north american technical center

��

��

��

��

��

��

��

�� !��"

"��#��$%%&

��

�� !��"

"��#��$%%&

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

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

Meteorological Parameters

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

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

Meteorological Equipment

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

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

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

Table 3–1 Invalid Data for CNS Onsite Meteorological ProgramOctober 31, 2004 – October 30, 2005

Bad Data-Spike3(B) 1/21 1900 – 210060 Meter Wind Direction

Bad Data-Spike9(B) 1/12 0800 – 1600100 Meter Wind Direction

Frozen Sensor151(A)1/3 0700 – 1/9 130010 Meter Wind Speed

Frozen Sensor/Sensor Failure

Bad Data-Spike

4153

3

(A)1/3 0700 – 1/9/ 13004/2 0600 – 8/13 16009/28 1900 – 10/31 2400(B) 1/21 1900 – 2100

60 Meter Wind Speed

Frozen Sensor

Bad Data-Spike

221

9

(A) 1/3 0700 – 1/9 13002/6 2300 – 2/9 2100(B) 1/12 0800 – 1600

100 Meter Wind Speed

Fall Calibration819/26 0900 – 09/29 1700All Parameters (A&B)

Troubleshoot – All 3 levels down

258/3 0800 – 8/4 0800All Parameters(A System Only)

Spring Calibration1033/29 1400 – 4/1 12004/4 0800 – 4/5 1500

All Parameters (A&B)

ProblemHoursMissing/Bad DataParameter

• Wind Directions from 195-245 degrees blow through tower

• Window is 25 degrees for vane and cup sensors and 30 degrees for sonic sensor

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%

Results

Unobstructed with no tower influence

Wind Speed Averages

0.90.97.07.8775410-MWS

1.61.510.311.8763760-MWS

1.41.412.813.97433100-MWS

Abs.Diff.B Avg.A Avg.Hours

Wind Speed Correlation

0.990.621.010.9775410-MWS

0.990.841.061.5763760-MWS

0.980.951.021.47433100-MWS

Corr.Y-int.SlopeDiff.Hours

Figure 1: 100-Meter Wind Speed Regression

y = 1.0159x + 0.9484

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0

100-Meter B (Sonic) Wind Speed

100-

Met

er A

(Cup

) Win

d S

peed

Observations: 7183

Correlation: 0.98


y = 1.0621x + 0.8437

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0


60-M

eter

A (C

up) W

ind

Spe

ed

Observations: 7637

Correlation: 0.99


y = 1.0141x + 0.6284

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0


10-M

eter

A (C

up) W

ind

Spe

ed

Observations: 7754

Correlation: 0.99

Wind Direction Averages

7.06.7189195614810-MWD

4.03.6180184397060-MWD

3.02.61821847375100-MWD


Wind Direction Correlation

0.993.081.026.7614810-MWD

0.991.301.033.6397060-MWD

0.990.871.022.67375100-MWD


Figure 4: 100-Meter Wind Direction Regression

y = 1.0191x - 0.8727

-50

0

50

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350 400

100-Meter B (Sonic) Wind Direction

100-

Met

er A

(Van

e) W

ind

Dir

ectio

n

Observations: 7375

Tower interference

Correlation: 0.99


y = 1.0271x - 1.2974

-50

0

50

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350 400


60-M

eter

A (V

ane)

Win

d D

irec

tion

Observations: 3970

Tower interference

Correlation: 0.99


y = 1.0191x + 3.0831

0

50

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350 400


10-M

eter

A (V

ane)

Win

d D

irec

tion

Observations: 6148

Tower interference

Correlation: 0.99

Tower Impacts

Wind Speed and Direction

• Wind Directions from 195-245 degrees blow through tower

• Window is 25 degrees for vane and cup sensors and 30 degrees for sonic sensor

100-m Wind Speed AveragesTower Impact

6.16.17.313.4266100-MWS-B

3.0-2.712.710.0409100-MWS-A


100-m Wind Speed Correlation Tower Impact

0.891.111.686.1266100-MWS-B

0.921.860.64-2.7409100-MWS-A


Figure 10: 100-meter Wind Speed Regression When Tower Impacts System A (Cups)

y = 0.6409x + 1.8626

0.0

5.0

10.0

15.0

20.0

25.0

30.0

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0100-Meter B (Sonic) Wind Speed

100-

Met

er A

(Cup

) Win

d S

peed

Observations: 409

Correlation: 0.92

Figure 11: 100-Meter Wind Speed Regression When Tower Impacts System B (Sonic)

y = 1.681x + 1.1097

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

0.0 5.0 10.0 15.0 20.0 25.0100-Meter B (Sonic) Wind Speed

100-

Met

er S

yste

m A

(Cup

) Win

d S

peed

Observations: 268

Correlation: 0.89


3.93.96.610.528560-MWS-B

1.5-0.510.39.836460-MWS-A


60-m Wind Speed CorrelationTower Impact

0.97-0.021.603.928560-MWS-B

0.941.680.79-0.536460-MWS-A


Figure 12: 60-Meter Wind Speed Regression When Tower Impacts System A (Cups)

y = 0.7889x + 1.6774

0.0

5.0

10.0

15.0

20.0

25.0

30.0

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.060-Meter B (Sonic) Wind Speed

60-M

eter

A (C

up) W

ind

Spe

ed

Observations: 364

Correlation: 0.94


y = 1.6029x - 0.024

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.060-MeterA (Cup) Wind Speed

60-M

eter

B (S

onic

) Win

d S

peed

Observations: 285

Correlation: 0.97


2.82.84.37.122510-MWS-B

1.2-0.48.17.739410-MWS-A


10-m Wind Speed CorrelationTower Impact

0.95-0.121.682.822510-MWS-B

0.971.190.80-0.439410-MWS-A


Figure 14: 10-Meter Wind Speed Regression When Tower Impacts System A (Cups)

y = 0.801x + 1.1866

0.0

5.0

10.0

15.0

20.0

25.0

0.0 5.0 10.0 15.0 20.0 25.0 30.010-Meter B (Sonic) Wind Speed

10-M

eter

A (C

up) W

ind

Spe

ed

Observations: 394

Correlation: 0.97


y = 1.6833x - 0.1175

0.0

5.0

10.0

15.0

20.0

25.0

30.0

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.010-Meter B (Sonic) Wind Speed

10-M

eter

A (C

up) W

ind

Spe

ed

Observations: 225

Correlation: 0.95

100-m Wind Direction AveragesTower Impact

55235240145100-MWD-B

44199203451100-MWD-A


100-m Wind Direction CorrelationTower Impact

0.9428.90.905145100-MWD-B

0.9712.90.964451100-MWD-A


Figure 16: 100-Meter Wind Direction Regression When Tower Impacts System A (Vane)

190

195

200

205

210

215

220

185 190 195 200 205 210 215


100-

Met

er A

(Van

e) W

ind

Dir

ectio

n

y = 0.9561x + 12.894

Observations: 451

Correlation: 0.97

Figure 17: 100-Meter Wind Direction Regression When Tower Impacts System B (Sonic)

230

232

234

236

238

240

242

244

246

248

250

228 230 232 234 236 238 240 242 244


100-

Met

er A

(Van

e) W

ind

Dir

ectio

n

y = 0.8958x + 28.931

Observations: 145

Correlation: 0.94

10-m Wind Direction AveragesTower Impact

772362438010-MWD-B

6619720340210-MWD-A


10-m Wind Direction CorrelationTower Impact

0.954.01.0178010-MWD-B

0.9911.20.98640210-MWD-A


Figure 18: 10-Meter Wind Direction Regression When Tower Impacts System A (Vane)

y = 0.9757x + 11.2

190

195

200

205

210

215

180 185 190 195 200 205 21010-Meter B (Sonic) Wind Direction

10-M

eter

A (V

ane)

Win

d D

irec

tion

Observations: 402

Correlation: 0.99

Figure 19: 10-Meter Wind Direction Regression When Tower Impacts System B (Sonic)

y = 1.0125x + 3.9992

232

234

236

238

240

242

244

246

248

250

252

228 230 232 234 236 238 240 242 24410-Meter B (Sonic) Wind Direction

10-M

eter

A (V

ane)

Win

d D

irec

tion

Observations: 80

Correlation: 0.95

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.

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

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.

north american technical center

Documents