Thesis Title: Decision-Making in Climate and Energy Policy

Advisor: Dr. Valerie Thomas

Committee members:

Dr. Marilyn Brown

Dr. David Goldsman

Dr. Matthew Realff

Dr. Joel Sokol

Date and Time: Monday, 3/13/2017, 8:30amCDT

Location: ISYE Groseclose 226A

Abstract:

As many governments at local, state, and national levels seek to lessen their impacts on climate change, carbon dioxide emissions reduction targets are becoming increasingly common. Many of these plans set goals based on a combination of the feasibility and economics of the policies and actions available and the necessary emissions reduction levels identified by the scientific community. 

Due to the intertemporal nature of analyses relating to climate and energy, many cost inputs are more easily ingested as and are more clearly presented as annualized costs. In Chapter II, a formalized methodology for the calculation of the levelized cost of electricity is presented. The levelized cost is widely used as a concise estimate of the cost of electricity generation or comparison between different technologies, incorporating the full lifecycle costs of electricity generation into a unit price over the lifetime of the plant. Several issues persist when these calculations are presented. First, the source and reliability of the cost inputs are often unverifiable if they are based on insider information or models that lack transparency. Second, the method typically involves projection of future fuel costs throughout the projected lifetime of the project. These cost streams are highly uncertain and have a significant effect on the result. Third, single point estimates are frequently used for inputs, which results in point estimates for the levelized cost that do not reflect the wide range of potential costs associated with electricity generation technologies. These issues show a continuing need for a formalized approach for comparing the costs of generation technologies.

In Chapter III, a model is presented to evaluate the cost of meeting carbon dioxide emissions targets using an electricity generation planning model incorporating natural gas and transportation fuels with simultaneous selection of efficiency investments in order to satisfy consumer service levels and policy-makers' desired carbon dioxide emissions targets.  This model bridges the gap between two sets of existing literature. The first set uses scenario-based analysis to generate feasible paths for efficiency in order to meet an emissions target and then calculates the resulting costs.  The second set uses optimization techniques to minimize either costs or emission, thereafter calculating the other metric based on the results. The framework presented herein allows a specific target to be met at minimum cost by allowing the user to define the efficiency portfolios and directly incorporate them into the cost structure of the optimization model. This framework is intended to be tractable and easily extended to specific applications.

In Chapter IV, the model presented in Chapter III is validated by performing a case study on the United States state of Georgia. Considering electricity, natural gas, and transportation fuel emissions, the case study examines three scenarios. The first involves only business-as-usual considerations; the second incorporates efficiency investments; the third adds a carbon dioxide emissions constraint along with the efficiency investments. By analyzing these three scenarios, the study finds that a 40% reduction in carbon dioxide emissions from 2015 levels is achievable by 2050 at present value costs 13% below that of business-as-usual, with the carbon dioxide emissions target itself accounting for costs being 2% above what would otherwise be achieved with efficiency investments alone.

The thesis illustrates a formalized, tractable approach to decision-making in climate and energy policy, while providing the flexibility needed for future work requiring extensions and application to specific contexts. The full source code is provided in order to assist in this endeavor.