Vindanalyse, Kjeller Vindteknikk
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Vedlegg G: Vindanalyse, Kjeller Vindteknikk Storehei, Oddeheia and Bjelkeberget, Birkenes kommune, Aust-Agder, Norway Pre-analysis of energy yield estimate Report: KVT/ALL/2013/R003 rev.1 KVT/ALL/ZO13/ROO3 rev.1 Report number Date KVT/ALL/2013/ROO3 rev.1 25.01.2013 Report Title Availability Limited to client Storehei, Oddeheia and Bjelkeberget, Birkenes Revision number kommune, Aust-Agder, Norway 1 Pre-analysis of energy yield estimate Client Number of pages E.ON Sverige AB 23 + Appendix Client Reference Status Martin Westin Final Summary Energy yield calculations for the three possible wind farm areas in Aust-Agder are presented in this report. The wind data used for the calculations are from the meso-scale model WRF. The mean wind speed at hub height 119 m is estimated to be 7.8 m/s for Storehei, 7.3 m/s for Oddeheia and 7.6 m/s for Bjelkeberget. Due to the short distance between the wind farms, the neighboring parks will cause increased wake losses. The reduction in net energy yield is approximately 0.2 % for Storehei, and approximately 1% for Oddeheia and Bjelkeberget, assuming that all the three sections are build. In addition to the wake losses additional losses of 13 % for Storehei, and 12 % for Oddeheia and Bjelkeberget is assumed. The energy yield calculations are summarized below. Park Turbine Installed capaCIty Wake loss Net energy yield Full load hours [MW] [%] [GWh] [h] Storehei Vestas V112 89.2 5.0 290.0 3252 Storehei Siemens SWT-3.0-113 87.0 5.6 298.9 3436 Storehei RePower 3.2M 114 92.8 5.0 298.7 3218 Oddeheia Vestas V112 33.8 4.3 99.8 2951 Oddeheia Siemens SWT«3.0-113 33.0 4.8 103.5 3136 Oddeheia RePower 3.2M 114 35.2 4.3 103.0 2925 Bjelkeberget Vestas V112 55.4 5.0 175.3 3168 Bjelkeberget Siemens SWT-3.0-113 54.0 5.6 180.9 3351 Bjelkeberget RePower 3.2M 114 57.6 5.0 180.8 3139 The uncertainty of the energy yield calculations is expected to be about 30 %. The high uncertainty level is due to the use of model data instead of wind measurements, the micro scale modeling in relatively complex terrain, the energy loss assumptions and the energy sensitivity. Disclaimer Although this report, to the best of our knowledge, represents the state-of-the-art in wind energy assessment methods, and effort have been made to secure reliable results, Kjeller Vindteknikk AS cannot in any way be held responsible neither to the use of the findings in the report nor for any direct or indirect losses arising from such use or from errors of any kind in the contents. Revision history Rev. number Date Number of copies Comment Distribution 0 22.01.2013 Only electronic Original version 1 25.01.2013 Only electronic Correct version power curve V112 Name Date Signature Prepared by Anne Line Løvholm 13 W 1012p) f” LUNTÅG/nc. h— Reviewed by Lars Tallhaug 17 f), Luff L . Approved by Finn K. Nyhammer 0L )/-l 026 Bgl 7M /( A Hm 111 (;1/ 1 KVT/ALL/2013/R003 rev.1 Content 1 INTRODUCTION ................................................................................................. 3 2 INPUT DATA ..................................................................................................... 4 3 WIND ANALYSIS METHOD ..................................................................................... 5 4 WIND CONDITIONS ............................................................................................. 7 4.1 STOREHEI 7 4.2 ODDEHEIA 10 4.3 BJELKEBERGET 13 5 ICING ........................................................................................................... 16 6 ENERGY YIELD CALCULATIONS ............................................................................ 18 6.1 STOREHEI 19 6.2 ODDEHEIA 19 6.3 BJELKBERGET 20 7 UNCERTAINTY ................................................................................................ 21 8 SUMMARY ...................................................................................................... 22 9 REFERENCES .................................................................................................. 23 APPENDIX A. WRF ................................................................................................... 24 APPENDIX B. WIND MAPS ........................................................................................... 25 APPENDIX C. POWER CURVES ..................................................................................... 32 APPENDIX D. WINDPRO PRINTOUTS .............................................................................. 33 2 KVT/ALL/2013/R003 rev.1 1 Introduction This report describes the pre-analyses for the energy yield at three wind farm sites in Birkenes, Aust-Agder. The wind farm areas are shown in Figure 1-1. The wind farms are located close to each other. The wind map for Norway shows that the wind conditions in the three park areas are similar. The elevation of the project area at Bjelkeberget is on average 325 m.a.s.l., the average elevation at Storheia is 354 m.a.sl. and the average elevation at Oddeheia is 317 m.a.sl.. The landscape is characterized by forested hills. The terrain within the wind farm areas are relatively flat, but there are some complex terrain in the surroundings of the wind farms. The layouts are specified by E-On. The layout at Bjelkberget consists of 18 turbines, the layout at Storheia consist of 29 turbines and the layout at Oddeheia consists of 11 turbines. The total installed capacity of each wind farm is 54 MW, 33 MW and 87 MW for Bjelkberget, Storheia and Oddeheia respectively. In this report the data used for the analyses are presented. Thereafter the wind climate at each of the wind farms is presented with key parameters and wind maps. In section 5 the icing map of the region is presented. Section 6 and section 7 include the energy yield calculations for each of the wind farms and a discussion of the uncertainty for the energy yield calculations. Figure 1-1: Map of the three wind farm areas in Birkeland. 3 KVT/ALL/2013/R003 rev.1 2 Input data Data from the meso-scale meteorological model WRF (Weather Research and Forecast model) are used for modeling the wind conditions at Storeheia, Oddeheia and Bjelkberget. The model is described in detail and further references are given in Appendix A. The terrain is described with height contours with equidistance equal to 5 m within and close to the park area. The roughness classifications are based aerial photos from www.statkart.no and from pictures provided by the customer. The turbine positions for the three areas are specified by the customer. The energy yield calculations are carried out for three turbine models. The turbine specifications used for the calculations are either from the EMD database (EMD 2008) or from E-On. The wind farms are located in a forested area. Representatives from Kjeller Vindteknikk have not been at the sites to evaluate the forest, but some pictures from a site visit are provided. Based on the provided pictures and the aerial photos the zero displacement height is estimated to 5 m. 4 KVT/ALL/2013/R003 rev.1 3 Wind analysis method Time series from the WRF model are used for calculation of the wind conditions in the area. A time series from a model run with geographical resolution of 1 km * 1 km and length of one year and a time series from a model run with geographical resolution of 4 km * 4 km with length of 12 years are used for the calculations. The short time series with high spatial resolution are expected to give the best description of the local wind climate at the sites. To estimate the expected long term wind climate, the short time series are long term corrected with the time series with length of 12 years. The long term correction of the wind climate is carried out with the sector bin method (Harstveit 2004). The geographical position of the model grid points and the length of the time series are given in Table 3-1. The wind data from WRF are from a model level with height 113 m above zero displacement height in the meso-scale model. Table 3-1: WRF model grid points used for the analysis. WRF model grid point Coordinates, WGS 84 UTM 33 Length 3050_Bjelkberget E: 106552, N: 6496768 1 year 3060_Bjelkberget E: 106497, N: 6495985 1 year 3050_Bjelkberget E: 106165, N: 6496436 12 year 3020_Storehei E: 102077, N: 6500483 1 year 3030_Storehei E: 100634, N: 6497680 1 year 3080_Storehei E: 102759, N: 6496768 1 year 3030_Storhei E: 102353, N: 6497685 12 year 3001_Oddeheia E: 108829, N: 6498433 1 year 3010_Oddeheia E: 110930, N: 6499291 12 year As noted in section 2 we have assumed a 5 m displacement height due to the forest of the area. The WRF model is not taking the displacement height explicitly into account in the calculations. In areas with forest, the height level of the calculated WRF data must be interpreted as above the displacement height and not the ground level. For example, for WRF data extracted from the 100 m model level, the zero displacement height of 10 m must be added to find the valid level above ground, which in this case will correspond to 110 m. The local wind maps for the different areas have been calculated with the micro-scale model WindSim (WindSim u.d.) The long-term corrected wind statistics from the WRF model is used as input parameter for the calculations. Both the vertical and the horizontal extrapolation are done in the micro-scale model. The roughness classification is summarized in Table 3-2. The roughness classification follows standard roughness values (WAsP Manual 1993), which also applies for other micro-scale models. WindSim is selected as the appropriate micro-scale model for these sites due to the relatively complex terrain in the surroundings of the wind farms. The areas within the park limits are flat for all the three areas, however the complex terrain around the parks will influence the wind conditions within the parks. The effects of the complex terrain, such as lowered wind speed due to turbulence, is expected to be captured in the calculations done in the CFD micro-scale model. Wind maps are calculated for several meso-scale wind statistics and different placements of the wind statistics are evaluated. The wind statistics which resulted in a coherent result for the wind farms were evaluated as most reliable and selected for the study.