95th ESA Annual Meeting (August 1 -- 6, 2010)

PS 62-145 - Temporal trends in US wind power energy density and the impacts of geographic features

Wednesday, August 4, 2010
Exhibit Hall A, David L Lawrence Convention Center
Jay E. Diffendorfer, Geosciences and Environmental Change Science Center, U.S. Geological Survey, Denver, CO and Roger W. Compton, Rocky Mountain Geographic Science Center, United States Geological Survey, Denver, CO
Background/Question/Methods Wind energy is the fastest growing segment of the electricity market and will likely continue as countries strive to reduce CO2 production while meeting energy demands.  Research continues to predict the environmental consequences of wind energy, compare impacts of different energy production technologies, consider methods for optimal placement of wind facilities, and study the role wind should play in future energy strategies.  All of these require fundamental information relating wind installations to the energy they produce and their impacts (both positive and negative) on economic, cultural, and environmental systems. However, high quality data relevant to policy-level decision making and wind power, particularly its spatial disturbance and future trends, are not yet accurately estimated.  Indeed, a wide range of energy densities (MW of electricity generated/area impacted) have been reported.  In addition, the capacity of turbines is increasing with enhanced R&D and manufacturing efficiencies.  Larger capacity turbines should result in higher energy densities.  Current projections of future wind impacts fail to account for this temporal trend in technology development.  In addition, geographic features and land use should affect the impacts of wind installations.  Our goal was to study the impacts of time, geographic features, and land use on the energy density of wind power as an initial step towards calculating robust estimates of future wind impacts. We developed a geodatabase of windfarms, then selected 40 installations based on start date and variables related to land form and land use.  We used Generalized Random Tessellation Stratified sampling to subsample each installation, then digitized roads, powerlines, pads, and buried cables to estimate area disturbed.  Turbine and field capacity were derived from information at the Energy Information Administration. 

Results/Conclusions Installed capacity of individual turbines has grown at a near exponential rate in the US since 1980, following trends found in other technology sectors.  Across our sites, energy density increased as turbine capacity increased, indicating published estimates of future wind impacts are likely over estimates because they do not account for the higher energy density of new technology in future installations.  Land use features explain variation in the energy density of wind power because topography drives road networks and connections to transmission lines, the major component of surface disturbance in a wind installation.