Bremangerlandet, Bremanger, Sogn og Fjordane Wind analysis, production estimate and climatic conditions at Bremangerlandet wind farm Report number: KVT/RKTR/2011/R045 KVT/RKTR/2011/R045 Content 1 INTRODUCTION ................................................................................................. 3 2 METHODS AND INPUT DATA .................................................................................. 4 2.1 WIND MEASUREMENTS 4 2.2 MODEL DATA 5 2.3 REFERENCE DATA 5 2.4 TERRAIN AND ROUGHNESS DATA 5 2.5 LONG TERM EXTRAPOLATION OF THE WRF DATA 6 2.6 WASP MODEL 6 3 WIND CONDITIONS ............................................................................................. 8 3.1 WIND CONDITIONS 8 3.2 TURBULENCE AND VERTICAL WIND 9 3.3 ICING 9 4 WIND MAP AND ENERGY YIELD ............................................................................ 10 4.1 WIND MAP 10 4.2 ENERGY YIELD AND LOSSES 11 5 UNCERTAINTY ESTIMATES .................................................................................. 14 6 EXTREME WIND CONDITIONS ............................................................................... 15 6.1 EXTREME WIND ANALYSIS AT SVINØY LIGHTHOUSE 15 6.2 TRANSFERRING EXTREME WIND SPEEDS FROM SVINØY TO KRÅKENES 16 6.3 TRANSFERRING FROM EXTREME WIND SPEEDS FROM KRÅKENES TO BREMANGER 17 7 OTHER ENVIRONMENTAL CONDITIONS ................................................................... 19 7.1 TEMPERATURE 19 7.2 AIR DENSITY 20 8 SUMMARY ...................................................................................................... 22 9 REFERENCES .................................................................................................. 23 APPENDIX A: WRF DESCRIPTION ...................................................................................... 24 APPENDIX B: WINDPRO PRINTOUTS .................................................................................. 25 2/25 KVT/RKTR/2011/R045 1 Introduction This report gives an estimate of the long-term wind speed conditions and the energy production for the planned wind farm at Bremangerlandet. Extreme wind, density and temperature conditions are also considered. The wind analysis is based on WRF simulations and measurements in a telecommunication mast. An overview of the wind farm area, WRF points and the telecommunication mast is given in Figure 1-1. Turbulence and icing in the wind farm area are also considered. Figure 1-1 Overview of the WRF points and the telecommunication mast in the Bremangerlandet wind farm. 3/25 KVT/RKTR/2011/R045 2 Methods and input data 2.1 Wind measurements Wind measurements have been carried out from January 2008 at a telecommunication mast at Bremangerlandet, marked as 6401 Bremangerlandet in Figure 1-1. The permanent telecommunication mast has the two anemometers, one heated, and one wind vane mounted as shown in Figure 2-1. Table 2-1 has an overview of the main parameters of the sensors. The antenna system in the mast will influence at the measurements at all directions. Figure 2-1 Met mast at Bremangerlandet. Table 2-1 Overview of sensors Sensor Type Height [m] Comments Wind speed NRG #40 41.5 Boom direction 125° Wind speed NRG HAE ICE III 40.5 Boom direction 125° Wind dir NRG HVE Ice III 39.5 Boom direction 125° Temp NRG 110S 33.5 4/25 KVT/RKTR/2011/R045 2.2 Model data The wind analysis is based on the meso-scale model WRF (Weather Research and Forecast model). Kjeller Vindteknikk AS has calculated a wind map for Norway for the Norwegian Water and Energy Directorate(Byrkjedal 2009). A short description of the model is given in the Appendix. This wind map is based on one year of data from a simulation done by the meso-scale model WRF with a horizontal resolution of 1 km x 1km. As the terrain at Bremangerlandet is rather complex four WRF points are used in the analysis. The Figure 1-1 shows the four WRF point used in the analysis. The WindPRO (EMD 2008) /WAsP model(WAsP Manual 1993) are applied to calculate a wind map of the wind farm area in Bremangerlandet. 2.3 Reference data A simulation done with the same meso-scale model (as for the 1kmx1km simulation) was done with a horizontal resolution of 5kmx5km from 2000 to December 2010 to correct the one year simulation for long term variations. The 5kmx5km simulation domain is shown in Figure A1. Our experience with use of WRF data as reference data set has shown good consistency and correlation with measured data. Information of the data sets used in the analysis is seen in Table 2-2. Table 2-2 Details of the weather input data used in the production analysis. Position Site name (WGS84, UTM zone 32) WRF_8001 N6865819,E292680 WRF_8002 N6865904,E291662 WRF_8011 N6867005,E290727 WRF_8012 N6867090,E289708 WRF_6001 N6869286,E291794 2.4 Terrain and roughness data The WAsP/WindPRO model uses height contours, roughness values of the surface and wind statistics as input parameters. Local terrain data at Bremangerlandet are given in 20 meter contours. The roughness classification is done manually based on background maps and aerial photos. The roughness lengths applied to WindPRO/WAsP for different surface types are presented in Table 2-3. The roughness classification follows standard roughness values from the WAsP manual (WAsP Manual 1993). Table 2-3 Roughness lengths for different surface types Surface type Roughness length [m] Water 0.0002 Open area 0.03 Mixed village and agricultural area 0.2 Forest 0.5 5/25 KVT/RKTR/2011/R045 2.5 Long term extrapolation of the WRF data The long term extrapolation of the measurement data are carried out by a method called the Sector-Bin method. Documentation of the method can be found in (Harstveit 2004). A Sector Bin method uses partial coefficients placed in a 13x13 matrix according to the closest 30° direction, including calm. Each cell in the matrix is then defined by the ratio of the wind speed measured in the corresponding sectors at the reference station and site. The partial coefficients are integrated for each sector at the site to yield a weighted transformation matrix mapping the reference stations values to site. The final uncertainty of the long-term estimate depends on the length of the time series, the standard deviation of annual mean values, the homogeneity of the reference series, the model uncertainty and the correlation between the reference and measured data. 2.6 WAsP model The WindPRO/WAsP models are applied to calculate a wind map of the wind farm area in Bremangerlandet and the energy output of the wind farm. The WAsP model is used as a tool for the horizontal extrapolation of the measurements. This is a linearized micro-scale flow model further described by (Bowen og Mortensen 1996) and the WAsP manual (1993). Linearized models are unable to predict flow separation, and this is a problem in complex terrain. To correct for the expected nonlinear influence of the flow field an empirical method called ΔRIX correction has been developed. This method uses the RIX factor as a measure of the complexity of a location. RIX is short for Ruggedness Index, and is a measure of how large part of the surrounding area that has a steepness above a given threshold. WindPro suggest a RIX radius of 3.5km. An analysis based on experimental results described by (Berge, et al. 2006) has studied several RIX radiuses. The best practice from this paper is to define the RIX number as the fraction of the terrain within a radius of 2km with a slope exceeding 30%, corresponding to 16.7º. The velocity correction in a point is made based on the difference, ΔRIX, from the RIX- value of the measurement location according to the formula: ,where UWAsP∆RIXcorr is the ∆RIX-corrected wind speed of the WAsP estimated wind speed, UWAsP . Generally the uncertainty of the horizontal extrapolation is smallest if the ΔRIX level is small, and increasing with increasing ΔRIX level. For high RIX values the model is operating outside its physical limits. Bremangerlandet is a very complex area and the RIX calculation can be around the physical limits of the WAsP model. Several RIX radiuses from 0.5km to 3.5km are therefore tested. Maximum RIX values are rather high for all RIX radiuses tested. KVT has therefore chosen to present two wind maps based on RIX radiuses of WindPRO and (Berge, et al. 2006). An important feature of the WAsP model is the capability of generalizing the measured observation at a local site into a regional wind climate – the so-called wind atlas. Once a wind atlas is established the local wind conditions at any site where the wind atlas is valid, can be calculated. We have now taken the advantage of this approach in order to map the WRF- calculations into the local height contours and surface roughness. The following procedure has been applied: 6/25 KVT/RKTR/2011/R045 - WAsP is set up with the WRF-terrain and roughness. The annual average wind speed at 80 m height above ground level is extracted from WRF at 4 different points in the wind farm (see Figure 1-1). - 4 wind atlases from WAsP are then derived based on each of these 4 data points. - The wind atlases, local topography (20 meter equidistance) and roughness values (Arial photos) are used to calculate 4 wind maps in the area of the wind farm with a horizontal resolution of 50 m in WAsP. - The 4 wind maps are ΔRIX corrected and weighted based on the distance to the WRF points and a final wind map for the entire wind farm is presented in Section 4.1. 7/25 KVT/RKTR/2011/R045 3 Wind conditions 3.1 Wind conditions The heated anemometer at 40.5 meter is compared to WRF data in the measuring period. The measurements contain several periods of missing data. The correlation between WRF and the measurements are listed in Table 3-1, from around 0.9 for southerly winds to 0.2 for north- north westerly winds. The directional scaling factor between the measurements and the WRF data shows large variation for each sector due to influenced measurements by the mast. KVT has therefore chosen to use WRF data and not the measurements in the calculation of the wind map at Bremangerlandet wind farm.