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Global Potential for Wind-Generated Electricity

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Global Potential for Wind-Generated Electricity Global potential for wind-generated electricity Xi Lua, Michael B. McElroya,b,1, and Juha Kiviluomac aSchool of Engineering and Applied Science, Cruft Lab 211, and bDepartment of Earth and Planetary Sciences, Harvard University, 100E Peirce Hall, 29 Oxford Street, Cambridge, MA 02138; and cVTT Technical Research Centre of Finland, P. O. Box 1000, 02044 VTT, Finland Communicated by James G. Anderson, Harvard University, Cambridge, MA, April 29, 2009 (received for review November 6, 2008) The potential of wind power as a global source of electricity is of the relatively high spatial resolution available with this product assessed by using winds derived through assimilation of data from a as compared with the lower spatial resolutions available with variety of meteorological sources. The analysis indicates that a net- alternative products such as ERA-40, NECP II, and JRA-25. It is work of land-based 2.5-megawatt (MW) turbines restricted to non- used here in a detailed study of the potential for globally distributed forested, ice-free, nonurban areas operating at as little as 20% of their wind-generated electricity in 2006. rated capacity could supply >40 times current worldwide consump- We begin with a description of the methodology adopted for tion of electricity, >5 times total global use of energy in all forms. the present study. The land-based turbines envisaged here are Resources in the contiguous United States, specifically in the central assumed to have a rated capacity of 2.5 MW with somewhat plain states, could accommodate as much as 16 times total current larger turbines, 3.6 MW, deployed offshore, reflecting the demand for electricity in the United States. Estimates are given also greater cost of construction and the economic incentive to for quantities of electricity that could be obtained by using a network deploy larger turbines to capture the higher wind speeds avail- of 3.6-MW turbines deployed in ocean waters with depths <200 m able in these regions. In siting turbines over land, we specifically within 50 nautical miles (92.6 km) of closest coastlines. excluded densely populated regions and areas occupied by forests and environments distinguished by permanent snow and ind power accounted for 42% of all new electrical capacity ice cover (notably Greenland and Antarctica). Turbines located Wadded to the United States electrical system in 2008 al- offshore were restricted to water depths Ͻ200 m and to distances though wind continues to account for a relatively small fraction of within 92.6 km (50 nautical miles) of shore. the total electricity-generating capacity [25.4 gigawatts (GW) of a These constraints are then discussed, and results from the total of 1,075 GW] (ref. 1; www.awea.org/pubs/documents/ global analysis are presented followed by a more detailed Outlook࿝2009.pdf). The Global Wind Energy Council projected the discussion of results for the United States. possibility of a 17-fold increase in wind-powered generation of electricity globally by 2030 (ref. 2; www.gwec.net/fileadmin/ Methodology documents/Publications/GWEO࿝2008࿝final.pdf). Short et al. (3), The GEOS-5 analysis uses a terrain-following coordinate system using the National Renewable Energy Laboratory’s WinDs model, incorporating 72 vertical layers extending from the surface to a concluded that wind could account for as much as 25% of U.S. pressure level of 0.01 hPa (an altitude of Ϸ78.2 km) (5). electricity by 2050 (corresponding to an installed wind capacity of Individual volume elements are defined by their horizontal Ϸ300 GW). boundaries (latitude and longitude) and the pressures at their top Archer and Jacobson (4) estimated that 20% of the global total and bottom. The horizontal resolution of the simulation is 2/3° wind power potential could account for as much as 123 petawatt- longitude by 1/2° latitude (equivalent to Ϸ66.7 km ϫ 50.0 km at hours (PWh) of electricity annually [corresponding to annually midlatitudes). The model provides 3D pressure fields at both averaged power production of 14 terawatts (TW)] equal to 7 times layer centers and layer edges in addition to wind speeds (me- the total current global consumption of electricity (comparable to ridional and zonal) and temperatures at the midpoint of indi- present global use of energy in all forms). Their study was based on vidual layers with a time resolution of 6 h. The 3 lowest layers are an analysis of data for the year 2000 from 7,753 surface meteoro- centered at approximate altitudes of 71, 201, and 332 m. The 6-h SCIENCE logical stations complemented by data from 446 stations for which data for the 3 lowest layers are used in the present analysis by SUSTAINABILITY vertical soundings were available. They restricted their attention to using an interpolation scheme indicated as follows to estimate power that could be generated by using a network of 1.5-megawatt temperatures, pressures, and wind speeds at 100 m, the hub (MW) turbines tapping wind resources from regions with annually height for the 2.5- and 3.6-MW turbines considered here. averaged wind speeds in excess of 6.9 m/s (wind class 3 or better) Knowing pressures at the lower and upper edges of individual at an elevation of 80 m. The meteorological stations used in their layers together with temperatures and pressures at the midpoints analysis were heavily concentrated in the United States, Europe, of the layers, altitudes corresponding to the midpoints of the and Southeastern Asia. Results inferred for other regions of the layers are calculated based on an iterative application of the SCIENCES world are subject as a consequence to considerable uncertainty. barometric law by assuming a linear variation of temperature ENVIRONMENTAL The present study is based on a simulation of global wind fields between the midpoints of individual layers. The barometric law from version 5 of the Goddard Earth Observing System Data was also used to calculate the pressure at 100 m. Wind speeds and Assimilation System (GEOS-5 DAS). Winds included in this com- temperatures at 100 m were computed by using a cubic spline fit pilation were obtained by retrospective analysis of global meteo- to data at the midpoints of the 3 lowest layers. rological data using a state-of-the-art weather/climate model in- The kinetic energy of the wind intercepted by the blades of a corporating inputs from a wide variety of observational sources (5), turbine per unit time (P) depends on the density of the air (␳), including not only surface and sounding measurements as used by the area swept by the rotor blades (␲r2), and the cube of the wind 3 Archer and Jacobson (4) but also results from a diverse suite of speed (V ) reduced by an efficiency or power factor (fp) accord- measurements and observations from a combination of aircraft, ing to the formula (6): balloons, ships, buoys, dropsondes and satellites, in short the gamut of observational data used to provide the world with the best possible meteorological forecasts enhanced by application of these Author contributions: X.L. and M.B.M. designed research; X.L. and M.B.M. performed data in a retrospective analysis. The GEOS-5 wind field is currently research; X.L., M.B.M., and J.K. analyzed data; and X.L., M.B.M., and J.K. wrote the paper. available for the period 2004 to the present (March 20, 2009) with The authors declare no conflict of interest. plans to extend the analysis 30 years back in time. The GEOS-5 Freely available online through the PNAS open access option. assimilation was adopted in the present analysis to take advantage 1To whom correspondence should be addressed. E-mail: [email protected]. www.pnas.org͞cgi͞doi͞10.1073͞pnas.0904101106 PNAS ͉ July 7, 2009 ͉ vol. 106 ͉ no. 27 ͉ 10933–10938 Downloaded by guest on October 1, 2021 1 P ϭ ␳␲r2f V 3 [1] 2 p The efficiency with which kinetic energy intercepted at any given wind speed is converted to electricity by the turbine depends on details of the turbine design specified by what is referred to as the turbine power curve. Typically, conversion to electricity varies as the cube of the wind speed at low wind speeds, asymptoting to a constant value for moderate to higher wind speeds, dropping to 0 at the highest wind speeds when the blades of the turbine are normally feathered to prevent damage. For the present purpose, we chose to use power curves and technical parameters for 2.5- and 3.6-MW turbines marketed by General Electric (GE) (http:// ࿝ ࿝ Fig. 1. Global distribution of annual average onshore wind power potential gepower.com/businesses/ge wind energy/en/index.htm). (W/m2) for 2006 accounting for spatial limitations on placement without 3 These power curves assume an air density of 1.225 kg/m under limitations on potential realizable capacity factors. conditions corresponding to an air temperature of 15 °C at a pressure of 1 atmosphere (7). To account for the differences in air density at the rotor elevations as compared with this stan- 100% of the time. We assume in this context that downtime for dard, wind speeds in the published power/wind speed curves maintenance accounts for loss of only a small fraction of the total were adjusted according to the formula potential power that could be generated by the installed turbines reflecting the fact that maintenance is normally scheduled for P ⅐ T 1/3 periods of relatively low wind conditions (11). We restrict V ϭ ͩ ͪ ⅐ V , [2] corrected 1.225R original attention in this analysis to regions with capacity factors Ͼ20%.
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