Frank, H.P.

Mortensen, N.G.

Rathmann, O.

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Downloaded from orbit.dtu.dk on: Dec 19, 2017Dependence of wind atlas data on the extent of topographic maps around a siteFrank, Helmut Paul; Rathmann, Ole Steen; Mortensen, Niels GyllingPublished in:Wind energy for the new millennium. ProceedingsPublication date:2001Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Frank, H. P., Rathmann, O., & Mortensen, N. G. (2001). Dependence of wind atlas data on the extent oftopographic maps around a site. In P. Helm, & A. Zervos (Eds.), Wind energy for the new millennium.Proceedings (pp. 761-764). München: WIP Renewable Energies.DEPENDENCE OF WIND ATLAS DATA ON THE EXTENT OF TOPOGRAPHIC MAPS AROUND A SITEHelmut P. Frank, Ole Rathmann and Niels G. MortensenRisø National LaboratoryWind Energy DepartmentP. O. Box 49, DK-4000 Roskilde, Denmarkphone: +45 46 77 50 13, fax +45 46 77 59 70, e-mail: helmut.frank@risoe.dkABSTRACT: Wind measurements in Denmark, Ireland, and Northern Portugal are analyzed with the Wind AtlasAnalysis and Application Program WAsP. Wind atlas data is generated from the measurements using topographic maps,which were clipped in a circle around the observation sites. The dependence of the “cleaned” mean speed, energy fluxdensity, mean direction, Weibull parameters, or upstream roughness on the diameter of the maps is investigated.In order to obtain representative wind atlas data it is recommended that the distance from a site to the edge of thetopographic maps should be 10 km or more.Keywords: Terrain; Roughness; Siting1 INTRODUCTIONThe Wind Atlas Analysis and Application Program WAsPis used widely to calculate the wind resource around asite or region. It employs the wind atlas methodology[8] to “clean” wind measurements from local influenceslike orographic speed-up, roughness changes, or obsta-cles like buildings or trees in order to obtain the windclimate representative for the region around the obser-vation site. However, non-hydrostatic orographic speed-up depends on terrain height variations with horizontalscales up to several kilometers around a site. Rough-ness changes can effect the wind field several kilometersdownstream. Therefore, it is important to know how fara map should extend around a site in order to get reliableestimates of the general wind climate. The importance ofthe resolution of topographic maps was investigated byMortensen and Petersen [5].An introduction to the WAsP model is given byMortensen et al. [4]. Troen [7] describes the flow modelfor orographic speed-up. WAsP employs the roughnesschange model of Sempreviva et al. [6].2 METHODIn order to investigate, how important the size of topo-graphic maps is for a wind atlas, WAsP was run severaltimes for a number of stations using maps of differentsize. The mean speed, energy flux density, annual energyproduction, mean direction, Weibull shape parameter, etc.of the wind atlas data was drawn as a function of map di-ameter.To avoid any preferred axis the clipped maps werecircular with the observation site in the center. Only theline segments within diameters of 2.5, 5, 10, and 20 kmwere taken. This is illustrated in Figure 1 for the mast atRisø. Circles indicating the extend of the clipped mapsare shown overlaid on top of the original mapThe main parameters affected by the size of the mapsare the orographic speed-up on hills or valleys, and theupstream roughness [8, Chapter 8.3]. As WAsP is a neu-trally stratified small-scale model the orographic speed-up depends mainly on hills with a half-width of less thana few kilometers. Therefore, only small speed-up can beexpected for sites in Denmark.The upstream roughness is used to transform the ob-served wind to different roughness classes of a wind atlas.6170617561806185684 686 688 690 692 694 696 698 700 0m≤h<20m20m≤h<40m40m≤hz0Figure 1: WAsP map of Risø. Circles with diameters 2.5,5, 10, and 20 km are drawn around the position of themast. Lines, z0, are roughness change lines.The decay length for the magnitude of roughness changesin WAsP is 10 km. Therefore, small maps can result inwrong upstream roughness values in WAsP. For example,in the circular map with diameter 10 km WAsP must as-sume that there is only water in the sector around 300◦.This would yield an underestimation of the wind in thewind atlas from that sector. In reality the surface frictionof the upstream land has reduced the wind speed com-pared to pure over-water conditions.3 RESULTSWe shall concentrate here on the wind atlas values at50 m height above a surface with roughness 3 cm. Thisis close to typical heights of many modern turbines and3 cm roughness represents a good site on land.The most interesting quantity for wind energy appli-cations is the annual energy production, AEP . There-fore, we present the effect of the map size on the AEP ,i.e. the wind distribution is folded with a power curve. Wechose the power curve of the Vestas V47 (660 kW) tur-bine for standard air density. The AEP is calculated withthe wind distribution from the wind atlas data for height50 m above 3 cm, i.e. as if the hub height were 50 m andthe turbine would stand on a plane with uniform surfaceroughness. Other quantities are presented in Frank et al.[3].3.1 Sites in Denmark and IrelandThe AEP as functions of map diameter for sites in Den-mark and Ireland. is shown in Figure 2 The importantresult is that even using maps with diameters 10 km, i.e.5 km distance to a site, errors greater than 10 % in annualenergy production can occur in wind atlas data. For theenergy flux density the error can be greater than 15 %.At sites within a few kilometers from a coast line, whichlies upwind in the dominant wind direction, it is very im-portant to include the coast line in the map. Examplesare the stations Klemensker Ø on Bornholm, and Tystofteon Zealand. Comparing Figure 2 with Figure 3 it can berecognized, that to a great extent the mean energy of thewind atlas data follows the upstream roughness used byWAsP. The strength of the variation of AEP is not di-rectly proportional to the variation of z0. This dependsalso on how much of the total energy is concentrated inthe sector with the highest energy flux density.Denmark has no steep mountains, and Ireland onlya few. Consequently, the orographic speed-up is rela-tively small. The orographic speed-up in WAsP acts onsmaller scales than roughness change effects. Good ex-amples are the stations Corrie Mountain, Kilronan Moun-tain, or Mount Eagle in Ireland. If the map gets so smallthat it does not encompass the full mountain, the oro-graphic speed-up can be seriously underestimated. How-ever, already for map diameters of 5 km the errors forthe orographic speed are less than 5 % for almost all thestations in Denmark and Ireland.The Weibull shape parameter k does not changemuch with varying map size. If the map diameter is 10 kmor greater, the mean wind direction deviates less than 5degrees from the value obtained with the full map.3.2 Sites in PortugalNorthern Portugal is very mountainous and the mountainsare steep. Hence, the orographic speed-up is big. On theother hand, the surface roughness is quite uniform. Onlyone station, Murtosa, lies on the flat coast where the land-sea roughness change is important. RIX approximatelyless than 10.The dependence of annual energy production, AEP ,on map diameter for the Portuguese stations is shown inFigure 5. The available maps are smaller than in Denmarkor Ireland. Some maps have an irregular shape becausethey were set together from several smaller maps. Diam-eters from 2 km to 15 km are chosen. Obviously, mapswith diameters of 5 km are far to small to get a reliableestimate of the annual energy production. Errors greaterthan 10 % must be expected in this type of terrain.For most sites the orographic speed-up is seriouslyunderestimated when using small maps (Figure 6). Formaps with diameters 5 km, the error of the mean windspeed can be over 5 %. The errors might be even greater ifbigger maps were available because there might be weakspeed-ups at greater scales than the total map size. Er-rors in mean wind direction are less than 3◦. The Weibullshape parameter, k, differs by less than 3 % from thevalue with the full map.4 CONCLUSIONSIn order to produce wind atlas data, i.e. a description ofthe regional wind climate independent of local distur-14001500160017001800190020002100220023002400201052.5 ∞AEP [MWh]Map Diameter  [km]Wind Atlas Data for Denmarkz=50m, z0=0.03mall sectorsRisoeTystofteSprogoeKegnaesSkjernVester VedstedBaastrupBeldringeGnibenAbedKastrupKandestederneHaldSilstrupAaholmAlstedgaardMejrupGedserKlemensker OeDueodde0.90.9511.051.11.151.21.251.3201052.5 ∞AEP /AEP∞Map Diameter  [km]Wind Atlas Data for Denmarkz=50m, z0=0.03mall sectorsRisoeTystofteSprogoeKegnaesSkjernVester VedstedBaastrupBeldringeGnibenAbedKastrupKandestederneHaldSilstrupAaholmAlstedgaardMejrupGedserKlemensker OeDueodde1000120014001600180020002200240026002800201052.5 ∞AEP [MWh]Map Diameter  [km]Wind Atlas Data for Irelandz=50m, z0=0.03mall sectorsBelmulletBirrCasement AeClaremorrisClonesCork ApDublin ApFinner CampKilkennyKnock ApMalin HeadMullingarRoches PtRosslare HbShannon ApValentia ObsAnargetAnnestownCahermurphyCarnsore PtCladyCorrie MtKilronan MtKnockanoreKnocknagarhoonMace HeadMount EagleRath HillRostonstown0.850.90.9511.051.11.151.21.25201052.5 ∞AEP /AEP∞Map Diameter  [km]Wind Atlas Data for Irelandz=50m, z0=0.03mall sectorsBelmulletBirrCasement AeClaremorrisClonesCork ApDublin ApFinner CampKilkennyKnock ApMalin HeadMullingarRoches PtRosslare HbShannon ApValentia ObsAnargetAnnestownCahermurphyCarnsore PtCladyCorrie MtKilronan MtKnockanoreKnocknagarhoonMace HeadMount EagleRath HillRostonstownFigure 2: Annual energy production of a Vestas V47 (660kW) turbine if it had a hub height of 50 m above a flat sur-face with roughness length 3 cm. Shown are the absolutevalues and the relative changes AEPD/AEP∞, where∞ represents the full map. Sites in Denmark are at thetop, and sites in Ireland at bottom.bances, it is recommended that topographic maps arounda site should extend 10 km out from it. Otherwise the er-ror of the expected annual energy production of a typicalwind turbine can be greater than 10 %. If there is a ma-jor roughness change like a coast line further away in a0.00010.0010.010.11201052.5 ∞z 0 [m]Map Diameter  [km]Wind Atlas Data for Denmarkz0 from sectorwith max. ERisoeTystofteSprogoeKegnaesSkjernVester VedstedBaastrupBeldringeGnibenAbedKastrupKandestederneHaldSilstrupAaholmAlstedgaardMejrupGedserKlemensker OeDueodde0.00010.0010.010.11201052.5 ∞z 0 [m]Map Diameter  [km]Wind Atlas Data for Irelandz0 from sectorwith max. EBelmulletBirrCasement AeClaremorrisClonesCork ApDublin ApFinner CampKilkennyKnock ApMalin HeadMullingarRoches PtRosslare HbShannon ApValentia ObsAnargetAnnestownCahermurphyCarnsore PtCladyCorrie MtKilronan MtKnockanoreKnocknagarhoonMace HeadMount EagleRath HillRostonstownFigure 3: The upstream roughness length in the sectorwhere most of the energy flux density is observed as afunction of map diameter; sites in Denmark on top, Irishsites at bottom.-202468101214201052.5 ∞Orographic Speed-up:  dS [%]Map Diameter  [km]Wind Atlas Data for DenmarkdS from sectorwith max. ERisoeTystofteSprogoeKegnaesSkjernVester VedstedBaastrupBeldringeGnibenAbedKastrupKandestederneHaldSilstrupAaholmAlstedgaardMejrupGedserKlemensker OeDueodde-100102030405060201052.5 ∞Orographic Speed-up:  dS [%]Map Diameter  [km]Wind Atlas Data for IrelanddS from sectorwith max. EBelmulletBirrCasement AeClaremorrisClonesCork ApDublin ApFinner CampKilkennyKnock ApMalin HeadMullingarRoches PtRosslare HbShannon ApValentia ObsAnargetAnnestownCahermurphyCarnsore PtCladyCorrie MtKilronan MtKnockanoreKnocknagarhoonMace HeadMount EagleRath HillRostonstownFigure 4: Orographic speed-up in the sector where mostof the energy flux density is observed as a function ofmap diameter. The top row shows sites in Denmark, thebottom row sites in Ireland.4006008001000120014001600180020001510852.52 ∞AEP [MWh]Map Diameter  [km]Wind Atlas Data for Portugalz=50m, z0=0.03mall sectorsMurtosaAfonsimLamasPenudeAvelosoPenaDraveAradaAdaufeCastanheiraSenhora de MoreiraMaraoLagoa de Joao0.811.21.41.61.822.22.41510852.52 ∞AEP /AEP∞Map Diameter  [km]Wind Atlas Data for Portugalz=50m, z0=0.03mall sectorsMurtosaAfonsimLamasPenudeAvelosoPenaDraveAradaAdaufeCastanheiraSenhora de MoreiraMaraoLagoa de JoaoFigure 5: Annual energy production of a Vestas V47 (660kW) turbine for sites in Portugal from wind atlas data at50 m above a flat surface with roughness length 3 cm.0204060801001201401510852.52 ∞Orographic Speed-up:  dS [%]Map Diameter  [km]Wind Atlas Data for PortugaldS from sectorwith max. EMurtosaAfonsimLamasPenudeAvelosoPenaDraveAradaAdaufeCastanheiraSenhora de MoreiraMaraoLagoa de JoaoFigure 6: Orographic speed-up in the sector where mostof the energy flux density is observed as a function of mapdiameter at sites in Portugal. The difference to the valuefor the total map, ∆SD −∆S∞, is shown at the bottom.frequent wind direction this should be included at evengreater distances, perhaps up to 20 km away. In moun-tainous terrain without major roughness changes some-what smaller maps might be possible because the oro-graphic flow model of WAsP reacts on terrain variationson smaller scale than the roughness change model.Big maps are critical when a wind atlas for a regionshall be made. For predictions close to a measurementsite — say one or 2 kilometer away — smaller mapsmight be used because the errors in the analysis of thepredictor site and the predicted site will almost cancel.This cancellation of errors explains why WAsP can beused in mountainous terrain of similar ruggedness [see1, 2].REFERENCES[1] A. J. Bowen and N. G. Mortensen. Exploring thelimits of WAsP: The Wind Atlas Analysis and Ap-plication Program. In A. Zervos, H. Ehmann, andP. Helm, editors, Proc. EUWEC’96, Go¨teborg 1996,pages 584–587. H. S. Stephens & Associates, 1996.[2] A. J. Bowen and N. G. Mortensen. WAsP predic-tion errors due to site orography. Report Risø-R-995(EN), Risø National Laboratory, 1999.[3] H. P. Frank, O. Rathmann, N. G. Mortensen, andL. Landberg. The numerical wind atlas — theKAMM/WAsP method. Report Risø-R-1252(EN),Risø National Laboratory, June 2001.[4] N. G. Mortensen, L. Landberg, I. Troen, and E. L. Pe-tersen. Wind Atlas Analysis and Application Program(WAsP) Vol. 2: User’s Guide. Risø National Labora-tory, Roskilde, Jan 1993. Risø–I–666(v.2)(EN).[5] N. G. Mortensen and E. L. Petersen. Influence of to-pographical input data on the accuracy of wind flowmodelling in complex terrain. In R. Watson, editor,Proc. EWEC’97, Dublin 1997, pages 317–320. IrishWind Energy Association, 1998. ISBN 0-9533922-0-1.[6] A. M. Sempreviva, S. Larsen, N. G. Mortensen, andI. Troen. Roughness change effects for small andlarge fetches. Boundary-Layer Meteorol., 50:205–225, 1990.[7] I. Troen. A high resolution spectral model for flowin complex terrain. In 9th Symposium on Turbulenceand Diffusion, April 30 - May 3, 1990, Risø, RoskildeDenmark, pages 413–416. AMS, Boston, 1990.[8] I. Troen and E. L. Petersen. European Wind Atlas.Risø National Laboratory for the Commission of theEuropean Communities, Roskilde, Denmark, 1989.ISBN 87-550-1482-8.This work has been financed through the Danish En-ergy Research Project “The Numerical Wind Atlas – theKAMM/WAsP Method”, ENS-1363/98-0020.

Dependence of wind atlas data on the extent of topographic maps around a site

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Dependence of wind atlas data on the extent of topographic maps around a site

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