools from the project partners and possibly third-party models. Wake models have been benchmarked on the Horns Rev and, currently, on the Lilgrund wind farm test cases. Dedicated experiments from ‘BARD Offshore 1’ wind farm will using scanning lidars will produce new data for the validation of wake models. Furthermore, the project includes power plant interconnection and energy yield models all interrelated with a simplified cost model for the evaluation of layout scenarios. The overall aim is to produce an efficient, easy to use and flexible tool - to facilitate the optimised design of individual and clusters of offshore wind farms. A demonstration phase at the end of the project will assess the value of the integrated design tool with the help of potential end-users from industry.This abstracts summarizes the objectives and preliminary results of work package 3. In order to provide an accurate value of the expected net energy yield, the offshore wind resource assessment process has been reviewed as well as the sources of uncertainty associated to each step.Methodologies for the assessment of offshore gross annual energy production are analyzed based on the Fino 1 test case. Measured data and virtual data from Numerical Weather Prediction models have been used to calculate long term wind speed, wind profile and gross energy.

Designing offshore wind farms next to existing or planned wind farm clusters has recently become a common practice in the North Sea. These types of projects face unprecedented challenges in term of wind energy siting. The currently ongoing European project FP7 EERA - DTOC (Design Tool for Offshore wind farm Clusters) is aiming at providing a new type of model work-flow to address this issue. The wake modeling part of the EERA - DTOC project is to improve the fundamental understanding of wind turbine wakes and modeling. One of these challenges is to create a new kind of wake modeling work-flow to combine wind farm (micro) and cluster (meso) scale wake models. For this purpose, a benchmark campaign is organized on the existing wind farm wake models available within the project, in order to identify which model would be the most appropriate for this coupling. A number of standardized wake cases for large offshore wind farms will be analyzed, which provide a reasonable range of conditions likely to be experienced in offshore wind farms. The systematic evaluation is based upon high - quality input data that is selected in the sister project IEA - Task 31 “WakeBench”.

Wind turbines with a rated power of 5 to 6MWare now being designed and installed, mostly for offshore operation. Within the EU supported UpWind research project, the barriers for a further increase of size, up to 20 MW, are considered. These wind turbines are expected to have a rotor diameter up to 250 m and a hub height of more than 150 m. Initially, the theoretical implications of upscaling to such sizes on the weight and loads of the wind turbines are examined, where it is shown that unfavourable increases in weight and load will have to be addressed. Following that, empirical models of the increase in weight cost and loads as a function of scale are derived, based on historical trends. These include the effects of both scale and technology advancements, resulting in more favourable scaling laws, indicating that technology breakthroughs are prerequisites for further upscaling in a cost-efficient way. Finally, a theoretical framework for optimal design of large wind turbines is developed. This is based on a life cycle cost approach, with the introduction of generic models for the costs, as functions of the design parameters and using basic upscaling laws adjusted for technology improvement effects. The optimal concept or concepts is obtained as the one that minimizes the total expected costs per megawatt hour (levelized production costs). Copyright © 2011 John Wiley & Sons, Ltd. Wind turbines with a rated power of 5 to 6MWare now being designed and installed, mostly for offshore operation. Within the EU supported UpWind research project, the barriers for a further increase of size, up to 20 MW, are considered. These wind turbines are expected to have a rotor diameter up to 250 m and a hub height of more than 150 m. Initially, the theoretical implications of upscaling to such sizes on the weight and loads of the wind turbines are examined, where it is shown that unfavourable increases in weight and load will have to be addressed. Following that, empirical models of the increase in weight cost and loads as a function of scale are derived, based on historical trends. These include the effects of both scale and technology advancements, resulting in more favourable scaling laws, indicating that technology breakthroughs are prerequisites for further upscaling in a cost-efficient way. Finally, a theoretical framework for optimal design of large wind turbines is developed. This is based on a life cycle cost approach, with the introduction of generic models for the costs, as functions of the design parameters and using basic upscaling laws adjusted for technology improvement effects. The optimal concept or concepts is obtained as the one that minimizes the total expected costs per megawatt hour (levelized production costs). Copyright © 2011 John Wiley & Sons, Ltd.

In this paper the basis for introducing thrust information from microscale wake models into mesocale model wake parameterizations will be described. A classification system for the different types of mesoscale wake parameterizations is suggested and outlined. Four different mesoscale wake parameterizations are demonstrated in theWeather Research and Forecasting mesoscale model (WRF) in an idealized atmospheric flow. The model framework is the Horns Rev I wind farm experiencing an 7.97 m/s wind from 269.4o. Three of the four parameterizations use thrust output from the CRESflow-NS microscale model. The characteristics of the mesoscale wake that developed from the four parameterizations are examined. In addition the mesoscale model wakes are compared to measurement data from Horns Rev I. Overall it is seen as an advantage to incorporate microscale model data in mesocale model wake parameterizations.