Untapped Wealth : Technical Methodology

Transcription

1 Untapped Wealth : Technical Methodology Oceana s report, Untapped Wealth, provides an analysis of the technological feasibility and cost effectiveness of offshore wind power. It does not attempt to detail specific ecologically sound practices, methods, or specific areas for development of offshore wind farms. Nor does it represent the level of accuracy needed for establishing siting criteria for specific offshore wind farm projects. Untapped Wealth highlights the substantial offshore wind resources available considering current technology and economic limitations. As technology advances, the ability to harvest offshore wind energy is expected to become more efficient and the estimates in this analysis do not consider future learning curves, technology improvements or price reductions. The estimates herein represent near-term, achievable offshore wind resource potential. Overall, Untapped Wealth relies on multiple conservative assumptions in developing estimates for offshore wind power production. At the same time, it may overestimate potential for Atlantic offshore oil and gas production. Despite this attempt to understate the benefits of offshore wind power and overstate the benefits of oil and gas, the analysis shows that offshore wind power offers greater energy production potential than new offshore oil and gas development. This document explains in detail the methodology used to obtain the estimates in the report. For additional details please contact Oceana directly. Estimating Potential Capacity Analytical Constraints Untapped Wealth aims to evaluate the most economically attractive areas for offshore wind development, and therefore quantify the total area where offshore wind farms could reasonably be built in the near term given the physical and economic limitations. Not all offshore areas are technically or economically useful for offshore wind farm development, and development in some areas should be restricted due to competing uses or ecological concerns. Several limitations reduce the likelihood of offshore wind farm development in a given area. Important limiting variables include ocean depth, distance from shore, and wind speed. These parameters are rarely entirely dependant on technical capability, rather, they are more commonly dependent on economics. Table 1: Assumptions Used to Determine Area Available for Near-term Offshore Wind Potential Parameter Figure Used Potential Range Limitation basis Hub Height 50 meters 50 Meters NREL Map Availability Water Depth 0-30 meters meters Economic Distance from Shore 3-24 nautical miles nautical miles Aesthetic, Economic Wind Speed 15.7 MPH MPH - >19.7 MPH Economic (Class 4 +) (Class 3 Class 7) Carrying Capacity 8 MW/km 2 6 MW/km 2 15 MW /km 2 Technological Exclusion Factor 67% 33% - 67% NREL Conservative Estimation 1/17

2 Hub Height For this analysis, we assume a hub height of 50 meters. This is a conservative assumption because all offshore wind turbines are expected to have hub heights greater than 50 meters. This figure was used, however, because it is the hub height for which wind resource data are provided by the National Renewable Laboratory (NREL). The NREL does not provide data for greater hub heights which would offer higher capacity factors and thus, more energy generation. As a result, the true amount of energy generated by higher hubs would be considerably greater in practice. Water Depth For this analysis, we limit the area available for offshore wind production to waters less than 30 meters deep. While it is likely that wind farms will be built in deeper waters in the coming decades, to date, all commercial offshore wind farms are in waters less than 30 meters deep. 1 The analysis is therefore limited to include only areas less than 30 meters deep, a conservative limitation. Bathymetry maps with a clear 30 meter delineation were generated in *.KMZ format and overlain in Google Earth using an application created by Columbia University (GeoMapApp) with a 100 meter resolution. 2 Distance from Shore The area between 3-24 nautical miles from shore was measured and considered to be the full extent of the area available for offshore wind farm development prior to the exclusion of some areas using the exclusion factor described below. Distance from shore is more of an aesthetic and economic constraint than a technological one. For this analysis, we assume there is no development within 3 nautical miles from shore, another conservative assumption to account for possible aesthetically driven limitations, as suggested by other, similar studies. 3 As offshore wind farms move further offshore costs increase 4 making it less likely offshore wind farms will be built further than 24 nautical miles in the near-term so this analysis was limited to areas less than 24 nautical miles from shore. As technology advances, offshore wind farms very well may become economically competitive at greater distances making this assumption again, a conservative one. Wind Speed Only wind speeds of 15.7 mph or greater are included in the analysis. The Department of Energy (DOE) has estimated that a substantial amount of electricity can be generated with wind speeds of 15.7 miles per hour (mph) offshore (Class 4 winds) for close to 12 cents per kilowatt hour of electricity generated. 5 As offshore wind turbines become technologically more efficient, lower wind speeds may prove more and more suitable for offshore wind development, which would increase the amount of wind energy that could be generated in the areas considered. However, this analysis excludes all offshore areas with wind speeds less than 15.7 mph (or less than Class 4 winds). Carrying Capacity Based on existing offshore wind farms and case studies, one square kilometer of sea area could support six to fifteen megawatts of offshore wind power capacity, using current technology (6 MW/km 2-15 MW/km 2 ). Untapped Wealth relies on a mid-range carrying capacity of 8 MW/ km 2, based on planned and operating offshore wind farms. The installed offshore wind farm most resembling this carrying capacity is Horns Rev, of Denmark; however, while other wind farms have higher values. Carrying capacity varies by turbine type, primary wind direction, wind velocity and turbulence. Actual projects would apply specialized studies to maximize output based on wind farm layout and would vary in carrying capacity some farms would have lower carrying capacities and others would have higher capacities compared to the assumption used for this analysis. 2/17

3 Table 2: Planned and Operating Offshore Wind Farms Project Country Capacity Turbine size MW/km 2 ratio Gwynt y Môr 6 United Kingdom 750 MW 3 MW 5 MW 6.1 MW/km 2 Maryland Case Study 7 United States - 5 MW 6.3 MW/km 2 Virginia Case Study 8 United States - 3 MW 6.4 MW/ km 2 Delaware Case Study 9 United States MW 6.7 MW/km 2 Cape Wind 10 United States 468 MW 3.6 MW 7.2 MW/km 2 Horns Rev 11 Denmark 160 MW 2 MW 8 MW/km 2 Barrow 12 United Kingdom 90 MW 3 MW 9 MW/km 2 Rhyl Flats 13 United Kingdom 90 MW 3.6 MW 9 MW/km 2 Kentish Flats 14 United Kingdom 90 MW 3 MW 9 MW/km 2 Clipper Wind United Kingdom - 10 MW 9.8 MW/km 2 MBE turbine 15 European Case Study 16-3 MW 10 MW 10 MW 15 MW/km 2 Alpha Ventus 17 Germany 60 MW 5 MW 15 MW/km 2 Italics indicate planned projects Bold indicates chosen carrying capacity Exclusion Factor Some areas that are technically available for wind power production might be off limits for a variety of reasons, including environmental concerns or national security. In order to account for such areas, an exclusion factor is often used to eliminate some otherwise available areas from estimations of available resource. To exclude such areas and determine the total available resource Untapped Wealth relies on an exclusion factor of 67 percent thus excluding two thirds of the areas that would otherwise meet the criteria described above. This is at the conservative end of the range of exclusion factors generally used in this type of analysis. 18 To be clear, for the technically and economically available resource, the analysis excludes 100 percent of areas between 0-3 nautical miles and beyond 24 nautical miles, and all areas greater than 30 meters deep. Then, it further excludes two thirds of the available area between 3 and 24 nautical miles and in waters less than 30 meters deep using the 67 percent exclusion factor This exclusion factor was chosen to prevent overstating the potential benefits of offshore wind development. Other analyses that attempt to map conflict zones have much lower exclusion factors as low as 33 percent. 19 Capacity Factors The capacity factor takes into account the fact that the wind does not always blow. A project built in a Class 6 wind area would be expected to generate more electricity than if that exact same project were built in an area with Class 4 winds. 20 To account for the benefits of higher wind class resources, capacity factors were based on DOE estimates which were developed by Black and Veach. 21 Table 3: Capacity Factors for Shallow Offshore Areas (<30m) at 50 Meter Altitude Power Class Capacity Factor Class Class Class Class Source: United States Department of Energy, Black & Veach 22 3/17

4 The capacity factors used in the analysis are also low-end estimates as several offshore wind farms already achieve greater than 45 percent capacity factors. 23 Also, as turbines are installed further offshore in deeper areas and as they expand in height and size as expected, capacity factors would be expected to increase accordingly. 24 See Capacity Factor Sensitivity Analysis below for a more detailed analysis of the capacity factors used in Untapped Wealth. 4/17

5 Offshore Wind Analysis Using the above criteria, two-dimensional (2D) wind resource map images were overlaid in Google Earth Pro s three-dimensional (3D) graphical user interface. Polygons were created by manually tracing areas based on the differing wind classes. These polygons were then fitted with state jurisdictional boundaries, state-federal offshore boundaries and contiguous sea boundaries (3 nautical mile and 24 nautical mile boundaries), and areas with bathymetries of 30 meters or less. Polygon area was then calculated (in square kilometers) to obtain total offshore wind area measurements. Area measurements were then multiplied by an 8 megawatt per kilometer squared (8MW/km 2 ) carrying capacity, which was then multiplied by a 33 percent inclusion factor (a 67 percent exclusion factor) to determine area carrying capacity. All polygon carrying capacities for each wind class and were added together by state in order to establish state resource availability. Annual electricity generation was estimated by multiplying carrying capacity by a corresponding wind class capacity factor and the number of hours in a year (8,760) and then by 1,000 to estimate kilowatt hours generated per year (1 megawatt hour = 1,000 kilowatt hours). Annual electricity generation for each polygon a given state was then added in order to establish total annual electricity generation for that state. To get the overall potential for the Atlantic coasts, all state totals were added, except for New Hampshire and Maine, which did not have sufficient area within the bounds of the analysis due to the lack of shallow water 3 nautical miles from shore. Image Overlay The 2009 NREL wind resource map shows estimated wind resources at 50 meters height, which is the basis for the offshore wind resource estimates. While most offshore wind turbines are significantly taller than 50 meters, NREL has not yet made an expansive offshore wind resource map at a higher hub height. Thus, using the 50 meter hub-height map provided by NREL adds yet another conservative aspect to the wind estimates.. Each image was overlain in Google Earth, using the image s state boundaries as guidelines, and resized dynamically so as not to overstate or understate the area of the wind resource. When imported to Google Earth, each pixel from the NREL map represents an area of approximately 6.25 square miles (2.5 miles x 2.5 miles). States with particularly large coastlines required overlaying two or more *.BMP images. The accuracy lost by this method of measurement is likely dwarfed by other aspects of the estimation process, such as bathymetry and distance from shore, which did not rely on manual overlay. The lack of perfect accuracy underscores the importance of not using this analysis as a siting guide. NREL and DOI should develop a similar resource assessment to estimate offshore wind potential. Polygon Creation To measure offshore areas in Untapped Wealth, it was necessary to create polygons, since polygon sizes are absolute and easily measureable. For each state, polygons were manually created for each of the wind classes available offshore (from Class 4 to Class 7 winds) by tracing over the overlain NREL map. To minimize jagged edges from pixilation of the NREL map, trace points were connected to the furthest extended point of a pixel. Between wind class areas, the trace points were connected to the furthest extended point of the lower wind class pixel, to minimize overstating the areas with higher wind class. In order to eliminate polygon overlap from the inaccuracy of manual tracing, *.XML code was copied into a text editor, where the string of code for the lower-level class polygon was copied and pasted in place of the higher-level class polygon string. State Jurisdiction (Defining 3 Nautical Mile and 24 Nautical Mile Lines) Data for the boundaries were obtained from the National Oceanic and Atmospheric Administration, Office of Coast Survey. 25 5/17

6 Bathymetry Bathymetry from GeoMapApp in *.KMZ format was overlain in Google Earth to identify areas that were less than 30 meters in depth. Lines were manually traced to exclude areas greater than 30 meters depth. Polygon *.XML code was edited to exclude depths greater than 30 meters in the same fashion as described above. Calculating Area Each polygon was saved as an individual *.KML file. KML code was copied and pasted to a KML area calculator, and results were returned in square kilometers. 26 Emissions Prevented Untapped Wealth relies on the United States Environmental Protection Agency s (EPA) Greenhouse Gas Equivalencies Calculator for estimating emissions prevented. The figure provided by EPA suggests that 1 Megawatt hour (MWh) of electricity generates, on average, 0.72 metric tons of carbon dioxide equivalent greenhouse gas emissions. In order to determine precisely how much greenhouse gas emissions could be reduced by offshore wind farms, one would have to identify exactly what form of power generation would be replaced and therefore detailed modeling would be necessary that could result in higher or lower averages than given by the EPA calculator. Such modeling is outside the scope of the analysis. Wind Turbine Economics This analysis relies heavily on DOE s report, 20% Wind Energy by 2030: Increasing Wind Energy s Contribution to US Electricity Supply 27 and supporting documentation. 28 The analysis compares offshore wind farm electric generation in a given state to other energy consumption and generation statistics for that state. Table 4: Shallow Offshore Wind Cost Estimates ($2006) Levelized Resource Costs no Class PTC (cents/kwh) Class Class Class Class Source: Black & Veach, Levelized Costs w/ptc (cents/kwh) Of the capital costs incurred by the development of an offshore wind farm, the largest costs include expenditures on turbines and turbine parts, installation and foundation costs, and transmission and transmission connection. 30 The figures in Table 4 above include turbines, towers, foundations, installation, profit, and interconnection fees. 31 The price per MWh figures are based on capacity factors described earlier (see Table 3: Capacity Factors for Shallow Offshore Areas (<30m) at 50 Meter Altitude above). 6/17

7 Cost per kwh and Annual Electricity Expenditure Black & Veach estimated shallow offshore wind power could provide electricity ranging from 10.6 cents to 13.1 cents per kilowatt hour depending on wind class (in 2006 dollars). This figure does not include price reductions that would result from the federal Production Tax Credit (PTC). 32 If a PTC were available, the prices would go down as shown in the table above. The price of electricity from offshore wind farms varies based on the relevant capacity factor. Since many states have more than one class of offshore wind power, to generate cost estimates, the electricity generation for each class was calculated, and then priced using the non-ptc based cost figures in Table 4 (above). For each state, the costs of electricity across the four wind classes, were added together and averaged to generate state costs. Studies on the cost of electricity from a United States offshore wind farm range from 3.2 cents per kilowatt hour 33, up to 29.1 cents per kilowatt hour. 34 As discussed earlier, project costs can vary due to foundation type, depth, distance from shore and turbine type. Several different technologies can be employed by offshore wind farms, even within the same development. The figures used in this analysis are meant to be general estimates, and are unlikely to reflect specific projects in an exact way. As the offshore wind industry advances, these costs will become better established. 7/17

8 Table 5: Economically and Technically Recoverable Resource (3-24nm, <30m bathymetry) State Wind Class Area (km2) Carrying Capacity (MW) Annual Generation (kwh) Cost $ 4 1,676 4,425 14,728,741,632 $1,929,465, $ $0 Florida West Total 4,425 14,728,741,632 $1,929,465, ,225 5,874 19,553,371,200 $2,561,491, $ $0 Florida East Total 5,874 19,553,371,200 $2,561,491, ,191 3,963,402,432 $519,205, $ $0 Georgia Total 1,191 3,963,402,432 $519,205, ,877 15,515 51,647,264,064 $6,765,791, ,387 3,662 13,472,053,056 $1,630,118, $0 South Carolina Total 19,177 65,119,317,120 $8,395,910, ,219 8,498 28,288,675,008 $3,705,816, ,900 18,216 67,020,307,200 $8,109,457, ,251 11,223 45,222,750,144 $5,110,170,766 North Carolina Total 37, ,531,732,352 $16,925,444, ,583,681,408 $338,462, ,501 9,243 34,005,521,088 $4,114,668, ,248 5,935 23,914,547,712 $2,702,343,891 Virginia Total 15,954 60,503,750,208 $7,155,474, ,161,855,872 $283,203, ,417 3,741 13,763,445,696 $1,665,376, ,170,195,840 $132,232,130 Maryland Total 4,681 17,095,497,408 $2,080,812, ,355,192,576 $308,530, ,930 7,100,267,328 $859,132, ,327,808 $98,573,042 Delaware Total 2,854 10,327,787,712 $1,266,235,616 New Jersey 4 1,623 4,285 14,262,975,936 $1,868,449, ,199 8,445 31,072,168,512 $3,759,732, ,245 3,287 13,244,489,280 $1,496,627,289 8/17

9 Total 16,017 58,579,633,728 $7,124,809, ,515 5,044,330,368 $660,807, ,064 2,809 10,334,725,632 $1,250,501, ,648,912,320 $186,327,092 New York Total 4,734 17,027,968,320 $2,097,636, ,124,736 $26,478, ,495,815,552 $180,993, ,095,728,832 $123,817,358 Rhode Island Total 739 2,793,669,120 $331,289, $ ,641,511,872 $198,622, ,872 12,862 51,829,037,568 $5,856,681, ,988,870,400 $210,820,262 Massachusetts Total 13,762 55,459,419,840 $6,266,124, ,788, ,894,500, ,797,846, New Hampshire Total 1,236 4,701,134, ,399,132, ,402 3,701 13,617,749, ,002 31, ,679,004, ,071 2,827 12,384,187,200 Maine Total 38, ,080,073, ,750 44, ,199,536, ,222 53, ,418,065, ,237 66, ,474,840, ,243 3,282 14,373,057,600 US East Coast Total 167, ,465,499, ,476 43, ,791,615,232 $18,967,701, ,522 48, ,905,815,936 $21,768,603, ,066 34, ,997,989,504 $15,706,772,814 US East Coast ,988,870,400 $210,820,262 (Excl. NH/ME) Total 127, ,684,291,072 $56,653,898,400 9/17

10 Wind/Oil/Gas Comparisons To better explain the energy potential of offshore wind, Untapped Wealth compares offshore oil and natural gas resources to offshore wind resources. This is done for the purposes of comparison, by normalizing each form of energy into kwh potential, BTU potential and potential miles that could be driven using the respective energy form. These are then compared to assess which fuel could do the most work, in terms of electrifying homes, heating homes or driving a light duty vehicle, respectively. While we recognize that these uses of wind could not be accomplished immediately at this scale, and that wind, oil and gas are not currently used for the same purposes, since each fuel can be used in each of these ways, and since there is potential for expansion in use of wind energy over time, this exercise provides a useful way to compare different fuels. It is assumed in each comparison that each fuel would be used entirely for the stated purpose. For example, if all the oil, gas and wind energy were used for electrical generation, how many homes could it power? Similarly, if it were all used for home heating, how many homes could it heat? Or if it were applied to transportation, how many vehicle-miles could be traveled. Please note that these estimates are not additive across uses. For the comparisons, we count all the oil, natural gas, and wind resources as being applied entirely to the given use. Oil and Natural Gas Resources The United States Department of the Interior (DOI) provides estimates for the offshore oil and natural gas resources on the outer continental shelf. DOI develops these estimates based on what is economically recoverable as some areas with oil and natural gas are too expensive to extract the resources at commercially viable levels. DOI estimates of the amounts of oil and gas available depend on the assumed price of oil and gas. Untapped Wealth compares offshore wind energy to DOI s economically recoverable assessment assuming $110 per barrel of oil, and $11.74 per thousand cubic feet of natural gas. 35 To allow comparison, it is assumed these resources are extracted, in total, over a 20 year period which is also the assumed operating lifetime of a wind turbine. For practical purposes, the analysis assumes that the oil and gas is extracted in equal amounts annually over that time period. Since the oil and gas on the Atlantic coast may not be entirely extracted in twenty years, this method may exaggerate the amount of oil and gas production, thus favoring oil and gas to some degree in the energy comparison. It is important to note that if in fact this resource was fully extracted in that time frame, after 20 years there would be no more economically recoverable oil or natural gas offshore. However, after the 20 year or longer lifespan for a wind turbine, a new turbine could be installed which could continue to collect offshore wind energy to generate electricity that is not considered in the comparison. As a result, the estimates and comparisons between offshore wind and offshore oil understate the potential of offshore wind and may overstate the potential of offshore oil and gas. This renewability value is not accounted for in our analysis. DOI has not yet performed a state-by-state estimate of economically recoverable oil and gas resources offshore; instead it does so on the basis of planning areas. This analysis focuses exclusively on states from Florida to Maine, including DOI s Eastern Gulf of Mexico, South Atlantic, Mid-Atlantic and North Atlantic planning areas. Since oil and gas estimates are not available on a state by state basis, comparisons are made by planning area rather than by state. Since Florida is part of three different planning areas, this analysis separates Florida s west coast into the Eastern Gulf of Mexico planning area, the Straits of Florida and the South Atlantic. The Straits of Florida resource assessments are considered as part of the South Atlantic figures. Estimating offshore wind resources by DOI planning area, which can be done simply by adding 10/17

11 the resource availability for the relevant states, allows for a direct comparison between wind and oil and gas. Offshore wind estimates for Connecticut were not performed in the analysis since it does not have federal waters, and estimates for New Hampshire and Maine were calculated for informational purposes, but they were not included in the total wind availability for the Atlantic Coast (127 GW figure) or the North Atlantic, since no considerable offshore wind potential exists in the 3-24 nautical mile limits in waters less than 30 meters depth in those states. Oil, Gas and Wind Comparison Electricity Generation on a Per-Home basis The DOI offshore oil and gas resources estimated for each planning area were converted into British Thermal Unit (BTU) output. One barrel of oil contains 5.8 million BTUs, while one cubic foot of gas contains 1,028 BTUs. 36 Each planning area s BTU potential was divided by 10,810 or the required BTUs to generate one kilowatt hour (kwh) of electricity in a conventional combustion turbine. 37 The offshore wind estimates developed in this analysis were available in kwh s, and thus no conversion to or from BTUs was required. Each of the kwh estimates for oil, gas and wind was divided by 11,020, or the number of kwh s consumed annually by the average American home. 38 The oil and gas resources are assumed to be extracted, in full, in equal amounts each year over 20 years- or the expected lifespan of a single wind turbine. Oil, Gas and Wind Comparison Heating on a Per-Home basis The DOI offshore oil and gas resources estimated for each planning area were provided in barrels (a barrel is 42 gallons) and cubic feet. DOE reports average annual consumption of primary heating fuel in gallons for oil, cubic feet for natural gas, and kilowatt hours for electricity. To equate oil, gas and wind resources into home heating, each resource for each planning area was divided by the consumption figures provided by DOE. This analysis relies on average annual consumption for space heating by main space heating fuel in New England, the Mid-Atlantic and South Atlantic 39. Oil, Gas and Wind Comparison Cars For this comparison, the DOI offshore oil and gas resources estimated for each planning area were converted to gallons of gasoline and gasoline equivalent. For each barrel of oil, gallons of gasoline can be extracted 40 and EPA estimates that cubic feet of natural gas is the equivalent of one gallon of gasoline. 41 Gasoline and gasoline equivalents were then converted to potential miles that could be driven, where each planning area s gasoline (oil) and gasoline equivalent (natural gas) potential was multiplied by 31.5 or the expected average car stock miles per gallon in 2030 according to DOE. 42 The offshore wind estimates developed in this analysis were available in kilowatt hours (kwh), and NREL estimates that an electric vehicle could travel 2.9 miles on one kwh of electricity. 43 Each planning area s wind generation potential was multiplied by 2.9 to estimate the number of miles that could be driven using the available wind energy. To convert miles driven to cars, each resource for each planning area was divided by 12,000 or the average number of miles driven by a residential vehicle /17

12 Capacity Factor Sensitivity Analysis The Oceana analysis relies on capacity factors from a 2007 study prepared by Black & Veach for DOE. The capacity factors are broken down by wind class (wind speed) at 50 meters height, in waters less than 30 meters depth, and are as follows: Table 6: Wind Class and Speed with Capacity Factors at 50 meters Wind Class Wind Speed m/s (mph) Capacity Factor Class (15.7) (16.8) 0.38 Class (16.8) (17.9) 0.42 Class (17.9) (19.7) 0.46 Class 7 >8.8 (19.7) 0.50 Source: United States Department of Energy, Black & Veach 45 In order to evaluate if these capacity factors are appropriate figures to use in the analysis, an already existing, installed offshore wind farm was compared to these figures. The Barrow Offshore Wind Farm (United Kingdom) has a rated capacity of 90 megawatts from 30 turbine generators (Vestas V90, 3 MW machines) with a carrying capacity of 9 MW / km 2 and has been in operation since The Actual Capacity Factors, Budgeted Capacity Factors and wind speeds at 75 meters height from the farm are reported annually and are as follows for the most recent report: Table 7: Barrow Offshore Wind Farm Wind Speeds at 75 meters, with Actual Capacity Factor and Budgeted Capacity Factor Date Speed (m/s) at 75m Actual Capacity Factor Budgeted Capacity Factor July August September October November December January February March April May June Average Source: UK Department of Energy and Climate Change (2009) 46 In order to compare the Actual and Budgeted capacity factors of the Barrow farm to Oceana s figures, the wind speeds reported at Barrow must be inferred at 50 meters height not 75 meters. Inferring wind speeds follows the 1/7th power law as follows: Inferred wind speed = (Inferred wind speed s height / Reference height) 1/7 *Reference wind speed Once the wind speeds at Barrow are inferred to 50 meters, Oceana s capacity factors can be directly compared to the Actual and Budgeted factors from the Barrow farm as follows: 12/17

13 Table 8: Inferred Barrow Offshore Wind Farm Wind Speeds at 50 meters, with Actual Capacity Factor, Budgeted Capacity Factor and Oceana Capacity Factor Date Inferred speed (m/s) at 50m Actual Capacity Factor Budgeted Capacity Factor Oceana Capacity Factor July August September October November December January February March April May June Average Source: Oceana and UK Department of Energy and Climate Change (2009) 47 As compared to the Actual Capacity Factor, the Oceana Capacity Factors are on average 4 points higher which would result in 10.5% higher estimates. As compared to the Budgeted Capacity Factor, the Oceana Capacity Factors are on average 1 points higher which would result in 3% higher estimates. However, some considerations suggest that Oceana s estimates are more in line with the true capacity factors. Barrow s lower capacity factors can be explained by the substandard performance of the farm from July-November 2007 when all 30 of the turbine gearboxes were replaced, which led to significantly lower Actual Capacity Factors from the Budgeted Capacity Factors. It should be noted the Actual Capacity Factors reflect operating rates and capacity factors combined, therefore operating rates are inclusive of the Actual Capacity Factors. Oceana s exclusion of Class 3 and lower wind speeds (<7 m/s, 15.7 MPH) and its ceiling on capacity factors (0.50 capacity factor for Class 7+ winds) aids in preventing overestimation of electricity output based on capacity factors. For example, in October 2007, the Barrow farm reported an average wind speed of 6.7 m/s at the 50 meter inferred height. Even though the Barrow farm still reported a Actual Capacity Factor for the month, no capacity factor would have been used in Oceana s analysis since these speeds were less than Class 4 winds. Additionally, for the months of November and December 2007 as well as January and March 2008, Actual Capacity Factors at the Barrow Farm were reported in excess of the Oceana Capacity Factor of 0.50 that would have been attributed to these wind speeds. Eliminating the three months that an Oceana Capacity Factor would have been attributed to the Barrow farm, while the farm was under-performing due to gearbox exchange, suggests that the Oceana Capacity Factors used in its analysis are not overestimates, but are very much on par for Actual Capacity Factors at an existing offshore wind farm. 13/17

14 Table 9: Inferred Barrow Offshore Wind Farm Wind Speeds at 50 meters, with Actual Capacity Factor, Budgeted Capacity Factor and Oceana Capacity Factor (Excluding months when turbines malfunctioned) Date Inferred speed (m/s) at 50m Actual Capacity Factor Budgeted Capacity Factor July August September October November December January February March April May June Average Source: Oceana and UK Department of Energy and Climate Change (2009) 48 Oceana Capacity Factor Excluding July, August and September 2007, when mechanical difficulties were experienced resulting in extremely low Actual Capacity Factors, but retaining the Actual Capacity Factor and Budgeted Capacity Factor for October 2007 because the Oceana Capacity Factors would not have registered this month (making the point of mechanical malfunction moot), it becomes evident that the Budgeted Capacity Factors and the Oceana Capacity Factors average out to be about the same. Additionally, compared to the Actual Capacity Factors, the Budgeted Capacity Factors as well as the Oceana Capacity Factors are too similar to dismiss as overestimates. Therefore, in two instances (the average of the Budgeted Capacity Factors July 2007-June 2008, and the average of the Actual Capacity Factors October 2007-June 2008), the average of the Oceana Capacity Factors are within a one point difference (~3%+/- output) of an actual, installed offshore wind farm. 14/17

15 1 Snyder, Brian and Kaiser, Mark (2008, November 9). Ecological and Economic Cost-Benefit Analysis of Offshore Wind Enregy, Renewable Energy 34; Columbia University (2010). Installing GeoMapApp on a Windows System, Marine Geoscience Data System, Lamont-Doherty Earth Observatory. [ 3 Musial, W. and Butterfield, S. (2004, June 28-29). "Future for Offshore Wind Energy in the United States," National Renewable Energy Laboratory, United States Department of Energy. [ 4 Musial, W. and Butterfield, S. (2004, June 28-29). "Future for Offshore Wind Energy in the United States," United States Department of Energy - National Renewable Energy Laboratory. [ 5 United States Department of Energy (2008, May). 20% Wind Energy by 2030:Increasing Wind Energy s Contribution to US Electricity Supply, P [ 6 Mott MacDonald (2010). "Gwynt y Mor Offshore Wind Farm, UK," [ 7 The Abell Foundation (2010, February 8). Maryland s Offshore Wind Power Potential, [ 8 Hagerman, George (2009, July 17). Green Power Superhighways or Offshore Wind or Both? Environmental and Energy Study Institute Capitol Hill Briefing. 9 Dhanju, Amardeep, Phillip Whitaker, and Willett Kempton (2007, March 7). Assessing offshore wind resources: An accessible methodology, Renewable Energy. [ 10 United States Department of Interior (2009, January). "Cape Wind - Final Environmental Impact Statement," Minerals Management Service. [ ct%20feis.pdf]. 11 Power-Technology (2009). "Horns Rev Offshore Wind Farm, Denmark," [ 12 Barrow Offshore Wind Limited (2008). "Barrow Offshore Wind: Project," [ 13 RWE NPower Renewables (2009, December 2). "RWE Innogy Opens Biggest Offshore Wind Farm in Wales," [ 14 Vattenfall. "Kentish Flats - Facts," [ 15 Based on 7 times 144 meter rotor diameter Clipper Wind (2010, February 18). "Clipper Windpower Announces Ground Breaking for Offshore Wind Blade Factory," [ 16 European Environment Agency (2009). Europe s onshore and offshore wind energy potential: An assessment of environmental and economic constraints, [ 17 Alpha Ventus (2009, August). Fact Sheet, [ 18 Musial, W. and S. Butterfield (2004, June). Future for Offshore Wind Energy in the United States, Preprint, United States Department of Energy - National Renewable Energy Laboratory. [ 19 Firestone, Jeremy, Willett Kempton, Blaise Sheridan, and Scott Baker (2010, February 18). Maryland s Offshore Wind Power Potential, The Abell Foundation and the College of Earth, Ocean, and Environment at the University of Delaware. [ 20 Laxon, A.; Hand, M.M.; and, Blair, N. (2006, October). High Wind Penetration Impact on US Wind Manufacturing Capacity and Critical Resources, United States Department of Energy - National Renewable Energy Laboratory. [ 15/17

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17 41 FuelEconomy.gov. Search for cars that don t need gasoline, [ 42 United States Department of Energy (2010). Table 59. Light Duty Vehicle Miles per Gallon by Technology Type. [ 43 Short, W. and P. Denholm (2006, April). A Preliminary Assessment of Plug-In Hybrid Electric Vehicles on Wind Energy Markets, United States Department of Energy National Renewable Energy Laboratory. [ 44 United States Department of Energy (2001). Per Vehicle Average Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001, Energy Information Administration. [ 45 Black & Veach (2007, October). "20 Percent Wind Energy Penetration in the United States," Final Report. Prepared for American Wind Energy Association. [ 46 United Kingdom Department of Energy and Climate Change (2008, June). Barrow Offshore Wind Farm 2 nd Annual Report, Offshore Wind Capital Grant Scheme. [ 20uk/1_ _e_@@_barrowannualreportjuly2007tojune2008final.pdf&filetype=4]. 47 United Kingdom Department of Energy and Climate Change (2008, June). Barrow Offshore Wind Farm 2 nd Annual Report, Offshore Wind Capital Grant Scheme. 0uk/1_ _e_@@_barrowannualreportjuly2007tojune2008final.pdf&filetype=4 48 United Kingdom Department of Energy and Climate Change (2008, June). Barrow Offshore Wind Farm 2 nd Annual Report, Offshore Wind Capital Grant Scheme. 0uk/1_ _e_@@_barrowannualreportjuly2007tojune2008final.pdf&filetype=4 17/17