Improving WAsP predictions in (too) complex terrain Niels G. Mortensen and Ioannis Antoniou Risø National Laboratory Anthony J. Bowen University of Canterbury 2006 EWEC 2 March 2006

Outline Case study in northern Portugal RIX and RIX concepts RIX configuration Correction procedure Improving WAsP predictions in (too) complex terrain? Wind farm verification Conclusions

Case study in northern Portugal

Cross-correlation of wind speeds (From Bowen and Mortensen, 1996 EWEC conference)

Effect of a steep hill – flow separation The flow behaves – to some extent – as if moving over a virtual hill with less steep slopes than the actual hill => actual speed-up is smaller than calculated by WAsP N. Wood (1995). “The onset of flow separation in neutral, turbulent flow over hills”, Boundary-Layer Meteorology 76, 137-164.

Complex terrain analysis Ruggedness index, RIX fraction of terrain surface which is steeper than a critical slope c Calculation radius ~ 3.5 km Critical slope c ~ 0.3 Onset of flow separation Performance envelope for WAsP is when RIX = 0 Performance indicator, RIX ΔRIX = RIXWTG – RIXMET ΔRIX < 0  under-prediction ΔRIX > 0  over-prediction Terrain steeper than c is indicated by the thick red (radial) lines

Prediction error vs. RIX difference “This performance indicator provides encouraging results…” (Bowen and Mortensen, 1996 EWEC conference)

The Ruggedness Index revisited Reanalyses of Portuguese data sets Larger and more detailed maps (SRTM 3) Improved RIX calculation Calculation implemented in WAsP and ME More calculation radii: 72 rather than 12 RIX configuration corresponds to BZ-model grid Improved predicted wind climate and power production Emergent wind speed distribution Both the prediction errors and RIX change

Maps for RIX calculation and modelling Hand-digitised map 8 by 8 km2 50- and 10-m cont. SRTM-derived map  20 km diameter 50-, 10- and 5-m height contours + spot heights

Wind speed prediction error vs. RIX

ln(Up/Um) vs. RIX Up = Um exp( RIX) where  = 1.5 R = 3500 m and c = 0.3

Influence of radius and critical slope R [m] Critical slope c 0.30 0.35 0.40 0.45 3000 0.960 0.967 0.978 0.973 3500 0.972 0.974 0.984 0.986 4000 0.971 0.982 0.979 5000 0.969 0.977 Wind speed prediction error is (almost) fixed… Number of sectors Modelling parameters RIX configuration can be varied easily Original configuration somewhat arbitrary… Different calculation radii: 3, 3.5, 4, and 5 km Different critical slopes: 0.30, 0.35, 0.40, 0.45 Matrix of R2 (coefficient of determination) for different configurations Weighting RIX with wind rose frequencies R2 for different values of the calculation radius and critical slope.

Influence of calculation height Vertical wind profile in complex terrain with RIX = 16% 40-m anemometer used as predictor Vertical profile is predicted well because of similarity in ruggedness index: ΔRIX = 0

Improving WAsP predictions in complex terrain Analysis procedure: Observed Wind Climate + sheltering obstacles + roughness map + elevation map Regional Wind Climate Application procedure: Predicted Wind Climates + power and thrust curves Predicted wind farm AEP Post-processing: Insert WTG at met. stations Make cross-predictions @ hhub Plot ln(Pp/Pm) vs. RIX Linear fit Pp = Pm exp( RIX) Slope of trend line  Correct production estimates: Apply correction factor Pm = Pp/exp( RIX) Corrected gross AEP Apply wake model results Corrected net AEP

ln(AEPp/AEPm) vs. RIX @ 50 m a.g.l.

Step 1-2: AEP [GWh] = F(WAsP)

Step 3-4: AEP [GWh] = F(WAsP, RIX)

Case study summary WAsP predictions in (too) complex terrain were improved 69% on average for five sites with 10% < RIX < 33% 88% on average for sites with ∆RIX > 10% In addition, we have found SRTM 3 data can be applied for wind resource assessment optimal configuration values for ruggedness index calculation an empirical relation between WAsP prediction error and ∆RIX Can this be verified elsewhere?

Wind farm in complex terrain Elevation map w/ 20-m contours 23-MW wind farm w/ 38 turbines Two reference met. stations () RIX coloured map, range 0-18% Turbine site RIX range: 4-14% Met. station RIX range: 4-5%

Prediction of power production Measured power productions, wind speeds and directions over one year available for analyses Measured wind farm power production overestimated by 13% using standard WAsP procedure Correction procedure applied: Correction based on Portuguese data set (similarity) Percentage applied to each turbine site Corrected wind farm power curve applied After correction, the power production is overestimated by 3% Prediction of actual AEP improved by 70% Site is also partly forested…

Conclusions Ruggedness index RIX and performance indicator RIX Concepts supported by new data and procedures Optimum radius and slope for RIX determined (RIX, U) relation not very sensitive to calculation radius R, critical slope c, or prediction height h Relation between WAsP prediction errors and RIX Linear relation between ln(Up/Um) or ln(Pp/Pm) and RIX RIX weighted with the wind rose does not improve the relation between ln(Up/Um) and RIX Correction procedure outside WAsP operational envelope Percentage can be applied to each turbine site Note, that all this is purely empirical… Similarity of sites: ridges, escarpments and mountain tops constant  should be determined for site and height Extension of WAsP procedures outside operational envelope Requires two or more (non-similar) met. stations Linear relation between ln(Pp/Pm) and RIX Case study predictions improve significantly Linear fit after extended procedure AEPP = 1.01 AEPM (R2 = 0.92) Procedure can be applied with (2…n) met. stations Procedure is purely empirical and should therefore be tested with other data sets…