Offshore Wind Energy_6

8/9/2019 Offshore Wind Energy_6

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Offshore Wind Energy

An Analysis of NDBC Wind Databy Philip H. Kahn

Copyright 2010 Philip H. Kahn 1


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Introduction

This study utilizes meteorological data provided by the National DataBuoy Center to characterize the wind energy resource potential at

several locations off the shores of the continental United States. 23

Discus buoys and one land station are compared over 11 years.

The wind resource is computed by extrapolating the wind speed from

5 meters to 80 meters elevation; applying a single power curve (that of

a G.E. 3.6sl wind turbine) to the extrapolated wind speed; and applying

a density correction to account for the effect of temperature and

pressure on the power density.

Plots of monthly and hourly variation of wind speed and capacityfactor are presented. Also, change histograms of extrapolated wind

speed and power generation are computed for individual and groups

of buoys to demonstrate the effect of geographic dispersion on the

hour-to-hour variability of power output.



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National Data

Buoy Center

www.ndbc.noaa.gov/

Contains meteorolog-

ical and oceano-

graphic data

Reported at least

hourly

Good temporal

coverage (except for

Great Lakes due to

winter ice)

Wind speed measured

at 5 meter elevation

Also measures wave

height (for surface

roughness)

http://www.ndbc.noaa.gov/http://www.ndbc.noaa.gov/


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Methodology

For stations with multiple observations per hour,wind speed data are block averaged.

For buoys, aerodynamic roughness length isdetermined using Charnocks relation and iteration;and used to extrapolate wind speed at hub height.

No correction for static stability is used in the currentstudy, though per Motta, et al (2003)* use oflogarithmic profiles without stability correction willtend to underestimate wind speeds at hub height.

For land based measurements fetch dependentroughness length are used to extrapolate wind speedto hub height.

*M. Motta, R.J. Barthelmie and P. Volund, 2003: Stability effects on predicted wind speed profiles and power output at the Vindeby offshore wind farm,Wind Eng Journal, http://ejournal.windeng.net/archive/00000001/01/e-paper_motta.pdf



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Methodology (cont.)

Hub height for all power computations in this reportis 80 meters above local elevation.

Density correction to power output is computed

based on temperature and pressure data on buoysand the land station, yielding a significant seasonalimpact on power production.

Power computations have no allowances for losses.

Hence they are overestimates of actual expectedpower production, and illustrate the estimatedimpact that variation in wind speed between buoyshas on power generation.



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GE 3.6sl Wind Turbine

Basis for all wind

energy computations

in this report

Same power curve

used for both on-

shore and off-shore

computations



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Data Availability

Due to the variability of winds on all time scales, whencomparing meteorological data from multiple instruments, it is

important to keep careful track of the temporal overlap of the

individual times series. In this study, we accomplish that by

computing the data availability percentage over each time frame

studied (monthly, quarterly and yearly); which is the number of

reported valid data values divided by the maximum possible data

values for the time frame (i.e. 720 hours in April, or 8760 hours

in 2003). The following table shows the data availability

percentage for each station and year studied. In many of thefollowing plots, a data threshold is defined for which those cases

where the data availability is less than the threshold are



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Data Availability (cont.)

eliminated. For example, plots that have a data threshold of .95include only those cases where data availability percentage

equals or exceeds 95%. Plots with a data threshold of 0 have no

cases eliminated and display the maximum amount of data

analyzed.



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Copyright 2010 Philip H. Kahn

Data Availability Chart

Percentages denote ratio of the number of actual data values to the number of

possible data values. All colored boxes were analyzed.

2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996

41001 65.3% 80.8% 60.7% 99.6% 86.1% 95.9% 99.8% 55.8% 95.1% 42.4% 66.1% 97.8%

41025 99.4% 99.2% 99.8% 79.7% 69.1% 68.3%42007 76.9% 88.4% 96.1% 76.5% 83.8% 94.1% 97.7% 99.6% 98.8% 94.1% 78.0%

42019 99.9% 99.0% 94.5% 99.0% 90.7% 99.9% 95.2% 99.8% 52.1% 84.8% 81.1%

42020 99.9% 78.7% 99.3% 99.0% 99.5% 99.7% 96.9% 98.2% 56.6% 98.0% 98.4%

42035 88.1% 99.2% 99.8% 78.3% 98.8% 99.4% 99.7% 91.5% 99.2% 98.9% 98.4%

42040 74.2% 99.0% 90.5% 94.1% 86.0% 99.7% 99.8% 99.5% 92.1% 75.3% 84.2%

44007 99.7% 85.0% 99.6% 69.4% 99.5% 96.7% 99.6% 98.9% 99.4% 99.1% 98.3%

44008 83.4% 76.6% 96.3% 56.4% 97.4% 89.6% 99.6% 38.6% 81.6% 98.4% 78.7%

44009 84.6% 99.5% 99.7% 99.9% 68.9% 98.5% 83.0% 99.1% 97.3% 99.0% 91.4% 88.1%

44011 96.8% 78.4% 96.8% 95.3% 58.1% 87.2% 95.3% 86.9% 90.9% 82.0% 96.9% 83.5%

44013 99.3% 99.0% 99.4% 99.3% 99.7% 99.6% 99.6% 98.3% 99.6% 94.3% 98.3%44014 99.2% 99.3% 60.1% 93.1% 99.9% 88.6% 99.7% 99.8% 97.3% 83.9% 70.9%

44017 82.2% 99.5% 84.2% 93.6% 92.0% 98.9% 33.2%

44018 99.4% 85.7% 98.4% 79.7% 62.1% 99.1% 41.8%

44025 94.8% 25.7% 91.0% 99.6% 99.6% 77.6% 99.8% 99.8% 97.6% 91.0% 93.2%

44027 86.4% 81.3% 99.8% 48.7% 63.2% 61.7%

45005 58.4% 38.0% 55.9% 58.9% 63.1% 62.3% 70.4% 60.5% 62.3% 58.9% 69.1%

45008 55.4% 59.5% 64.5% 65.9% 61.7% 54.9% 55.7% 62.5% 59.9% 52.1% 51.5%

45012 52.7% 55.8% 49.2% 56.0% 58.0% 47.6% 58.3%

46041 94.7% 22.1% 40.1% 99.1% 99.7% 99.4% 64.4% 77.2% 70.1% 47.5% 46.3%

46054 78.0% 81.1% 84.4% 35.2% 97.3% 98.2% 65.6% 97.6% 97.7% 96.6% 96.4%

46063 99.5% 76.0% 43.3% 51.2% 96.3% 99.7% 99.6% 74.7% 80.6% 98.7% 66.8%

JST___ 98.2% 98.8% 97.9% 97.2% 98.1% 98.3%

>75% Data Coverage


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Overall Average Wind Speed and Capacity Factor

The following slide contains a table showing the overall averagewind speed and capacity factor for the studied stations. The

fourth column shows simply the average of the annual average

wind speed for all hours with data. The fifth column shows the

average of 12 monthly averages of wind speed for all hours with

data. The sixth column is the same as the fifth but with a data

threshold of 95%, meaning that months with less than 95% data

availability are not used in the computations. The fourth and

fifth columns are more subject to sampling errors. Similar

definitions apply to the seventh, eighth and ninth columns, butthey are capacity factor instead of wind speed.



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Annual Mean Wind Speed and Capacity Factor For Period Studied (1998

through 2008, subject to Data Availability)

Station Latitude Longitude

Avg. Wind

Speed from

Yrly. Avgs. (m/s)

Avg. Wind

Speed from

Monthly Avgs.

Avg. Wind

Speed from

Monthly Avgs.

w/ 95% Avail.

Avg.

Capacity

Factor from

Yrly. Avgs.

Avg. Cap.

Fctr. from

Monthly

Avgs.

Avg. Cap. Fctr.

from Monthly

Avgs. w/ 95%

Avail.

41001 3442'13" N 7244'2" W 8.93 9.09 9.12 45.1% 46.3% 46.7%

41025 350'22" N 7524'7" W 9.13 9.33 9.34 46.6% 48.1% 48.2%

42007 305'25" N 8846'7" W 6.80 6.79 6.75 27.6% 27.5% 27.2%

42019 2754'47" N 9521'36" W 7.86 7.87 7.93 36.1% 36.2% 36.7%

42020 2657'59" N 9641'42" W 8.07 8.07 8.06 37.5% 37.5% 37.5%

42035 2913'54" N 9424'46" W 7.08 7.07 7.08 29.3% 29.3% 29.4%

42040 2912'19" N 8812'19" W 7.20 7.19 7.24 31.2% 31.2% 31.5%

44007 4331'53" N 708'39" W 6.92 6.95 6.93 30.7% 31.0% 30.8%

44008 4030'9" N 6914'48" W 8.18 8.29 8.31 39.1% 40.0% 40.1%

44009 3827'49" N 7442'7" W 8.11 8.12 8.07 38.9% 38.9% 38.5%

44011 416'41" N 6634'47" W 8.17 8.30 8.29 38.7% 39.7% 39.8%

44013 4221'14" N 7041'29" W 7.41 7.43 7.43 33.4% 33.6% 33.6%44014 3636'40" N 7450'11" W 7.72 7.83 7.86 35.6% 36.6% 36.8%

44017 4041'27" N 722'47" W 8.72 8.61 8.65 43.6% 42.4% 43.0%

44018 4115'31" N 6917'40" W 8.21 8.40 8.37 39.0% 40.8% 40.5%

44025 4015'1" N 739'59" W 8.58 8.41 8.39 42.4% 41.1% 41.0%

44027 4416'21" N 6718'51" W 8.15 8.36 8.37 38.8% 40.7% 40.8%

45005 4140'36" N 8223'54" W 6.80 7.12 6.85 28.2% 30.9% 28.7%

45008 4417'0" N 8224'59" W 7.22 7.75 7.37 32.0% 36.4% 33.1%

45012 4337'9" N 7724'18" W 6.95 7.53 7.09 29.1% 33.3% 30.0%

46041 4721'10" N 12443'50" W 6.91 6.99 7.10 29.6% 30.5% 31.3%

46054 3416'28" N 12027'34" W 9.82 9.92 9.91 53.7% 54.4% 54.1%

46063 3416'21" N 12041'55" W 8.84 8.92 9.03 48.2% 49.1% 49.9%JST 4019'6"N 7849'48"W 6.33 6.33 6.32 25.8% 25.8% 25.8%

14


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Capacity Factor Comparisons

Twelve of the NBDC buoys are located off the east coast(41001, 41025, 44007, 44008, 44009, 44011, 44013, 44014,44017, 44018, 44025 and 44027).

For the purposes of comparison, they have been grouped intothree groups:

Very Near to Shore (VNS). The VNS group is comprised of two buoys,44013 and 44007, and has an average annual capacity factor of 32.2% andan average distance to shore of 9 kilometers.

Near to Shore (NS). The NS group is comprised of seven buoys, 41025,44009, 44014, 44017, 44018, 44025, and 44027, and has an average

annual capacity factor of 41.3%, and an average distance to shore of 43kilometers.

Far from Shore (FS). The FS group is comprised of three buoys, 41001,44008 and 44011, and has an average annual capacity factor of 42.2%,and an average distance to shore of 217 kilometers.



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Capacity Factor Comparisons (cont.)

Conclusions:The Near Shore buoys have a wind resource that is apparently

attenuated.

There are numerous locations with estimated capacity factor in

the high 30%s and/or above 40%. The east coast buoys with the strongest wind resource are the

two off of North Carolina (41001 and 41025).

Nationally, the best wind resource measured by the Discus

buoys of the NDBC is off the California coast near Santa Barbara(buoys 46054 and 46063). This wind resource is particularly

strong in the summer when local demand peaks.



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Weibull Fits

The following two slides show probability density of wind speedfor station 44009 (off of Delaware) for the entire year of 2007.

The first of the two slides is of the measured wind speed at 5

meters elevation, and the second slide is of the wind speed

extrapolated to 80 meters elevation. The plots show that the

Weibull distribution fits quite well both to the measured and

extrapolated wind speeds.



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Histogram of Measured Wind Speed for C:\Buoy_Wind_Data_Analysis\44009\44009_2007\HMD_44009_2007_8718hours_twr

Shape = 1.964 Scale = 7.173

Wind Speed (meters/sec.)

Density

0 5 10 15

0.0

0

0.0

2

0.0

4

0.0

6

0.0

8

0.1

0

0.1

2

Weibull Fit to Measured Wind Speed 44009 2007



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Histogram of Transformed Wind Speed for C:\Buoy_Wind_Data_Analysis\44009\44009_2007\HMD_44009_2007_8718hours_twr

Shape = 1.876 Scale = 9.067

Wind Speed (meters/sec.)

Density

0 5 10 15 20 25

0.0

0

0.0

2

0.0

4

0.0

6

0.0

8

0.1

0

Weibull Fit to Hub Height Wind Speed 44009 2007



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Wind Rose Plots

The following two slides show wind rose plots of wind speedduring 2006 for four buoys. The first slide compares 44007 and

44027 (both near the coast of Maine); while the second slide

compares 44008 and 44018 (which are much further offshore).

The first slide shows significant terrain effects on the winds at

44007, which is the closest to shore of all of the buoys studied.

The wind speed at 44007 is lower than it is at the nearby buoy

44027, which is further offshore than 44007. The wind roses for

44008 and 40018 are much more similar due to their location far

from shore. This indicates that the low wind speed and capacityfactor for 44007 is more likely due to its proximity to shore

rather than due to instrument error.



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Monthly Wind Speed for One Year

The following plot shows the monthly average wind speedextrapolated to 80 meter hub height determined from wind

speed measured by buoy 44009 located off the coast of

Delaware for the year 2007. The plot shows the characteristic

summer lull in wind speeds with the maximum wind energy in

the last two and first two months of the year, that is typical of

buoys located of the east coast of the U.S.



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44009 2007 Hub Height Wind Speed


0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11 12

WindSp

eed(Met/Sec)

Month

Full Year


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Hourly Wind Speed for Full Year and 4 Seasons

The following five plots show hourly average wind speedextrapolated to 80 meter hub height determined from wind

speed measured by buoy 44009 for the year 2007. The first plot

shows the hourly variation of wind speed for the entire year;

while the subsequent four plots show the hourly variation for

Winter (December, January and February), Spring (March, April

and May), Summer (June, July and August) and Fall (September,

October and November). The time of day is UTZ (Greenwich

Standard Time).



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0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 1 1 1 2 1 3 14 1 5 16 1 7 1 8 19 2 0 2 1 2 2 23 2 4

WindSpeed(Met/Sec)

Hour

Full Year


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0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 1 1 1 2 1 3 14 1 5 16 1 7 1 8 19 2 0 2 1 2 2 23 2 4

WindSpeed(Met/Sec)

Hour

Winter


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0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 1 1 1 2 1 3 14 1 5 16 1 7 1 8 19 2 0 2 1 2 2 23 2 4

WindSpeed(Met/Sec)

Hour

Spring


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0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 1 1 1 2 1 3 14 1 5 16 1 7 1 8 19 2 0 2 1 2 2 23 2 4

WindSpeed(Met/Sec)

Hour

Summer


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0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 1 1 1 2 1 3 14 1 5 16 1 7 1 8 19 2 0 2 1 2 2 23 2 4

WindSpeed(Met/Sec)

Hour

Fall


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All Stations Monthly

The next slide shows for each station the wind speed averagedover each month of all the years studied. The following slide

shows for each station the wind speed averaged over each

month plotted individually, indicating the scatter of the

individual months. The succeeding two plots are similar but

show the capacity factor instead of the wind speed. These plots

give a good idea of the annual and inter-annual variability of the

wind speed and capacity factor as measured by the 23 NDBC

data buoys.



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Monthly Average Hub Height Wind Speed For All Years


Overall Average Per Month Data Threshold = 0 %

Month

WindSpeed

(met/sec)

5

10

15

2 4 6 8 10 12

41001 41025

2 4 6 8 10 12

42007 42019

2 4 6 8 10 12

5

10

1542020

5

10

15

42035 42040 44007 44008

5

10

15

44009

5

10

1544011 44013 44014 44017

5

10

1544018

5

10

1544025 44027 45005 45008

5

10

1545012

5

10

1546041

2 4 6 8 10 12

46054 46063

2 4 6 8 10 12

5

10

15JST__

32


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Monthly Average Hub Height Wind Speed For Individual Years


Monthly Averages Data Threshold = 0 %

Month

WindSpeed

(met/sec)

5

10

15

2 4 6 8 10 12

41001 41025

2 4 6 8 10 12

42007 42019

2 4 6 8 10 12

5

10

1542020

5

10

15

42035 42040 44007 44008

5

10

15

44009

5

10

1544011 44013 44014 44017

5

10

1544018

5

10

1544025 44027 45005 45008

5

10

1545012

5

10

1546041

2 4 6 8 10 12

46054 46063

2 4 6 8 10 12

5

10

15JST__

33


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Monthly Average Capacity Factor For All Years


Overall Average Per Month Data Threshold = 0 %

Month

CapacityF

actor(%)

20

40

60

2 4 6 8 10 12

41001 41025

2 4 6 8 10 12

42007 42019

2 4 6 8 10 12

20

40

60

42020

20

40

60

42035 42040 44007 44008

20

40

60

44009

20

40

60

44011 44013 44014 44017

20

40

60

44018

20

40

60

44025 44027 45005 45008

20

40

60

45012

20

40

60

46041

2 4 6 8 10 12

46054 46063

2 4 6 8 10 12

20

40

60

JST__

34


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Monthly Average Capacity Factor For Individual Years


Monthly Averages Data Threshold = 0 %

Month

CapacityF

actor(%)

20

40

60

2 4 6 8 10 12

41001 41025

2 4 6 8 10 12

42007 42019

2 4 6 8 10 12

20

40

60

42020

20

40

60

42035 42040 44007 44008

20

40

60

44009

20

40

60

44011 44013 44014 44017

20

40

60

44018

20

40

60

44025 44027 45005 45008

20

40

60

45012

20

40

60

46041

2 4 6 8 10 12

46054 46063

2 4 6 8 10 12

20

40

60

JST__

35


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All Stations Hourly (Full Year, Winter & Summer)

The next three slides show hourly variation of wind speed foreach station averaged over the full year for the first plot; over

the winter for the second plot; and over the summer for the

third plot. Each circle plotted represents the average wind speed

for a particular hour in each day of the averaging period. In the

case of the full year plot each circle represents the average of

hourly 365 values; while for the seasonal plots each circle

represents the average of up to 91 hourly values. The following

3 slides are the same but with capacity factor plotted rather than

wind speed. Cases that show a line of circles away from themain body of data points result from averaging periods that are

missing a large percentage of data values.



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Full Year Hourly Average Hub Height Wind Speed For Individual Years


Full Year Data Threshold = 0

Hour

WindSpeed

(met/sec)

5

10

15

0 5 10 15 20 25

41001 41025

0 5 10 15 20 25

42007 42019

0 5 10 15 20 25

5

10

1542020

5

10

15

42035 42040 44007 44008

5

10

15

44009

5

10

1544011 44013 44014 44017

5

10

1544018

5

10

1544025 44027 45005 45008

5

10

1545012

5

10

1546041

0 5 10 15 20 25

46054 46063

0 5 10 15 20 25

5

10

15JST__

37


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Winter Hourly Average Hub Height Wind Speed For Individual Years


Winter Data Threshold = 0

Hour

WindSpeed

(met/sec)

5

10

15

0 5 10 15 20 25

41001 41025

0 5 10 15 20 25

42007 42019

0 5 10 15 20 25

5

10

1542020

5

10

15

42035 42040 44007 44008

5

10

15

44009

5

10

1544011 44013 44014 44017

5

10

1544018

5

10

1544025 44027 45005 45008

5

10

1545012

5

10

1546041

0 5 10 15 20 25

46054 46063

0 5 10 15 20 25

5

10

15JST__

38


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Summer Hourly Average Hub Height Wind Speed For Individual Years


Summer Data Threshold = 0

Hour

WindSpeed

(met/sec)

5

10

15

0 5 10 15 20 25

41001 41025

0 5 10 15 20 25

42007 42019

0 5 10 15 20 25

5

10

1542020

5

10

15

42035 42040 44007 44008

5

10

15

44009

5

10

1544011 44013 44014 44017

5

10

1544018

5

10

1544025 44027 45005 45008

5

10

1545012

5

10

1546041

0 5 10 15 20 25

46054 46063

0 5 10 15 20 25

5

10

15JST__

39


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Full Year Hourly Average Capacity Factor For Individual Years


Full Year Data Threshold = 0

Hour

CapacityF

actor(%)

20

40

60

0 5 10 15 20 25

41001 41025

0 5 10 15 20 25

42007 42019

0 5 10 15 20 25

20

40

60

42020

20

40

60

42035 42040 44007 44008

20

40

60

44009

20

40

60

44011 44013 44014 44017

20

40

60

44018

20

40

60

44025 44027 45005 45008

20

40

60

45012

20

40

60

46041

0 5 10 15 20 25

46054 46063

0 5 10 15 20 25

20

40

60

JST__

40


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Winter Hourly Average Capacity Factor For Individual Years


Winter Data Threshold = 0

Hour

CapacityF

actor(%)

20

40

60

0 5 10 15 20 25

41001 41025

0 5 10 15 20 25

42007 42019

0 5 10 15 20 25

20

40

60

42020

20

40

60

42035 42040 44007 44008

20

40

60

44009

20

40

60

44011 44013 44014 44017

20

40

60

44018

20

40

60

44025 44027 45005 45008

20

40

60

45012

20

40

60

46041

0 5 10 15 20 25

46054 46063

0 5 10 15 20 25

20

40

60

JST__

41


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Summer Hourly Average Capacity Factor For Individual Years


Summer Data Threshold = 0

Hour

CapacityF

actor(%)

20

40

60

0 5 10 15 20 25

41001 41025

0 5 10 15 20 25

42007 42019

0 5 10 15 20 25

20

40

60

42020

20

40

60

42035 42040 44007 44008

20

40

60

44009

20

40

60

44011 44013 44014 44017

20

40

60

44018

20

40

60

44025 44027 45005 45008

20

40

60

45012

20

40

60

46041

0 5 10 15 20 25

46054 46063

0 5 10 15 20 25

20

40

60

JST__

42


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Single Year Station Comparisons

The following two slides show the power estimated poweroutput from a GE 3.6sl turbine with 80 meter hub height for

buoy 44009 and the Johnstown, PA ASOS station located at the

local airport. The first of the two plots shows the monthly

variation of power output for 2007 and the second plot shows

the hourly variation of power output for the full year of 2007.

The next two slides show monthly variation of power output for

2007 for: buoy 44009 and 41025 (located off Cape Hatteras,

NC); and buoy 44009 and 44017 (located off the south shore of

Long Island NY).



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2007 Monthly Power Output (44009 light gray, JST dark gray)


0

500

1000

1500

2000

2500

3000

1 2 3 4 5 6 7 8 9 10 11 12

Pow

er(kW)

Month

44009 vs JST


45/80

2007 Hourly Power Output (44009 light gray, JST dark gray)


0

500

1000

1500

2000

2500

3000

1 2 3 4 5 6 7 8 9 10 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

Pow

er(kW)

Hour

Full Year


46/80


2007 Monthly Power Output (44009 light gray, 41025 dark gray)

46

0

500

1000

1500

2000

2500

3000

1 2 3 4 5 6 7 8 9 10 11 12

Pow

er(kW)

Month

41025 vs 44009


47/80


2007 Monthly Power Output (44009 light gray, 44017 dark gray)

47

0

500

1000

1500

2000

2500

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1 2 3 4 5 6 7 8 9 10 11 12

Pow

er(kW)

Month

44009 vs 44017


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Multiple Year Station Comparisons

The following four slides each show six box-and-whisker plots ofdifferent station pairs, where the percentage difference in wind

speed is plotted by month of the year. For each month, the

mean is depicted with a heavy horizontal line through the box,

which contains the second and third quartiles of the monthly

difference values. The whiskers extend to the extreme of the

monthly values of wind speed difference percentage. The next

four slides are similar but with difference of capacity factor

plotted instead of percentage difference in wind speed. These

slides demonstrate the variation of wind resource among manyof the buoys.



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Monthly Wind Speed Differences For Selected Pairs of Stations

49


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50


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51


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52


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Monthly Capacity Factor Differences For Selected Pairs of Stations

53


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55


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56


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Multiple Year Station Comparisons: Discussion

The wind resource at JST__ is generally less than that of virtually all of thebuoys. This site is at a relatively high elevation (over 2000 feet above sealevel), however it is located at an airport and does not benefit fromtopographical speed-up as do typically developed land-based wind energyproduction sites in the eastern part of the U.S. (See upper left plot of Slide49.)

The summer winds at 44009 are equal or greater than those at 44017 and44025, though the winter winds at the latter two stations off the southerncoast of Long Island are stronger than those off of Delaware, indicatingthat those sites are comparable to the Delaware one. (See upper middleand upper right plot of Slide 49.)

The winds at 44013 (just east of Boston Harbor) are unexpectedly light.

This is presumably due to sheltering of the winds by the city and by CapeCod. (See the lower left plot of Slide 49.)

The wind resource at stations 44014 and 44018 are roughly comparable to



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Multiple Year Station Comparisons: Discussion (cont.)

that of 44009. (See lower middle and lower right plots of Slide 49.)

The wind resource at 44007 (off the coast of Southern Maine) appears tobe significantly weaker than that of 44009. (See upper left plot of Slide50.) This is consistent with the discussion of the wind rose computed for44007 (Slides 20, 21 and 22).

Station 41025 (off of Cape Hatteras, NC) has significantly better wind

resource than 44009 and the other buoys further north. (See the upperright plot of Slide 50.) This is corroborated with the summary annualaverages shown in Slide 14.

Station 42020 off the southern coast of Texas has better winds in themonths of May, June and July relative to 44009, while in the other months44009 fares better than 42020. (See lower left plot of Slide 50.) Overall,the two stations are quite close in annual wind resource (per Slide 14).

Station 45005 (located in Lake Erie) only reports in the warmer months ofthe year due to lake ice. During the months that 45005 reports data, itswind resource lags that of 44009. (See the lower middle plot of Slide 50.)



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Multiple Year Station Comparisons: Discussion (cont.)

Station 46054 (off of Santa Barbara, CA) has the strongest wind resourceof all of the buoys studied. It has especially strong winds in the summermonths due to pronounced sea breeze circulation driven by the largeocean to land temperature difference occurring in southern California.(See the lower right plot of Slide 50, Slide 33 and Slide 14).

Strong summer sea breeze is evident in the comparison between stations

44008 and 44018. 44008 is located further offshore than 44018 and duesouth of it. (See the upper left plot of Slide 52.) This is corroborated bythe comparison between 44011 and 44018, which both are relatively faroffshore. (See the upper right plot of Slide 52.)

The southern Texas coast (station 42020) appears to have significantlybetter wind resource than the northeastern Texas coast (station 42035).

(See the lower right plot of Slide 52.)



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Effects of Geographic Dispersion

To see the effect geographic dispersion on power output, hour to hour

changes in power output were compared between individual and groupsof buoys.

Histograms of changes in wind speed and power were computed for 1, 2,3, 4, 8 and 12 hour differences for individual buoys and for groups of 3buoys and 7 buoys.

Slides 62 through 67 show the wind speed change histograms for 1, 2, 3, 4,8 and 12 hour changes for buoy 44018 for 2008, while Slides 68 through73 show the same for power.

Power change histograms were compared between a single buoy and theaverage of three buoys (relatively close together), and between a singlebuoy and the average of seven buoys (more widely dispersed).

In Slides 74 and 75, the power change histograms for a single station(44008) are overlaid by the histograms for the average of three relativelyclose by buoys (44008, 44018 and 44025) located near Long Island andCap Cod.



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Effects of Geographic Dispersion (cont.)

In Slides 76 and 77, the power change histograms for a single buoy(44018) were overlaid by the power change histograms for the average ofseven buoys that were dispersed from North Carolina to Maine (41025,44007, 44008, 44013, 44014, 44018 & 44025).

In Slides 78 and 79, the power change histograms for the close-by group ofthree buoys (44008, 44018 & 44025) is overlaid by the power change

histograms for the average of the seven widely dispersed buoys (41025,44007, 44008, 44013, 44014, 44018 & 44025).

Slides 76 and 77 clearly illustrate the smoothing effect on the hour-to-hour change of the power output from dispersed wind farms compared toa single wind farm.

Note that the central spikes in the power change histograms result fromthe cut-in and cut-off speeds of the wind turbine power curve used for thecomputations



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1 Hour Wind Speed Change Histogram for Buoy 44018 in 2008


HMD_44018_2008_8731hours Wind Speed

1 Hour Change (met/sec)

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1 Hour Power Change Histogram for Buoy 44018 in 2008


HMD_44018_2008_8731hours Power

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2 Hour Change (kW)

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3 Hour Change (kW)

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4 Hour Change (kW)

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8 Hour Change (kW)

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12 Hour Change (kW)

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2008 Power Change Histograms for 1, 2, 3, 4, 8 & 12 hour changes at Buoy 44008 (in red)

overlaid by Average of 44008, 44018 & 44025


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HMD_44008_2008 AVG_44008_44018_44025_2008 Power

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HMD_44008_2008 AVG_44008_44018_44025_2008 Power

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HMD_44008_2008 AVG_44008_44018_44025_2008 Power

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HMD_44008_2008 AVG_44008_44018_44025_2008 Power

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overlaid by Average of 44008, 44018 & 44025 (expanded scale)


Density

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HMD_44008_2008 AVG_44008_44018_44025_2008 Power

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HMD_44008_2008 AVG_44008_44018_44025_2008 Power

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HMD_44008_2008 AVG_44008_44018_44025_2008 Power

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HMD_44008_2008 AVG_44008_44018_44025_2008 Power

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overlaid by Average of 41025, 44007, 44008, 44013, 44014, 44018 & 44025


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HMD_44018_2008_8731hours AVG_41025_44007_44008_44013_44014_44018_44025_2008 Power

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overlaid by Average of 41025, 44007, 44008, 44013, 44014, 44018 & 44025 (expanded

scale)


Density

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1 Hour Change (kW)

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2008 Power Change Histograms for 1, 2, 3, 4, 8 & 12 hour changes of the Average of 44008,

44018 & 44025 (in red) overlaid by Average of 41025, 44007, 44008, 44013, 44014, 44018

& 44025


Density

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AVG_44008_44018_44025_2008 AVG_41025_44007_44008_44013_44014_44018_44025_2008 Power

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AVG_44008_44018_44025_2008 AVG_41025_44007_44008_44013_44014_44018_44025_2008 Power

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AVG_44008_44018_44025_2008 AVG_41025_44007_44008_44013_44014_44018_44025_2008 Power

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2008 Power Change Histograms for 1, 2, 3, 4, 8 & 12 hour changes of the Average of 44008,

44018 & 44025 (in red) overlaid by Average of 41025, 44007, 44008, 44013, 44014, 44018

& 44025 (expanded scale)


Density

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AVG_44008_44018_44025_2008 AVG_41025_44007_44008_44013_44014_44018_44025_2008 Power

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AVG_44008_44018_44025_2008 AVG_41025_44007_44008_44013_44014_44018_44025_2008 Power

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AVG_44008_44018_44025_2008 AVG_41025_44007_44008_44013_44014_44018_44025_2008 Power

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AVG_44008_44018_44025_2008 AVG_41025_44007_44008_44013_44014_44018_44025_2008 Power

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Density

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0e+00

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AVG_44008_44018_44025_2008 AVG_41025_44007_44008_44013_44014_44018_44025_2008 Power

12 Hour Change (kW)

Density

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0e+00

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80/80

Final Word

The National Data Buoy Center of the National Oceanographicand Atmospheric Administration offers a dataset that yieldsuseful information about the wind resource around our nationsshores. Though the platform was not expressly designed toinventory wind resources, the fact that so many of the same typeof buoy package have been deployed with similar anemometersat the same measuring height means that useful comparisonsbetween sites can be performed. Slides 31, 35, 36 and 37demonstrate that the dataset hangs together quite well.Considering that the buoys endure the harsh environment of the

ocean, it is remarkable that the instruments maintain calibrationover time as well as they apparently do.

Offshore Wind Energy_6

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Transcript of Offshore Wind Energy_6