session 7: wind modelling - dewi.de · pdf filesession 7: wind modelling ... relevant flow...

Session 7: Wind Modelling

DEWEK 2004 - Proceedings

State of the Art in Application of Flow Models for Micrositing

M. Strack, V. Riedel, DEWI WilhelmshavenGerman Wind Energy Institute GmbH (DEWI), Ebertstr. 96, D-26382 Wilhelmshaven,

email: [email protected]

1. Abstract

The limits of the European Wind Atlas methods for calculation of the wind conditions in complex terrain are well known. So ingeneral a growing interest for application and validation of flow models can be observed. Different meso-scale models areapplied to describe the state of the atmosphere, but also micro-scale flow models are considered to resolve the small scalevariations of wind speed and turbulence within a wind farm in complex terrain.In the presented paper an overview of the state of the art in application of flow models for Micrositing purposes is given. Thestate of the art does not relate to the newest development in computational fluid dynamics (CFD), but covers several aspectsimportant for the application of CFD models for Micrositing purposes.A short overview and classification of the applied flow models and their properties with regard to the application is given. Therelevant flow phenomenon, as determined by comprehensive measurement campaigns in flat or complex terrain, are shownas typical problems to show the complexity of the task. Exemplary verifications of flow model results against measurementdata show, that complicated flow patterns can be simulated quite well by an appropriate flow simulation. However, it be-comes clear that this requires not only appropriate models, but also that the application scheme and resolution must bechosen appropriate, otherwise no realistic results can be expected. An appropriate flow simulation can provide a completedescription of the flow field and hence can allow a new standard for description of site conditions, especially concerningparameters which are relevant for the loads on the wind turbine in complex terrain, like turbulence, wind speed gradients andflow inclination. The potential of this and the big advantages are shown on base of exemplary investigation of a large windfarm site in complex terrain. Last but not least, the requirements and obstacles for flow model application in wind energy aredescribed. In this context, a Round Robin Test of Flow Models in Wind Energy is announced, which is expected to becomean important guideline for assessment of the uncertainty of flow model results.

2. Flow Models Applied in Wind Energy

Numerous flow models of different type and complexityhave been applied for wind energy purposes. In Figure 1a brief and certainly incomplete overview is given, showingthe names of some models and doing a classification ofthe models regarding their main properties. The typicalmagnitude of the spatial resolution is given as additionalinformation.The European Wind Atlas methods [1] can be seen asstandard for wind energy purposes. The limits of the Euro-pean Wind Atlas methods for calculation of the wind con-ditions especially in complex terrain are well known, butstill the methods are predominantly applied as they havethe advantage of being easy and practical to apply, beingassessable for many situations and comparable. Besidesthe WASP program and some products, which directlymake use of the WASP results, like WindPro or Wind-Farmer, the main principles are also implemented on arectangular grid basis in the model LINCOM, which isincluded in the product WASP-Engineering. The flowmodel capabilities are very limited and consist of a set ofsimplified descriptions of wind flow in the atmosphericboundary layer, derived among others from potential flowtheory, and further semi-empirical correction models. Themodel resolution usually is very high, and the computa-tional requirements very low. Some result properties likethe symmetric behaviour of orographic effects are clearlyunrealistic, and only due to the strong simplification andlow complexity of the model.Another class of models are the so called mass-consistentmodels. The basis of probably all of these models is theNOABL model [2], and several modifications or commer-cial variants like MCF, AIOLOS or WindMap exist. Thisclass of models apply only a very small subset of thephysical flow equations, which are solved numerically. Theusual resolution of these models is medium to high andthe computational requirement is quite low.The mass consistent models do have similar limits thanthe European Wind Atlas results, an their results oftenshow quite similar behaviour to the European Wind Atlas

results [6]. A significant enhancement compared to theEuropean Wind Atlas model is mostly not visible.Both model classes described so far are diagnostic mod-els, which means that the results strongly depend on theinput data (initialisation). A more realistic flow simulationbases on the numerical solution of the main physical flowequations, what is done with a so called prognostic model.Often “real” flow simulation is associated with the applica-tion of a prognostic model, which allow to gather newknowledge about the flow from the results of the simula-tion. Models of this category are very complex and dohave high computational demands.

European Wind Atlas• WASP• LINCOM

Mass-consistent models• NOABL• MCF, AIOLOS• WindMap

Reynolds-equation solver• Phoenics• CFX• Fluent

Com

plex

ity Atmosphere models• KAMM• MM5• Fitnah• GESIMA

diag

nost

icpr

ogno

stic

5 m

10 m

1000 m20 m

Figure 1: Overview of flow models applied for windenergy purposes.

The prognostic models applied for wind energy can bedivided into meso-scale atmospheric models and micro-scale Reynolds-equation solver.The meso-scale atmospheric models, like KAMM, MM5,Fitnah or GESIMA, usually base on research work in theframe of weather prediction or atmospheric dispersionsimulation, and provide a quite complete set of atmos-pheric phenomenon like radiation or clouds. Furthermore,these models are usually prepared to make use of com-prehensive data sources coming from numerical weatherprediction. The limit of the meso-scale atmospheric mod-els is mostly the typical finest resolution in the magnitudeof 1×1 km2, which is too coarse to resolve relevant small-



scale variations within complex terrain. Furthermore, theusual meso-scale models are not capable of simulatingturbulence generation by the topography and its transport,as the turbulence in atmospheric models usually is formu-lated dependent from the mean flow properties.The family of the Reynolds-equation solver base on com-putational fluid dynamics (CFD) methods or services pro-vided for industrial applications like the optimisation ofvehicles or the design of turbine blades. The use of CFDmethods is fully established for such purposes and severalhighly developed, flexible CFD packages are available.These can be adjusted to the specific application require-ments, like the wind modelling in the boundary layer,which means that specialised know-how is required toapply these models. Usually these CFD models comprisea higher order turbulence model, are flexible regarding thecalculation grid used, work very efficient and are validatedfor many application cases. The resolution for wind energypurposes is, due to the size of the required model area,limited to a finest resolution in the order of 20 m, andhence is capable of resolving small scale height struc-tures. Due to the mostly used k-ε turbulence model, thegeneration of turbulence by the topography and its trans-port can be simulated in principal.Most of the described models were already tested by theauthors. The WASP model within the scope of some re-search investigations [5][6] and as part of the daily projectwork, within this scope also WindMap. The meso-scalemodel GESIMA was tested during extensive researchwork [3][4][6]. A comprehensive model comparison, in-cluding the above mentioned and several other models ofdifferent complexity, including LINCOM, AIOLOS andothers, was performed during a European research proj-ect [6]. The MM5 model application is described in anotherpaper [7], whereas in the following the investigations areconducted on base of the micro-scale model PHOENICS,which is provided by Cham LTD, UK.As base for the calculations, the PHOENICS model wasadjusted by DEWI to the atmospheric boundary layerenvironment. This encloses the development of an appro-priate application scheme, the selection of the correctsubmodels and parameterisations and as important aspectthe adjustment and verification of the turbulence param-eterisation for boundary layer conditions [8].As these issues have a considerable influence, it is im-portant to emphasise that the model results as presentedin the following have to be considered as exemplary re-sults, which can potentially be obtained, if a principallyvalidated micro-scale flow model is adjusted and appliedcarefully and correct within the developed applicationscheme. The aim is not, to derive a general statementregarding the capabilities of the applied model, and thiswould not be possible, as such a property would be con-nected more to the way of application of the model, than tothe specific model itself.

3. Wind Profile Verifications

As part of the systematic verification of the flow modelcapabilities a verification campaign with the measurementdata of the 130 m-mast near to the test site of DEWI, northof Wilhelmshaven, near to the coast of the North Sea, wasperformed. The high quality, long term data allow a reli-able wind profile measurement on base of the wind speedmeasurement heights 11 m, 32 m, 62 m, 92 m and 126 mand additional meteorological measurements to determinee.g. the temperature stratification.

The wind profile measurement was compared to the cal-culation on base of the logarithmic wind profile and theCFD simulation results for different situations. The mostclear situation is shown in Figure 2, where this comparisonis shown for a situation of a wind direction sector with lowand uniform roughness length, neutral temperature stratifi-cation and wind direction coming from inland.The wind profile as calculated by the logarithmic windprofile, which is identical to the WASP principle for this(idealised) conditions, shows a quite good agreement withthe measurement data up to heights of about 60 m. Forlarger heights the actual wind speed is underpredicted bythe logarithmic wind profile by several percent.The wind profile as calculated by the CFD method fits verywell to the measured profile for all measurement heights. Itturns out that for this situation the extrapolation of the windspeed value measured at 11 m to the highest anemometerat 126 m can be done by the CFD calculation with an errorfar below 1%.This is a noticeable small error, which however should notbe assumed to be valid in general and transferable to anyother situation, as especially the homogenous roughnessconditions for this situation are quite ideal. However, theclose match of the CFD results to the measurements isclear, and also true for other situations and directions.

Figure 2: Wind profile as calculated with the logarith-mic wind profile and the CFD methods, rela-tive to the 32 m measurement value.

It turns out that for this situation the logarithmic wind pro-file, where the WASP principle bases on, for the shownroughness conditions and the inland wind direction sys-tematically underpredicts the wind speed in large heights.This fits to experience, which are gained with other largemeasurement mast data, however, which are known to bedependent from site properties, usually smaller than forthe shown idealised situation and not generally to betransferred to other sites.Noticeable is the fact, that this effect is observed for neu-tral stratification cases, because such an effect often wasassociated with stratification influence. So this effectseems to be a pure turbulence effect, which obviously canbe described very well by a good turbulence model.

4. Flow Simulations at Oberzeiring Site

For the verification of complex terrain flow modelling ca-pabilities, but also to show the complexity of the flow phe-nomenon itself, the evaluation of mast measurement data,SODAR data and wind farm energy yield data from the

Measurement data (neutral stratification) CFD-Simulation

Logarithmic wind profile

relative Wind Speed



Figure 3: Photo of the wind farm Oberzeiring.

Figure 4: Overview of the orography of the Ober-zeiring site. One red contour line means 100m height difference. Legend: ● wind turbinepositions, + SODAR measurement posi-tions, + measurement mast positions.

wind farm Oberzeiring was evaluated. The wind farmOberzeiring (Figure 3) is located in Austria, Niedere Tau-ern, on a height of approximately 1900 m above sea level,and hence is the highest wind farm in Europe. It operatesince end of 2002. The site is very complex and showssteep, long slopes with large height differences and im-portant orographic structures, which have a considerableeffect on the wind flow. In Figure 4 a small section fromthe digital terrain data is shown, to get an overview of theterrain structure.A comprehensive measurement campaign has been per-formed at the site to measure the wind conditions and toprovide the basis for a good modelling of the wind condi-tions. Besides wind measurements at one 50 m mast, ameasurement at hub height (65 m) to measure the windturbine power curve and several SODAR measurementsat 4 different locations within the wind farm were per-formed. In Figure 4 also the positions of most of themeasurements are shown.As subject of the first investigations the wind variationwithin the wind farm was evaluated. The mean wind con-ditions in the wind farm area were calculated by means ofthe CFD model and evaluated as value relative to the windspeed measured at the 65 m mast. In Figure 5 this varia-tion is shown as colour map, in the upper map for a winddirection situation of 327°, for the lower map for a winddirection of 331°. It turns out, that the comparatively tinywind direction change of 4 degrees leads to a change ofthe relative wind speed of 3% at some locations of thewind farm. This sensitivity on the wind direction is extremeand was not expected. This effect can be observed also inevaluating the energy yield data from the wind farm.With systematic evaluation of the flow fields for differentslightly changing wind direction it becomes clear, that thestrong sensitivity is not only caused by the orographic

Figure 5: Spatial variation of mean wind speed on thesite and its variation with wind directionchanges.

speed-up effects in the wind farm area, but that also somekind of a flow separation happens at the northern slope ofthe wind farm, where the flow behaves totally differentpassing a certain height structure westwards than passingeastwards.The described effect has the important impact, that thesimulation of the wind conditions for the wind farm Ober-zeiring has to be performed with extreme resolution of thewind direction, if the result should be realistic. A simulationwith fixed wind direction sectors would not make sense atthe Oberzeiring site.Taking into account these findings, it is possible to con-sider the complicated but relevant flow effects correctly. InFigure 6 the variation of the energy yield at the wind farmOberzeiring, as actually observed, as calculated by WASP

0 %

2 0 %

4 0 %

6 0 %

8 0 %

1 0 0 %

1 2 0 %

0 1 2 3 4 5 6 7 8 9 1 0 1 1

T u rb in e N o .

Rel

ativ

e En

ergy

yie

ld

M W h (W A S P ), P a rk ,re la tive to T u rb in e 6

M W h (P h o e n ics ) , P a rk ,re la tive to T u rb in e 6

M W h (M e a s u re d ), P a rk ,re la tive to T u rb in e 6

Figure 6: Comparison of the energy yield variationat the wind farm, as actually occured, ascalculated by WASP and as calculatedby CFD.



and as calculated by CFD areshown. It becomes clear, that thevariation is very large, but can bereproduced quite well by the CFDresults, much better than theWASP model. The average de-viation of the CFD results are2.3%, whereas the WASP aver-age deviates by 9.1%. A part ofboth of this deviation may becaused by slightly different per-formance of the wind turbines,which cold not be evaluated indetail.The CFD result fits quite well,whereas the WASP model is notcapable even to extrapolate thewind conditions measured at hubheight to the different wind tur-bines.In addition to the measurementmast data, the data from theSODAR measurement wereevaluated. In Figure 7 and Figure8 the measured SODAR profileand in comparison the calculationresults for the respective winddirection sector are shown for anexemplary selection of situations.It can be observed, that the varia-tion of the calculated wind profileis large, sometimes a clear nega-tive profile is calculated, some-times the result gives a positivegradient. Actually the SODARmeasurement denotes a verysimilar behaviour, except for usu-ally the lowest wind speed meas-urement, which can assumed tobe disturbed. As a result, also thisissue leads to a good correspon-dence of the CFD simulation andthe measurement.

5. Site Assessment in Com-plex Terrain

Megawatt-wind turbines are being installed increasinglyalso in very complex terrain. This development does notonly increase the requirements for energy yield assess-ment, but the aspect of the site assessment regarding thesuitability of the wind turbine for the site becomes moreimportant.

This assessment is done with respect to the safety re-quirements as defined in the IEC standard 61400-1 ([9] or[10]) and includes the parameters relevant for the windturbine loading, which are especially the mean windspeed, extreme wind speed, ambient turbulence, waketurbulence, wind shear and flow inclination. Most of theseparameters are part of the flow field as obtained from theflow simulation. Many of these parameters are not possi-ble to estimate realistically without performing a flowsimulation.

As visible in Figure 9, the wind gradients and the flowinclination, respective their maximum values or the valueswithin the rotor area, can be derived from the flow model

result, as it provides the complete flow field. In Figure 10another effect, the generation and transport of turbulenceis shown (the colour value represents the value of theturbulent kinetic energy). Especially in the region withlarge wind gradients, as on the top of the shown hill, theproduction of turbulence is increased, which affects bytransport by the mean flow also the next wind turbines.

In Figure 11 an overview of the investigated complexterrain site is given, shown are 7 km × 7 km in which theheight varies from 20 m to 640 m above sea level. Theplanned wind farm consists of approximately 50 windturbines. A very good coverage of the wind farm area with10 measurement masts of high quality and the height20 m - 55 m is given. This is a valuable base for investiga-tion and verification purposes.For the assessment of the site conditions, and as possibleinput for a site specific certification of the wind turbines, aset of parameter is defined, which covers the most impor-tant requirements of the IEC 61400-1:

Figure 7: Comparison of different calculatedwind profiles at the site Ober-zeiring to the measured one bySODAR (site 1).

Figure 8: Comparison of different calcu-lated wind profiles at the siteOberzeiring to the measuredone by SODAR (site 4).



Wind speedmean, distributions, sector-wiseextreme wind speed

Turbulence matrixdependent on wind speed and directionmean and standard deviationwith and without wind farm turbulence

Flow inclinationMean, mean absolute and extreme valuessituation of occurrence

Maximum wind speed gradientvalue and situation of occurrence

So for each of the wind turbine positions a site assess-ment document is provided, which contains all the re-quired information.

Figure 9: Vertical slice through a CFD flow field.

Figure 10: Section of CFD turbulence field. The colouralue shows the turbulent kinetic energy.

The wind farm turbulence is calculated by means of twodifferent models, the Frandsen model [11], which repre-sents the standard to perform wind farm wake assessmentfor fatigue load relevant issues, and an Eddy-Viscositymodel, which should provide a realistic, not necessarilyconservative result for the wake turbulence.For the most important parameters the spatial resolution isshown by calculation of a colour map. Figure 12 shows acolour map of the characteristic turbulence intensity asdefined in the IEC 61400-1. As the IEC proposes the val-ues 18% and 16% for the class A and B, it is obvious, thatfrom the map clear hints for optimisation of the wind farmconfiguration can be derived.Regarding the verification of the calculated parameters, ithas to be considered that not all parameters can be veri-fied by measurements, because some of the parametersare even impossible or difficult to measure. However, it isquite obvious that for these kind of parameters the per-formance of a flow simulation according to the state of theart is the best possible way to estimate these.

10

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15

16

17

18

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Figure 12: Calculated spatial variation of characteristicturbulence intensity. Calculated by CFD onbase of the turbulence measurement data.

Figure 11: Overview of the wind farm site. Legend: ● wind turbine positions, + measurement mast positions



As the mean wind speed and turbulence values weremeasured at 10 masts at the site, the measurement val-ues were used as the base for verification calculations. Inthe following the verification is performed in the way, thatfor each measurement mast the values at all other mastsare calculated (only on base of one masts data) and com-pared to the measured values. As the wind farm clearlyconsists of two part, separated by a quite deep valley,each of the two parts is considered separately.For the wind speed the following values for the deviationsare derived: The mean absolute deviation within the east-ern respectively western part of the wind farm amount to2.3% - 2.5% in wind speed.For the turbulence intensity the following values for thedeviations are derived: The mean absolute deviationwithin the eastern respectively western part of the windfarm amount to 1.8% - 2.2% absolute percent.Considering the complexity of the site, these are low un-certainty values. For both values it has to be emphasised,that this is the uncertainty of the verification on base ofone mast, and that the uncertainty of the application isnoticeable lower, as for this the measurement data from allthe masts are applied.

6. Conclusion and Outlook

The capabilities of appropriate flow models to calculate thewind flow conditions have been shown. It has to be em-phasised that these results are considered as exemplaryand not intended to have general meaning. However theseresults give an outlook on the potential of flow modelling,but also emphasise that the modelling of complex flowpattern require a sufficient effort.On the other hand, the uncertainties of energy yield prog-noses based on the European Wind Atlas Method areobvious and become an increasing problem, as the com-plexity of the sites increase, the hub height exceeds thescope of validity of the underlying theory, and at the sametime the accuracy demands increase. Furthermore, theinterest in getting a more complete view of the flow, in-cluding turbulence and further load relevant properties, isrising.So the requirement for a progress in the Micrositing meth-ods is quite obvious. However, as flow models and theirresults are difficult to assess, and transferable experienceis not available, from the financing point of view there aresome reservations to abandon the standard, which still isthe European Wind Atlas Method.In this situation DEWI has announced a Round RobinNumerical Flow Simulation in Wind Energy. Within thisblind test of flow models it is planned to provide an envi-ronment to perform comparable flow simulations to CFDservice providers, and to perform an independent evalua-tion and assessment of the results by DEWI. The aim is tocome to transferable findings regarding the uncertaintyassessment of the flow models, which are in the market.There is a great interest among CFD service providers allover the world to participate. Moreover a group of spon-sors including some of the most relevant companies inwind farm financing and developing in Germany and onewind turbine manufacturer support the Round Robin testand ensure, that the project will be performed effectiveand will result in applicable findings.The project will be supported also by the German Ministryof Environment. The start of the project is scheduled tostart still in 2004 respectively beginning of 2005 and will

come up with results still in 2005.So, as supplement to the ongoing technical development,the Round Robin Numerical Flow Simulation in Wind En-ergy is expected to provide important progress in practiseand acceptance of flow simulation in Micrositing.

7. Acknowledgement

The authors would like to thank the companies Tauern-wind / Energiewerkstatt, Austria, and Desarollos Eólicos, aNuon Company, Spain, for allowing to use and present theproject work and measurement data. Both of these proj-ects had an outstanding background of high quality meas-urement data and allowed a seminal approach forperforming the described tasks.

8. References

[1] I. Troen, E.L. Petersen: Europäischer Windatlas. RisøNational Laboratory, Roskilde, Dänemark, 1990.

[2] R.M. Traci et al.: Developing a Site Selection Meth-odology for Wind Energy Conversion Systems, (FinalReport for the Period 15 June 77 to 15 Sept. 78)DOE/ET/20280-3, UC-60 (September 1978)

[3] Heinemann, Detlev; Mengelkamp, Heinz-Theo;Strack, Martin; Erfahrungen mit der Anwendung desnichthydrostatischen mesoskaligen Strö-mungsmodells GESIMA zur Windpotentialbestim-mung in komplexem Gelände. - DEWEK '98: 4. Deut-sche Windenergie-Konferenz, 21. bis 22. Okt. 1998 inWilhelmshaven. - Wilhelmshaven: DEWI, 1999. - S.69-72

[4] Heinemann, Detlev; Mengelkamp, Heinz-Theo;Strack, Martin; Waldl, Hans-Peter; Experiences withthe Application of the Non-Hydrostatic MesoscaleModel GESIMA for assessing Wind Potential in Com-plex Terrain, 1999 European Wind Energy Confer-ence Proceedings, Nice, France, 1-5 March 1999; S.1169-1176

[5] Martin Strack, Gerhard Gerdes, Thomas Pahlke,Ulrich Focken; Wind Potential Assessment in Com-plex Terrain: Verification of WASP and Investigationof Improvements by Integration of Flow Models ofDifferent Complexity. - DEWEK 2000, Deutsche Win-denergie-Konferenz, 2000, Wilhelmshaven

[6] Tammelin, Bengt; Bergström, Hans; Botta, G. ; Dou-vikas, Dimitris; Hyvönen, Reijo; Rathman, Ole; Strack,Martin; Verification on wind energy predictions pro-duced by WASP and some mesoscale models inEuropean mountains. 2001 European Union WindEnergy Conference: Copenhagen, Denmark, 2-6 July2001. - S. 678-685

[7] Strack, Martin; Durante, Francesco: Validation ofMesoscale Simulations for Offshore Sites. - DEWEK2004, Deutsche Windenergie-Konferenz, 2004,Wilhelmshaven

[8] Detering, H.W., Etling, D.: Application of the E-ε Tur-bulence Model to the Atmospheric Boundary Layer,Journal of Boundary Layer Meteorology, 33, pp. 113-133, 1985.

[9] IEC: IEC61400-1 Wind turbine generator systems -Part 1: Safety Requirements, 2. Ed., 1998.

[10] IEC: IEC61400-1 Wind turbine generator systems -Part 1: Safety Requirements, 3. Ed., Draft, 12/2003.

[11] S. Frandsen, M.L. Thogersen: Integrated FatigueLoading for Wind Turbines in Wind Farms by Com-bining Ambient Turbulence and Wake. Wind Engi-neering Vol. 23, No. 6 1999, 327

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