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ARS Home » Plains Area » Brookings, South Dakota » Integrated Cropping Systems Research » Research » Publications at this Location » Publication #239002
Title: A Data Envelopment Analysis Approach to Prioritize Renewable Energy Technologies

Author
item KONGAR, ELIF - University Of Bridgeport
item Rosentrater, Kurt

Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 4/1/2009
Publication Date: 4/3/2009
Citation: Kongar, E., Rosentrater, K.A. 2009. A Data Envelopment Analysis Approach to Prioritize Renewable Energy Technologies. American Society for Engieering Education, 2009 Northeast Conference, Bridgeport CT, April 3-4, 2009.

Interpretive Summary: Due to growing financial and environmental concerns, governmental rules, regulations and incentives alternative energy sources will soon grow at a much faster pace than conventional sources of energy. However, the current body of research providing comparative decision making models that either rank these alternative energy sources and/or determine best possible alternatives is still limited. In addition, there is no unifying model that benchmarks the environmental efficiencies of countries in terms of their alternative energy usage in relation to environmental damage. This paper aims at filling these gaps by proposing two sets of Data Envelopment Analysis (DEA) models to (i) rank energy source alternatives, and (ii) rank countries depending on various criteria. The first set of DEA models considers both the economics of energy sources and additional environmental criteria such as CO2 emissions and damage cost. The second DEA model evaluates the relative environmental efficiencies of the top 25 petroleum consuming countries in the world. Numerical examples are also included to demonstrate the functionality of the proposed models.

Technical Abstract: Due to growing financial and environmental concerns, governmental rules, regulations and incentives alternative energy sources will soon grow at a much faster pace than conventional sources of energy. However, the current body of research providing comparative decision making models that either rank these alternative energy sources and/or determine best possible alternatives is still limited. In addition, there is no unifying model that benchmarks the environmental efficiencies of countries in terms of their alternative energy usage in relation to environmental damage. This paper aims at filling these gaps by proposing two sets of Data Envelopment Analysis (DEA) models to (i) rank energy source alternatives, and (ii) rank countries depending on various criteria. The first set of DEA models considers both the economics of energy sources and additional environmental criteria such as CO2 emissions and damage cost. The second DEA model evaluates the relative environmental efficiencies of the top 25 petroleum consuming countries in the world. Numerical examples are also included to demonstrate the functionality of the proposed models.