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ARS Home » Plains Area » Brookings, South Dakota » Integrated Cropping Systems Research » Research » Publications at this Location » Publication #236272
Title: A Data Envelopment Analysis Model for Renewable Energy Technology Selection

Author
item KONGAR, ELIF - UNIVERSITY OF BRIDGEPORT
item Rosentrater, Kurt

Submitted to: Symposium Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 3/24/2009
Publication Date: 4/1/2009
Citation: Kongar, E., Rosentrater, K.A. 2009. A Data Envelopment Analysis Model for Renewable Energy Technology Selection. Northeast Decision Sciences Institute, 2009 Annual Conference, Uncasville, CT, April 1-3, 2009.

Interpretive Summary: Public and media interest in alternative energy sources, such as renewable fuels, has rapidly increased in recent years due to higher prices for oil and natural gas. However, the current body of research providing comparative decision making models that either rank these alternative energy sources and/or determine the best possible alternatives is still limited. This paper aims at filling this gap by proposing a DEA model structure for ranking energy source alternatives under varying circumstances. The model considers both the economics of energy sources and additional environmental criteria such as CO2 emissions and damage cost. Numerical examples are also included to demonstrate the functionality of the proposed model.

Technical Abstract: Public and media interest in alternative energy sources, such as renewable fuels, has rapidly increased in recent years due to higher prices for oil and natural gas. However, the current body of research providing comparative decision making models that either rank these alternative energy sources and/or determine the best possible alternatives is still limited. This paper aims at filling this gap by proposing a DEA model structure for ranking energy source alternatives under varying circumstances. The model considers both the economics of energy sources and additional environmental criteria such as CO2 emissions and damage cost. Numerical examples are also included to demonstrate the functionality of the proposed model.