This graph is based on technology that is three generations old, deployed offshore, which means it is in a good wind location. Offshore wind delivers a capacity factor of around 44% vs onshore at 30-33%.
The models being deployed now offshore are 3.0 -3.6Mw per turbine. The ones in testing phase are around 7Mw/ per turbine.
Energy return on investment (EROI), economic feasibility and carbon intensity of a hypothetical Lake Ontario wind farm
"Although the energy demands used from the Wind Power Note and Elsam studies are normalized on a per-MW basis, it is not assumed nor suggested that the energy requirement for a wind turbine is linearly proportional to its capacity rating. No evidence suggests that this is the case; rather, it can be assumed that larger turbines will require proportionally less energy during their life cycles than smaller turbines. This is a likely result of economies of scale energy cost savings. However, each of the four turbines analyzed (in the Wind Power Note, Elsam and this analysis) are within a half-megawatt of capacity rating. Thus, the margin of error will be much smaller than if an analysis of a 100 kW turbine was performed using this method. Additionally, the goal of this analysis is to provide a reasonable approximation of the energy requirement and energy return on investment (EROI) expected for turbines used in a Lake Ontario wind farm. As the farm remains hypothetical, a close approximation is the extent of what can sensibly be achieved, and certainly well suited for this initial analysis.
Table 3: Per turbine energy requirement, production, EROI, and energy payback period.
Table 3 provides a breakdown of the predicted energy requirements of the GE 1.5 MW and Vestas 1.65 MW turbines using the values from the Wind Power Note and Elsam studies. In relation to their expected lifetime power production, an EROI of between 28.3 and 36.7 is calculated for the GE turbine and between 30.5 and 39.6 for the Vestas turbine. The average energy requirement is about 4.22 million kWh for the GE turbine and 4.64 million kWh for the Vestas turbine. The energy payback period for both turbines is less than one year." http://www.eoearth.org/article/Energy_return_on_investment_%28EROI%29%2C_economic_feasibility_and_carbon_intensity_of_a_hypothetical_Lake_Ontario_wind_farmAnd this from an older study of land based wind farms by the editor of the article above. This analysis iss basesd on technology this is literally antiquated,:
Energy from Wind: A Discussion of the EROI Research"...The EROI for wind turbines compares favorably with other power generation systems (Figure 3). Baseload coal-fired power generation has an EROI between 5 and 10:1. Nuclear power is probably no greater than 5:1, although there is considerable debate regarding how to calculate its EROI. The EROI for hydropower probably exceed 10, but in most places in the world the most favorable sites have been developed....
...Another reason that larger turbines have a larger EROI is the well-known "cube rule" of wind power, i.e., that the power available from the wind varies as the cube of the wind speed. Thus, if the wind speed doubles, the power of the wind increases 8 times. New turbines are taller than earlier technologies, and thus extract energy from the higher winds that exist at greater heights. Surface roughness -- roughness determined mainly by the height and type of vegetation and buildings -- reduces wind velocity near the surface. Over flat, open terrain in particular, the wind speed increases relatively fast with height...."http://www.theoildrum.com/story/2006/10/17/18478/085http://www.osti.gov/energycitations/product.biblio.jsp?osti_id=78265 Cavallo 1995:
Description/Abstract Wind-generated electricity can be fundamentally transformed from an intermittent resource to a baseload power supply. For the case of long distance transmission of wind electricity, this change can be achieved at a negligible increase or even a decrease in the per unit cost of electricity. The economic and technical feasibility of this process can be illustrated by studying the example of a wind farm located in central Kansas and a 2,000 km, 2,000 megawatt transmission line to southern California. Such a system can have a capacity factor of 60%, with no economic penalty and without storage. With compressed air energy storage (CAES) (and with a negligible economic penalty), capacity factors of 70--95% can be achieved. This strategy has important implications for the development of wind energy throughout the world since good wind resources are usually located far from major demand centers.
http://adsabs.harvard.edu/abs/2005JGRD..11012110AArcher & Jacobson 2005
Abstract
The goal of this study is to quantify the world's wind power potential for the first time from data. Wind speeds are calculated at 80 m, the hub height of modern, 77-m diameter, 1500 kW turbines. Since relatively few observations are available at 80 m, the Least Square extrapolation technique is utilized and revised here to obtain estimates of wind speeds at 80 m given observed wind speeds at 10 m (widely available) and a network of sounding stations. Tower data from the Kennedy Space Center (Florida) were used to validate the results. Globally, ~13% of all reporting stations experience annual mean wind speeds >= 6.9 m/s at 80 m (i.e., wind power class 3 or greater) and can therefore be considered suitable for low-cost wind power generation. This estimate is believed to be conservative. Of all continents, North America has the largest number of stations in class >= 3 (453), and Antarctica has the largest percent (60%). Areas with great potential are found in northern Europe along the North Sea, the southern tip of the South American continent, the island of Tasmania in Australia, the Great Lakes region, and the northeastern and northwestern coasts of North America. The global average 10-m wind speed over the ocean from measurements is 6.64 m/s (class 6); that over land is 3.28 m/s (class 1). The calculated 80-m values are 8.60 m/s (class 6) and 4.54 m/s (class 1) over ocean and land, respectively. Over land, daytime 80-m wind speed averages obtained from soundings (4.96 m/s) are slightly larger than nighttime ones (4.85 m/s); nighttime wind speeds increase, on average, above daytime speeds above 120 m. Assuming that statistics generated from all stations analyzed here are representative of the global distribution of winds, global wind power generated at locations with mean annual wind speeds >= 6.9 m/s at 80 m is found to be ~72 TW (~54,000 Mtoe) for the year 2000. Even if only ~20% of this power could be captured, it could satisfy 100% of the world's energy demand for all purposes (6995-10177 Mtoe) and over seven times the world's electricity needs (1.6-1.8 TW). Several practical barriers need to be overcome to fully realize this potential.
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6TH1-4N7RY2T-9&_user=260508&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000015498&_version=1&_urlVersion=0&_userid=260508&md5=263c93fcf3a4e293a1f66f1864850ef4Abstract
Kempton 2007
Electric-drive vehicles can provide power to the electric grid when they are parked (vehicle-to-grid power). We evaluated the economic potential of two utility-owned fleets of battery-electric vehicles to provide power for a specific electricity market, regulation, in four US regional regulation services markets. The two battery-electric fleet cases are: (a) 100 Th!nk City vehicle and (b) 252 Toyota RAV4. Important variables are: (a) the market value of regulation services, (b) the power capacity (kW) of the electrical connections and wiring, and (c) the energy capacity (kWh) of the vehicle's battery. With a few exceptions when the annual market value of regulation was low, we find that vehicle-to-grid power for regulation services is profitable across all four markets analyzed. Assuming now more than current Level 2 charging infrastructure (6.6 kW) the annual net profit for the Th!nk City fleet is from US$ 7000 to 70,000 providing regulation down only. For the RAV4 fleet the annual net profit ranges from US$ 24,000 to 260,000 providing regulation down and up. Vehicle-to-grid power could provide a significant revenue stream that would improve the economics of grid-connected electric-drive vehicles and further encourage their adoption. It would also improve the stability of the electrical grid.
Now it's your turn, you don't get a pass by claiming "just let it lay where it is and we'll be ok." I've laid out a number of the issues related to the risks associated with nuclear energy - address those risks directly and comprehensively or STFU.