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Optimizing Wind Power Generation while Minimizing Wildlife Impacts in an Urban Area

Overview of attention for article published in PLOS ONE, February 2013
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Title
Optimizing Wind Power Generation while Minimizing Wildlife Impacts in an Urban Area
Published in
PLOS ONE, February 2013
DOI 10.1371/journal.pone.0056036
Pubmed ID
Authors

Gil Bohrer, Kunpeng Zhu, Robert L. Jones, Peter S. Curtis

Abstract

The location of a wind turbine is critical to its power output, which is strongly affected by the local wind field. Turbine operators typically seek locations with the best wind at the lowest level above ground since turbine height affects installation costs. In many urban applications, such as small-scale turbines owned by local communities or organizations, turbine placement is challenging because of limited available space and because the turbine often must be added without removing existing infrastructure, including buildings and trees. The need to minimize turbine hazard to wildlife compounds the challenge. We used an exclusion zone approach for turbine-placement optimization that incorporates spatially detailed maps of wind distribution and wildlife densities with power output predictions for the Ohio State University campus. We processed public GIS records and airborne lidar point-cloud data to develop a 3D map of all campus buildings and trees. High resolution large-eddy simulations and long-term wind climatology were combined to provide land-surface-affected 3D wind fields and the corresponding wind-power generation potential. This power prediction map was then combined with bird survey data. Our assessment predicts that exclusion of areas where bird numbers are highest will have modest effects on the availability of locations for power generation. The exclusion zone approach allows the incorporation of wildlife hazard in wind turbine siting and power output considerations in complex urban environments even when the quantitative interaction between wildlife behavior and turbine activity is unknown.

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Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Portugal 1 <1%
Ghana 1 <1%
Unknown 100 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 21%
Student > Ph. D. Student 20 19%
Student > Bachelor 18 17%
Student > Master 10 10%
Other 6 6%
Other 12 12%
Unknown 15 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 18%
Engineering 17 17%
Environmental Science 16 16%
Earth and Planetary Sciences 9 9%
Biochemistry, Genetics and Molecular Biology 4 4%
Other 17 17%
Unknown 21 20%