A Spatial Decision Support System for the Development of Multi-Source Renewable Energy Systems

This research involves the development of a comprehensive decision support system for energy planning through the increased use of renewable energy sources, while still considering the role of existing electricity generating facilities. This dissertation focuses on energy planning at the regional level, with the Greater Southern Appalachian Mountain region chosen for analysis due to the dependence on coal as the largest source of generation and the availability of wind and solar resources within the region. The first stage of this planning utilizes a geographic information system (GIS) for the discovery of renewable energy sources. This GIS model analyzes not just the availability of wind and solar power based on resource strength, but also considers the geographic, topographic, regulatory, and other constraints that limit the use of these resources. The model determines potential wind and solar sites within the region based on these input constraints, and finally the model calculates the cost and generation characteristics for each site. The results of the GIS model are then input into the second section of the model framework which utilizes a multi-objective linear programming (MOLP) model to determine the optimal mix of new renewable energy sources and existing fossil fuel facilities. In addition to the potential wind and solar resources discovered in the GIS, the MOLP model considers the implementation of solid wood waste biomass for co-fire at coal plants. The model consists of two competing objectives, the minimization of annual generation cost and the minimization of annual greenhouse gas emissions, subject to constraints on electricity demand and capital investment, amongst others. The model uses the MiniMax function in order to find solutions that consider both of the objective functions. The third major section of this dissertation analyzes three potential public policies — renewable portfolio standard, carbon tax, and renewable energy production tax credit — that have been used to foster increased renewable energy usage. These policies require minor modifications to the MOLP model for implementation. The results of these policy cases are then analyzed to determine the impact that these policies have on generation cost and pollution emissions within the region.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Business (Management Science)

Department dc:contributor.department

Business (Management Science)

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2010

Author dc:creator

• Arnette, Andrew Nicholas

Chair dc:contributor.committeechair

• Zobel, Christopher W.

Committee members dc:contributor.committeemember

• Rakes, Terry R.
• Rees, Loren P.
• Carstensen, Laurence W.
• Ragsdale, Cliff T.

• Geographic Information Systems
• Decision Support System
• Multi-Objective Optimization
• Renewable Energy

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

etd-06292010-152104

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/28159