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2. W
IND
R
ESOURCE
A
SSESSMENT
S
ECTION
S
UMMARY
Rhode Island wind speeds reflect the fact that the state is relatively flat, and unable to take advantage of the increases in wind speed associated with high
elevations. Much of the inland portion of Rhode Island is forested, contributing to a high
degree of surface roughness that slows wind speeds in that portion of the state. The highest wind speeds in Rhode Island tend to be close to the coast, due to this
area’s proximity to the flat expanse of the ocean. The U.S. Department of Energy estimates that wind energy production currently
requires wind speeds greater than 7 msec 16mph at 80m 262 ft. According to previous modeling by AWS TrueWind, Rhode Island has an average wind speed
of 5.5-6.0 meterssec 12-13mph at 80m 262ft. Coastal regions of the state have higher wind speeds, measuring an average of
6.5-7.5 meterssec 15-17mph at 80m 262ft. Block Island has the highest wind speeds in the state, at 8-9 meterssec 18-20mph at 80m 262ft.
There is more seasonal variation in wind speeds closer to the shore, but greater daily variation in wind speeds as one moves further inland.
Available wind resources can be further refined by considering the technical constraints on energy production, such as the efficiency of the turbine, and the
practical constraints, which are reviewed in Section 3. Availability of commercially significant wind resources in Rhode Island is a prerequisite
for considering wind energy development within the state. RESP research confirmed the findings of prior studies that Rhode Island possesses some areas with commercially viable wind resources
at current technological levels. As technology improves, the harvestable wind resources in the state may increase.
Land-based wind resources were first examined across the state by the RI Winds study ATM, 2007. That study evaluated wind resources across the entire state including offshore
waters to identify the most viable areas for wind energy development. Unlike the RESP, the RI Winds evaluated wind resources exclusively from the perspective of utility-scale turbines
1.5MW or larger. The results of that study demonstrated that the greatest potential for utility- scale development exists offshore. According to the study, land-based wind energy potential at
scales greater than 1.5MW is limited because, at 80 m, only 2.6 of Rhode Islands land mass has mean annual wind speeds over 7 ms. The RESP expanded upon the RIWINDS study by
examining in greater detail the wind resources of the state and considering the potential for smaller wind energy projects ranging between 100kW-1.5MW.
2.1 Average Wind Speeds across Rhode Island Wind resources can be compared horizontally across a landscape or vertically across a
range of elevations. Understanding how wind speeds vary across a landscape is important when
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selecting a potential project site, while understanding vertical variation in wind resources is useful for understanding wind speeds at the height at which it would be harvested by a particular
turbine. Research conducted for the RESP examined wind resources in both dimensions, comparing wind resources across Rhode Island and assessing vertical variation in wind resources
at selected sites see Grilli et al., 2012 and Merrill and Knorr, 2012 in Volume II of this report. Wind speed and direction is determined by macro-scale atmospheric patterns influenced
by temperature, pressure, and humidity. On smaller scales, it is shaped by topography and land cover, which influence the behavior of the wind near the land surface. For example, when wind
flows over a topographic feature such as a mountain ridge, wind speeds are accelerated. In addition, wind speeds are greater at higher elevations. In contrast, areas with rough land cover,
such as forests, tend to slow the wind. Rhode Island’s topography and land cover offer a good starting point for predicting wind
speeds across the state. The highest elevations are present in the northwestern part of the state see Ch. 1 Figure 1, however these are also areas that are densely forested see Ch. 1 Figure 2
and thus have higher surface roughness see Ch. 1 Figure 3, which lowers wind speed in these areas. Moreover, despite the presence of hilly areas in the northwestern part of the state, Rhode
Island is relatively flat, with the highest point in the state only reaching just over 812 feet 247m in the Town of Foster. As a result, Rhode Island’s wind resources are lessened by the fact that
the state lacks areas where high elevation and low surface roughness overlap.
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Ch. 1 Figure 1. Topography in Rhode Island.
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Ch. 1 Figure 2. Generalized Land Cover Patterns Across Rhode Island.
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Ch. 1 Figure 3. Surface Roughness Across Rhode Island Based on Land Cover.
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Ch. 1 Figure 4. Annual average wind speeds at 80 m 262 ft in elevation. Figure based on modeled wind produced by AWS Truepower, formerly named AWS TrueWind.
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Wind resource maps are based on models that generate estimates of wind speed across a map grid at a given elevation taking into account topography, land cover and surface roughness.
The RESP assessed wind resources by drawing on three-dimensional modeled wind data AWS Truewind, 2007 and on observations of wind profile data at selected sites Grilli et al. 2012.
Wind resource models are not a substitute for observational data; their utility lies in that they can be used to extrapolate existing data across much larger areas, such as an entire state, as well as
vertically and over time. 2.2 Modeled wind speeds across Rhode Island
Wind speeds at various heights have been modeled by AWS TrueWind for the entire New England region, using a mesoscale meteorological model and wind flow simulation model
with a resolution of 200m x 200m 656ft x 656ft. The AWS Truewind MesoMap was validated with weather observations from surface stations, instrumented balloons, satellites, aircraft, and
other instruments. These models incorporate weather data, sea-surface temperatures, land cover, topography, and other geophysical data also drive the simulations. Ch. 1 Figure 4 is the AWS
TrueWind map of annual average wind speeds at a height of 80 meters 262ft for the entire United States.
The AWS Truewind modeled data suggests that overall, the fastest winds within the state are located along the southern coastline see Ch. 1 Figure 5. For example, at 80m 262ft, the
majority of the state has average annual wind speeds ranging from 5.5-6.0msec 12-13mph, while coastal regions having averages of 6.5-7.5msec 15-17mph, and Block Island has the
highest average annual wind speeds, equaling 8-9msec 18-20mph; see Ch. 1 Figure 5. Plentiful wind resources along the coast can be attributed to this area’s proximity to the open sea, while
scarcer wind resources in the inland part of the state can be attributed to greater surface
roughness. Ch. 1 Figure 5, Ch. 1 Figure 6, and Ch. 1 Figure 7 suggest that in the inland part of the state, surface roughness appears to override the positive effects of high topographical
elevation on wind speeds. Ch. 1 Figure 5 displays the average annual wind speeds at 80m 262 feet; this is the
approximate hub height of a 1.5MW turbine, Ch. 1 Figure 6 displays the average annual wind speeds at 50m 164ft; this is the approximate hub height of a 660-kW turbine, and represents
the average annual wind speeds at 30 m 98 ft; this is the approximate hub height of a 100kW wind turbine. Additional wind resource maps and analysis can be found in the RESP technical
reports presented in Volume II and online at RI Energy.org
.
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Ch. 1 Figure 5. Average Annual Wind Speeds at 80m 262ft, as Predicted by AWS Truewind MesoMap.
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Ch. 1 Figure 6. Average Annual Wind Speeds at 50m 164ft, as Predicted by AWS Truewind MesoMap.
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Ch. 1 Figure 7. Average Annual Wind Speeds at 30m 98ft, as predicted by AWS Truewind MesoMap.
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2.3 Data on Wind Speeds across Rhode Island The types of tools that can be used to gather observational wind speed data include
anemometers and SODARs. Anemometers serve to gather information on wind speeds over periods of days, weeks, or years. Long-term data sets like those collected by the National
Oceanic and Atmospheric Administration NOAA often rely on pole-mounted anemometers to collect data at a single elevation, usually near the surface. In contrast, many of the shorter-term
data sets available are gathered using multiple anemometers, often mounted on a single meteorological tower, to measure wind speeds at various heights. Because wind speeds increase
with elevation, the availability of wind speed measurements at various elevations is useful to accurately assess the characteristics of the wind resource at a proposed wind turbine site.
Meteorological towers can also be outfitted with temperature and humidity gauges at the same elevations as anemometers so that wind speed measurements can be correlated with other
parameters. A SODAR Sonic Detection And Ranging Instrument, on the other hand, uses acoustics
to measure wind speeds up to 200 meters 656 feet. SODARs can collect wind data at much higher elevations than would be feasible using meteorological towers. They are also easier to
deploy than meteorological towers because they are mobile and do not require permanent installation. A SODAR’s reliance on acoustics rather than a physically mounted instrument mean
that it can be set up to gather wind speed data from various elevations in the same location at the
same time, making this tool especially valuable for comparing variations in wind speeds with height. One downside of using SODARs is temperature data is not collected at elevation.
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Ch. 1 Figure 8. Meteorological Tower Locations in Rhode Island.
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Wind data has been collected around Rhode Island see Ch. 1 Figure 8. Some data sets are long-term, spanning decades, such as the data collected at the TF Green Airport. Others are
much shorter term, spanning two years or less. These various sites and time periods can provide a glimpse into the wind resources in Rhode Island and ground-truth the modeled wind speed
estimates provided by the AWS Truewind MesoMap. However, because of the limited amount of data collected this picture is not complete.
Ch. 1 Table 1. Existing Wind Data Used for RESP Resource Assessment.
Location Source
Time series Type of data
Fields Point tower
Narragansett Bay Commission
March 2007 – November 2007
January 2008 – March 2009
30m 98ft, Paired42m + 49m138ft + 161ft
Camp Cronin, Narragansett
tower RI DEM
November 2009 – February 2011 30m, 40m, 50m 98ft,
131ft, 164ft Newport
tower Naval Station
August 2009 – August 2011
Paired 47.5m + 58m 156ft + 190ft;
Paired 24m + 40m 79ft + 131ft
Taylor Point, Jamestown
SODAR Jamestown
May 2011 – December 2011
40m, 60m, 200m 131ft, 197ft, 656ft
URI Bay Campus tower
RESPURI 2012 -
Paired: 40m + 50m + 60m 131ft +
164ft+197ft
URI Bay Campus SODAR
RESPURI 2012 -
40m, 60m, 200m 131ft, 197ft, 656ft
Merrill and Knorr 2012 evaluated four existing data sets for the purposes of the RESP. In addition, a new meteorological tower was installed at the University of Rhode Island’s Bay
Campus in Narragansett and deployed two mobile SODAR units at various sites around the state. Ch. 1 Table 1 shows a list of the various data sets compiled by Merrill and Knorr 2012.
1
The researchers then calculated average wind speed at each height measured, and fit a log profile and
power law distribution to each data set to estimate the wind profile with elevation. Ch. 1 Figure 9 shows average wind speeds at measured elevations, power law fit, and log law fit for each
location.
1
The final two listings represent equipment that has been installed but has not produced data yet.
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Merrill and Knorr 2012 compared data from the four sites providing a preliminary indication of the variation in wind speeds with geography, height, season, and time of day.
Results suggested stronger wind speeds at Camp Cronin, weaker wind speeds at Fields Point, and intermediate wind speeds at the Newport Naval Station and Taylor Point. This pattern can be
explained by the varying proximity of the four sites to the coast, with sites closer to the ocean displaying higher wind speeds than those further inland.
A comparison of wind speeds during different months of the year indicates a general pattern of weaker winds during summer, strongest winds during spring and fall, and intermediate
winds in winter. The Fields Point site presented less pronounced seasonal variation in wind speeds tha
n other three sites. This is most likely due to that site’s overall weaker wind environment. Merrill and Knorr 2012 also explored variation in wind shear i.e., the increase of
horizontal wind speeds with elevation across the four sites. They found that at Fields Point, the wind shear coefficient changes little throughout the year, while the Camp Cronin and Taylor
point sites display a greater change. In laymen’s terms, the rate of increase in wind speeds with elevation becomes more pronounced during certain times of year; this variation is stronger at
Camp Cronin and Taylor Point than at Fields Point. A comparison of wind speeds at different points during the day suggests that the onshore
sea breeze flow of wind from the southwest that takes place in the afternoon is greater at Fields Point than for the other three sites. This is most likely because the variation caused by the sea
Ch. 1 Figure 9. Vertical Profiles of Wind Speed at Four Selected Sites in Rhode Island. [The green diamond indicates the average speed at each level, and the curves indicate the variation following the log profile and
power law distribution.]
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breeze land breeze cycle is highest as one moves further inland. The results of this analysis can be found in greater detail in Merrill and Knorr 2012.
Analysis of observational data at specific data collection sites can also serve to verify the accuracy of the modeled data that is used to map wind speeds statewide. To assess the accuracy
of the modeled data at predicting wind speeds, Grilli et al. 2012 compared the AWS TrueWind modeled data reflected in the maps above to existing wind speed measurements collected at eight
points across Rhode Island. The results of this comparison show that at any specific location tested, the difference between the AWS TrueWind estimation and actual mean wind speeds
ranges from -4.5 to +2.5 in a confidence interval of 95 . Therefore, if we measure the mean wind speed at any point in Rhode Island there is a 95 of chance of finding the mean value
being in this small interval around the predicted AWS value. This relatively small difference demonstrates that AWS Truewind is a good estimator of the mean wind speed Grilli et al. 2012.
Using accurate modeled wind data is important due to the fact that even small differences in wind speed result in much larger differences in power production because, as a general rule, the
power output of a wind turbine increases by the cube of wind speed Wizelius 2007. 2.4 Assessing Areas for Wind Energy Production
According to the U.S. Department of Energy, wind speeds classified as “fair” or adequate wind speeds for wind energy production are considered to be those greater than 4.5, 5.5, and
7msec 10, 12, and 16mph at 30, 50, and 80m 98, 164, and 262ft hub heights, respectively see Ch. 1 Figure 10 for a diagram of turbine measurements. Winds meeting these criteria are
classified as Class 3 or higher by the U.S. Department of Energy see
http:www1.eere.energy.govwindwind_potential.html. A typical 1.5 MW wind turbine has a hub height of 80 meters 262 feet. RESP researchers developed a series of maps that explore the
distribution of commercially harvestable wind speeds across the state. Ch. 1 Figure 11 shows locations in Rhode Island where annual mean wind speeds are
over 7msec 16mph at 80m 262ft hub height, meeting the Department of Energy’s standard for adequate wind resources for development. As the figure shows, only a small portion of the
state e.g., coastal regions and Block Island exhibits wind speeds that meet this criteria. However, this observation does not necessarily mean that wind energy cannot be developed in
other parts of the state, especially as improvements in technology make development more viable in areas with slower average annual wind speeds. Ch. 1 Figure 12 and Ch. 1 Figure 13 show
wind speeds in Rhode Island at the 80m 262ft hub height above 6.5 and 6msec 15 and 13mph, respectively.
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Ch. 1 Figure 10. Wind Turbine Terminology.
Total Turbine Height H
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Ch. 1 Figure 11. Average Annual Wind Speeds at 80m 262ft Greater than 7msec 16mph.
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Ch. 1 Figure 12. Average Annual Wind Speeds at 80m 262ft Greater than 6.5msec 15mph.
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Ch. 1 Figure 13. Average Annual Wind Speeds at 80m 262ft Greater than 6msec 13mph.
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2.5 Wind Power Production Potential wind production can be projected at three levels: the theoretical resource, the
technical resource, and the practical resource. The available energy production available at each of these levels is progressively smaller than at the previous one, because each level takes into
account a greater number of limiting factors than the last. The theoretical resource is the amount of power generated by the wind, or the amount of energy theoretically available at a site if all
power were harvestable. The technical wind power resource, in contrast, is a subset of theoretical resource equal to the amount of power that can actually be produced at a location given the
characteristics of the extraction device turbine. Lastly, the practical wind power resource accounts for restrictions on the availability of extractable wind power that result from
environmental and social precautions. Theoretical Wind Resource
The theoretical resource is defined as the maximum amount of energy theoretically possible given the topography, land cover, and atmospheric patterns present at a particular
location. In other words, it is the amount of power measured in power density, or wattsm
2 2
that would be available at a site if turbines were present to harvest it and if turbines were 100 efficient. The theoretical resource is the standard value used in the wind industry and the one
mapped by AWS Truewind. Ch. 1 Figure 14 shows the theoretical resource available at a 30m 98ft hub height across the state calculated by Grilli et al. 2012, based on AWS TrueWind
modeled wind speed data in Wattsmeter
2
. Technical Wind Resource
Like the theoretical resource, the technical resource is measured in power density wattsm
2
. It is calculated by accounting for the following factors:
Betz’ Law, which holds that no device can extract more than 59.3 percent of the kinet
ic energy in wind this is why wind entering a turbine’s rotor flows through the turbine instead of stopping when it hits the rotor;
Cut-in speed the minimum wind speed at which a turbine begins to operate; typically between 3-4msec, or about 7-9mph;
Rated power the wind speed at which the turbine ceases to generate additional energy per msec of wind speed; all turbines are engineered for a specific rated
power, typically somewhere between 12-17msec, or 27-38mph; Cut-out speed the maximum wind speed at which a turbine operates before
shutting down for safety reasons, typically around 25msec, or 56mph; Inefficiencies due to rotor blade friction and drag, gearbox energy losses,
generator and converter losses, that reduce the power delivered by a wind turbine. Ch. 1 Figure 15 illustrates the technical power available at 30 m 98 feet elevation across
the state calculated by Grilli et al. 2012, based on AWS TrueWind modeled wind speed data.
2
Power density measured in wattsm
2
refers to the energy of the wind hitting a vertical cross section found within the vertical plane circumscribed by the turbine’s rotor.
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Ch. 1 Figure 14. Theoretical wind power Wattsmeters2 that can be generated at a 30m 98ft hub height elevation.
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Ch. 1 Figure 15. Technical wind power wattsmeter2 that can be generated at a 30m 98ft hub height elevation assuming 14 ms [31mph] rated speed, cut in and cut out, 3.5 and 25ms [8 and 56mph] respectively.
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Technical resource can also be visualized by looking at a variable called capacity factor. Capacity factor is the ratio of the actual energy produced during a given time period to the
hypothetical maximum energy that could possibly be produced during that time if the turbine were running at rated speed 100 of the time. Capacity factor is a function of the frequency
distribution of wind speeds at a given site, the height of the turbine, and the rated speed of the turbine. From an economic perspective, generally capacity factors above 0.25 are considered
viable AWEA 2009, however there may be exceptions to this rule based on the economics of a specific project. Ch. 1 Figure 16 shows capacity factors across Rhode Island at 80m 262ft for a
turbine with a 12msec 27mph rated speed. In keeping with the wind resource maps shown previously, coastal areas show the greatest capacity factors.
Ch. 1 Figure 16. Annual mean capacity factor at 80m 262ft hub height.
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Practical Wind Resource in Rhode Island Practical wind power resource is a further refinement of the estimation of technical wind
power resource that accounts for restrictions on the availability of extractable wind power due to environmental and social considerations. There is no single, scientifically determined estimate of
practical resource for a given location. Rather, the practical resource at a site is determined by a wide array of factors that can be customized to meet the needs of individual communities. These
include tolerance of visual impacts, bird and bat impacts, noise and shadow flicker, and many other considerations detailed in Section 3 of this chapter. Section 4 of this chapter further
explores the practical wind resource available in Rhode Island by presenting environmental and social considerations that may make some sites less feasible to develop.
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Kategori