James Pelkey
Pronouns: He/Him/His
UROP Fellowship: University of Michigan Energy Institute
Research Mentor(s): Michael Craig, PhD
School for Environment and Sustainability
Presentation Date: Thursday, July 30, 2020 | Session 1 | Presenter: 6
Authors: James Pelkey, Michael Craig
Abstract
Making nuclear power an integral part of our energy future is vital in order to achieve lower carbon emissions, as nuclear is already our nation’s greatest source of carbon-free electricity. Approximately 22 percent of global CO₂ emissions are due to heavy industry. Of this percentage, about 40 percent, or 10 percent of total emissions, is caused by combustion used for high-quality heat. This necessitates the decarbonization of heat sources for industrial processes. Small Modular Reactors (SMRs) have grown in importance in order to create the safest, cleanest, and most affordable power sources in the nuclear energy industry.
A model will be made to optimize SMR design to maximize revenue by analyzing a selection of different SMR designs currently under development, and also will assume the same design and optimize operations in order to maximize the profit of the reactors. This profit-maximizing model utilized data from both electrical grids and heavy industries. For the electrical grid, local marginal prices and ancillary service data from the California Independent System Operator were used. The wet corn milling, paper and pulp, and refining industries were analyzed using the prices of the finished products the industry would make, as well as the thermal and temperature requirements of each industrial heating process the industry used in order to ensure that SMR designs can meet the requirements for the industry.
The model will be run for each industrial facility and power market on an hourly basis for each year of analysis using the hourly data that’s been collected. The constraints of this model will include electricity generation, thermal output, and ancillary service provision to individual and combined minimum and maximum values. There will be several sensitivity analyses ran for each location and year on these given constraints. To generate a net revenues curve, the model will quantify operational net revenues for an SMR at each time step and industrial facility. Integrating net revenues over all time steps, a net revenues curve indicating spatial heterogeneity and a cumulative installed capacity of SMRs will be made.
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Research Disciplines
Environmental Studies, Engineering
