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2 CNS Meteorological System Upgraded 100-meter tower in 2004 to include a dual elevator on the same tower face Dual monitoring systems with independence from sensor to Plant Computer Wind Sensors have Cups/Vanes on one side and Sonic on the other

3 Meteorological Parameters Systems A and B 10, 60, and 100 meter wind speed and direction 3 Delta-ts (60m-10m, 100m-10m, 100m-60m) 10, 60, and 100 meter temperatures System A only 10 meter dew point Station Pressure Precipitation

4 Meteorological Equipment System A Climatronics F460 Wind speed and Direction Sensors Climatronics Temperature Sensors Tower Systems Elevator Climatronics Dew Point Sensor Climatronics Tipping Bucket Rain gauge with Wind Shield Campbell Scientific 23X Micro Dataloggers Climatronics Pressure Sensor

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6 Meteorological Equipment System B Met One 50.5 Sonic Wind speed and Direction Sensors Climatronics Temperature Sensors Tower Systems Elevator Campbell Scientific 23X Micro Dataloggers

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10 Purpose Independently verify wind data collected from both systems are not statistically different Data from System A (cup/vane) can be interchanged with data from System B (sonic) Demonstrate the impact of the tower structure on meteorological data

11 Data Set One year of onsite validated hourly meteorological data (October 31, 2004 October 30, 2005) 8784 possible hourly values for each parameter for both Systems A and B on the 100-meter tower

12 Methodology Remove bad data from System A and System B files including calibrations, frozen sensors, failed sensors, bad data spikes, etc Remove wind directions when wind speeds less than 3 mph and/or wind directions are through tower Remove wind speeds when wind directions are through tower

13 Table 3 1 Invalid Data for CNS Onsite Meteorological Program October 31, 2004 October 30, 2005 Parameter Missing/Bad Data Hours Problem All Parameters (A&B) 3/ / / / Spring Calibration All Parameters (A System Only) 8/ / Troubleshoot All 3 levels down All Parameters (A&B) 9/ / Fall Calibration 100 Meter Wind Speed (A) 1/ / / / (B) 1/ Frozen Sensor Bad Data-Spike 60 Meter Wind Speed (A)1/ /9/ / / / / (B) 1/ Frozen Sensor/Sensor Failure Bad Data-Spike 10 Meter Wind Speed (A)1/ / Frozen Sensor 100 Meter Wind Direction (B) 1/ Bad Data-Spike 60 Meter Wind Direction (B) 1/ Bad Data-Spike

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18 Wind Directions from degrees blow through tower Window is 25 degrees for vane and cup sensors and 30 degrees for sonic sensor

19 Data Availability 100- meter wind speed 82% 60-meter wind speed 87% 10-meter wind speed 88% 100-meter wind direction 84% 60-meter wind direction 45% 10-meter wind direction 70%

20 Results Unobstructed with no tower influence

21 Wind Speed Averages Hours A Avg. B Avg. Diff. Abs. 100-M WS 60-M WS 10-M WS

22 Wind Speed Correlation Hours Diff. Slope Y-int. Corr. 100-M WS 60-M WS 10-M WS

23 Figure 1: 100-Meter Wind Speed Regression y = x Observations: 7183 Correlation: Meter A (Cup) Wind Speed Meter B (Sonic) Wind Speed

24 Figure 2: 60-Meter Wind Speed Regression y = x Observations: 7637 Correlation: Meter A (Cup) Wind Speed Meter B (Sonic) Wind Speed

25 Figure 3: 10-Meter Wind Speed Regression y = x Observations: Correlation: Meter A (Cup) Wind Speed Meter B (Sonic) Wind Speed

26 Wind Direction Averages Hours A Avg. B Avg. Diff. Abs. 100-M WD 60-M WD 10-M WD

27 Wind Direction Correlation Hours Diff. Slope Y-int. Corr. 100-M WD 60-M WD 10-M WD

28 Figure 4: 100-Meter Wind Direction Regression y = x Observations: 7375 Correlation: Meter A (Vane) Wind Direction Tower interference Meter B (Sonic) Wind Direction

29 Figure 5: 60-Meter Wind Direction Regression y = x Observations: 3970 Correlation: Meter A (Vane) Wind Direction Tower interference Meter B (Sonic) Wind Direction

30 Figure 6: 10-Meter Wind Direction Regression y = x Observations: 6148 Correlation: Meter A (Vane) Wind Direction Tower interference Meter B (Sonic) Wind Direction

31 Tower Impacts Wind Speed and Direction

32 Wind Directions from degrees blow through tower Window is 25 degrees for vane and cup sensors and 30 degrees for sonic sensor

33 100-m Wind Speed Averages Tower Impact Hours A Avg. B Avg. Diff. Abs. 100-M WS-A 100-M WS-B

34 100-m Wind Speed Correlation Tower Impact Hours Diff. Slope Y-int. Corr. 100-M WS-A 100-M WS-B

35 Figure 10: 100-meter Wind Speed Regression When Tower Impacts System A (Cups) y = x Observations: 409 Correlation: Meter A (Cup) Wind Speed Meter B (Sonic) Wind Speed

36 Figure 11: 100-Meter Wind Speed Regression When Tower Impacts System B (Sonic) Meter System A (Cup) Wind Speed y = 1.681x Observations: 268 Correlation: Meter B (Sonic) Wind Speed

37 60-m Wind Speed Averages Tower Impact Hours A Avg. B Avg. Diff. Abs. 60-M WS-A 60-M WS-B

38 60-m Wind Speed Correlation Tower Impact Hours Diff. Slope Y-int. Corr. 60-M WS-A 60-M WS-B

39 Figure 12: 60-Meter Wind Speed Regression When Tower Impacts System A (Cups) y = x Observations: 364 Correlation: Meter A (Cup) Wind Speed Meter B (Sonic) Wind Speed

40 Figure 13: 60-Meter Wind Speed Regression When Tower Impacts System B (Sonic) Meter B (Sonic) Wind Speed y = x Observations: 285 Correlation: MeterA (Cup) Wind Speed

41 10-m Wind Speed Averages Tower Impact Hours A Avg. B Avg. Diff. Abs. 10-M WS-A 10-M WS-B

42 10-m Wind Speed Correlation Tower Impact Hours Diff. Slope Y-int. Corr. 10-M WS-A 10-M WS-B

43 Figure 14: 10-Meter Wind Speed Regression When Tower Impacts System A (Cups) 25.0 y = 0.801x Observations: 394 Correlation: Meter A (Cup) Wind Speed Meter B (Sonic) Wind Speed

44 Figure 15: 10-Meter Wind Speed Regression When Tower Impacts System B (Sonic) Meter A (Cup) Wind Speed y = x Observations: 225 Correlation: Meter B (Sonic) Wind Speed

45 100-m Wind Direction Averages Tower Impact Hours A Avg. B Avg. Diff. Abs. 100-M WD-A 100-M WD-B

46 100-m Wind Direction Correlation Tower Impact Hours Diff. Slope Y-int. Corr. 100-M WD-A 100-M WD-B

47 Figure 16: 100-Meter Wind Direction Regression When Tower Impacts System A (Vane) y = x Observations: Meter A (Vane) Wind Direction Correlation: Meter B (Sonic) Wind Direction

48 Figure 17: 100-Meter Wind Direction Regression When Tower Impacts System B (Sonic) y = x Observations: Meter A (Vane) Wind Direction Correlation: Meter B (Sonic) Wind Direction

49 10-m Wind Direction Averages Tower Impact Hours A Avg. B Avg. Diff. Abs. 10-M WD-A 10-M WD-B

50 10-m Wind Direction Correlation Tower Impact Hours Diff. Slope Y-int. Corr. 10-M WD-A 10-M WD-B

51 Figure 18: 10-Meter Wind Direction Regression When Tower Impacts System A (Vane) Meter A (Vane) Wind Direction y = x Observations: 402 Correlation: Meter B (Sonic) Wind Direction

52 Figure 19: 10-Meter Wind Direction Regression When Tower Impacts System B (Sonic) Meter A (Vane) Wind Direction y = x Observations: 80 Correlation: Meter B (Sonic) Wind Direction

53 Conclusions Outside of Tower wake impacts, Systems A and B are statistically the same for WS/WD. Outside of Tower wake impacts, all differences are small. WD small bias likely due to alignment errors during calibration.

54 Conclusions (cont d) Cup anemometer records wind speed on average 1mph higher than sonic likely due to overspeeding. Tower wake has greatest impact on wind speed. Differences up to 10 mph seen at wind speeds above 25 mph. Appears the wind speed tower impact is largest on sonic sensors but is it? Data from either system are interchangeable

55 Conclusions (cont d) Tower wake has little to no impact on wind direction on either vane or sonic sensors. Data from either System A (cups/vanes) or System B (sonic) are interchangeable outside of tower wake. Within wake, data scrutiny is needed either manually or with software.