Wind in complex terrain. A comparison of WAsP and two ... - WindSim

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4 ResultsThe CFD-models are initialized based on assumptionsabout higher level (~500m) and lateral boundary levelwind speed and profiles. A logarithmic wind profile(corresponding to neutral stability conditions) isemployed at the boundaries in both models. Thus, inorder to compare the output of the CFD-models withany measurements, the modeled wind speed fieldshave to be scaled by use of the measurements. Forexample, for a specific annual wind speed from sectorS at 50 m at one of the sites, the output of the CFDmodelwill be assumed equal to the measurement atthis site. It is then further assumed that the wind fieldcan be scaled linearly based on the scaling at thisparticular site. By employing this method modelsimulations of the wind speed at all the measuringsites can be obtained. Thus it is assumed that the ratioof the modeled and measured values at one site willapply to the whole modeling domain. Thisassumption may not be valid everywhere in themodeling domain, but it is quite commonly applied tomodeling. In the following section we assess themodel simulations by using this method. The CFDmodelsare scaled to yield correct wind speed at the50 m level at Site 2 and Site 3 respectively, then theresults at the other measuring sites are extracted fromthe CFD-models.The WAsP model work differently. In order tomake the results from WAsP comparable to the CFDmodels,the measurements at 50 m from Site 2 andSite 3 are inserted in the model and the wind speed ofthe other measuring mast are obtained for the samesectors as utilized by the CFD-models.Note that the CFD-models were run only for thetwo sectors north (N) and south (S) to savecomputational efforts. Each sector covers 30°centered around 360° and 180° respectively.According to the wind rose (see Figure 2), thedirections N and S represent ca. 13% and 18% of thewind data respectively.4.1 Annual average wind speedIn Figure 3 the vertical profiles at site 2 have beenobtained based on a “true” solution at 50 m height atsite 3. For the southerly sector the wind direction isnearly perpendicular to the steep slope to the south ofsite 2 and a strong speed-up is encountered. BothWindSim and WAsP yield only small differencesfrom the observations, while 3DWind yields a largeoverestimation of the wind speed. For the northerlysector, the wind speed actually decreases from 10 mto 50 m at site 2. All three models underestimate thewind speed for this sector, still WAsP yields the bestresults in this particular case.A further comparison of the output of the modelsimulations with the observations has been carried out. Thethree models are all scaled to fit the observations at 50 mheight at either site 2 or site 3.Based on the scaled values of each of the two sites,the annual average wind speed is estimated at theother levels of the same mast (10m and 30m) andHeight (m)Height (m)605040302010Site 2 - S (scaled at site 3 50m)00.00 0.50 1.00 1.50 2.00605040302010Scaled windspeedSite 2 - N (scaled at site 3 50m)00.00 0.50 1.00 1.50 2.00Scaled windspeedOBSWASPWINDSIM3DWindOBSWASPWINDSIM3DWindFigure 3. Scaled vertical profiles at Site 2 for sector S(upper panel) and sector N (lower panel).Modelled2.001.801.601.401.201.000.800.600.400.200.00Obs vs model Sector S0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00ObservedWasp WINDSIM 3DWind
2.001.801.601.40Obs vs model Sector Nresults underline that a RIX-correction should alwaysbe supported by empirical data, and a generalizationof the method from one area to another is notrecommended.Modelled1.201.000.800.600.400.200.000.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00ObservedWasp WINDSIM 3DWindFigure 4. Observed vs. modelled annual normalizedwind speed for sector S (upper panel) and sector N(lower panel).at the three measuring levels of the other 50m mastand finally at 10 m at site 1. The results aresummarized in Figure 4 and Table 2. The totalnumber of data pointsWAsPSWind-Sim S3D-Wind SWAsPNWind-Sim N3D-WindNMAE 0.11 0.10 0.28 0.14 0.24 0.24COR 0.88 0.84 0.74 0.89 0.58 0.79Table 2: Mean Absolute Error (MAE) and correlationcoefficient (COR) of ratios between models andmeasurement. Each statistical parameter is based on12 data values.to be verified are 12, thus any statistical analysis hasto be interpreted with care since the data points arefew. For the sector S, WAsP and WindSim showsimilar behavior, while the errors are somewhatlarger for 3DWind. For sector N, WAsP givessomewhat surprisingly the best correspondence, whileWindSim has the lowest correlation. Based on theresults of Figure 3 and 4 and Table 2 we concludethat the errors are as large (and actually a littlelarger) for the CFD-models compared to WAsP forthe two sectors analyzed. This is an importantfinding, although we lack insight into the reasonswhy the CDF-models are unable to improve thesimulations at Gurskøy. In the following sections wepresent a discussion aiming to give a betterunderstanding of the modeling results.A RIX-analysis was carried out for the three sitesto check if the WAsP results could be improved. TheRIX-values using a radius of 2 km were 24.2%, 20%and 17.2% for the site 1, site 2 and site 3 respectively.In contrast to [3] no relationship between thedifferences in RIX-values and the prediction errorwas found. For example, employing the 10 mmeasurements at site 1 gave an over prediction of thewind speed at site 2 and 3, while an under predictioncould be expected from the RIX-analysis. These4.2 Turbulence and the directionaldependenceIn Figure 5 the turbulence intensities at site 3 ispresented. While 3DWind overestimates theturbulence for sector S WindSim gives too low values.For sector N both models are closer to theobservations, but still 3DWind over predicts whileWindSim under predicts. The same pattern isencountered for site 2 (not shown), and in othersimilar model experiments using 3DWind. Ourconclusion from these investigations is that the overprediction of the turbulence in 3DWind at site 3 mostprobable is linked to an underestimation of theaverage wind speed at the same site. This also leadsto the overestimation of the predicted average windspeed level of 3DWind at site 2 based on the windfield scale to site 3 (upper panel of Figure 3). InFigure 6 the turbulence pattern derived from 3DWindis presented for the wind directions 180° and 190°.Separated flow and strong turbulence is developed onthe lee side of the mountain to the south of the ridgewhere the three meteorological masts are located. Atboth sites 2 and 3 it is likely that the turbulenceintensities could be rather sensitive to the exact winddirection.From Figure 7 it is also noted that the annualaverage wind speed varies largely for different windspeed directions. The variability at site 2 for thedirection 170°, 180° and 190° is quite well capturedby 3DWind. It is also observed that the outcome ofHeight (m)605040302010Site 3 sector S00 0.05 0.1 0.15 0.2 0.25 0.3Turbulence intensityObs WindSIM 3DWind
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Page 8 and 9: Figure 10: Outer domain (red) and i
Page 10: Wind Energy, in press.[4]. WindSim

Wind in complex terrain. A comparison of WAsP and two ... - WindSim

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