1. 2-D data discussion Raymond Byrne DKiT, Ireland Maeva Sabre CSTB, France

2. Data Summary 1 minute averages (2D) I - wind speed - wind speed standard deviation - wind direction - wind direction standard deviation - air pressure - % relative humidity - ambient temperature - power output

3. 2-D data from customer field sites in IR There are approximately 16 customer sites with logged data for ~ 1 year (some more, some less). At two of the sites there is, in addition, 1 second data recorded for around 1 month. The sites all contain HAWTs and consist of a mix of upwind and downwind machines. Although the data may not be suitable for what you are looking for it may be useful for some of the following: a) Wind speed distributions - are they adequately described by Weibull? b) The range of turbulence intensities and directions standard deviations observed across the sites c) Trends in power performance of turbines in relation to turbulence intensity and directional standard deviation d) How the performance of upwind turbines compare to downwind wind turbines in varying degrees of turbulence intensity and directional standard deviation e) How does observed AEP compare to predicted AEP by current IEC small wind standard

4. No_SN CR200_Wind_Ambient.CR237057Meteo_DataPgo_Avg TIMESTAMPWS_Top_AvgWind_Dir_AvgWind_Dir_StdWS_Top_StdBP_mbarRHAirTCWatts TSmeters/sec mbar%Deg CAvg "2011-04-01 00:00:00"5.285001190.28579.8623050.9573966996.468588.7241111.17677959.9999 "2011-04-01 00:01:00"6.811667200.58867.935841.152258996.468588.7241111.176771740 "2011-04-01 00:02:00"5.715195.1338.5042771.234616996.468588.7241111.17677899.9999 "2011-04-01 00:03:00"5.97198.34977.7815581.880009996.468588.7241111.176771140 "2011-04-01 00:04:00"5.653335197.42489.8311260.9798748996.468588.7241111.17677779.9999 "2011-04-01 00:05:00"6.27195.59686.4482981.024418996.468588.7241111.17677720 "2011-04-01 00:06:00"6.193334196.307413.343551.062208996.468588.7241111.176771200 "2011-04-01 00:07:00"7.088334197.48549.7163831.005334996.468588.7241111.176771500 "2011-04-01 00:08:00"7.118333204.90888.9486561.397318996.468588.7241111.176771320 "2011-04-01 00:09:00"7.698335205.927.0193421.585401996.468588.7241111.176771859.999 "2011-04-01 00:10:00"7.848335201.39527.7636080.8645793996.468588.7241111.176772099.999 "2011-04-01 00:11:00"7.25202.67436.4571921.164116996.468588.7241111.176772159.999 "2011-04-01 00:12:00"6.336667202.094210.105251.255649996.468588.7241111.176771320 "2011-04-01 00:13:00"7.705205.09966.3364620.9769731996.468588.7241111.176771500 "2011-04-01 00:14:00"5.645204.26598.4925070.8436872996.468588.7241111.176771140 "2011-04-01 00:15:00"6.516667203.74818.2926871.321888996.468588.7241111.176771380 "2011-04-01 00:16:00"6.918334205.32797.5625860.7864457996.468588.7241111.176771500 "2011-04-01 00:17:00"6.191667204.31497.692920.9272349996.468588.7241111.176771320 "2011-04-01 00:18:00"6.83197.56559.6271661.118079996.468588.7241111.176771440 "2011-04-01 00:19:00"8.513331196.8798.4244471.430902996.468588.7241111.176772880.001 "2011-04-01 00:20:00"7.918333199.69417.8319541.55483996.468588.7241111.176772099.999 "2011-04-01 00:21:00"7.31203.18919.3774281.667503996.468588.7241111.176772460 "2011-04-01 00:22:00"7.070001202.49467.9121951.312034996.468588.7241111.176771980 "2011-04-01 00:23:00"6.64207.45119.5036480.8041975996.468588.7241111.17677839.9999 "2011-04-01 00:24:00"7.028334203.42879.1630060.9457081996.468588.7241111.176771380 "2011-04-01 00:25:00"7.233334200.86698.7694310.9618847996.468588.7241111.176771620 "2011-04-01 00:26:00"7.725201.601610.221311.105083996.468588.7241111.176772640 "2011-04-01 00:27:00"6.536667206.03226.7920240.6324468996.468588.7241111.176771140 "2011-04-01 00:28:00"6.206665204.60526.775290.7924364996.468588.7241111.176771200 "2011-04-01 00:29:00"6.663335200.50337.3600720.8899376996.468588.7241111.176771440 "2011-04-01 00:30:00"7.473334203.12447.5956341.587647996.468588.7241111.176771680 "2011-04-01 00:31:00"8.473334203.96737.6743680.8453534996.468588.7241111.176772580

5. Maeva’s thoughts Using 2D data to characterize turbulence in urban area is not obvious because of the vertical component w of the wind that is more important in urban area than in rural one. The turbulence scale is a function of the density of the buildings and their heights. The vertical component is an important factor to define the dynamic behavior of the SWT and the requests/solicitations to which they are subjected. But if we just need to have an idea of the wind potential, 2D can be enough because the SWT will have the best answer for horizontal wind, perpendicular to its axe.