Theses and Dissertations Collection

Growing concerns over the impact of fossil fuels on climate change are driving efforts to use more low emission fuel sources. In response, fluctuating renewable energy sources, such as solar and wind power, are growing to meet more of the electric demand. However, maintaining reliable energy accessibility to the grid requires a stable, dispatchable source of power. Nuclear power plants provide low emission, reliable energy to the grid \cite{IPCC}. To best reduce reliance on fossil fuels while ensuring reliable energy generation and profitability, Nuclear Renewable Hybrid Energy Systems (NRHESs) focus on electrically and thermally coupling renewable generation with a nuclear power plant (NPP) by co-locating the generation sources on an industrial park. The industrial park is comprised of at least the NPP, the renewable energy source, and some form of industrial process that consumes the energy not used by the grid. The main question this thesis focuses on is what are the economic and thermodynamic benefits of thermally coupling an industrial process to the nuclear power plant in a NRHES as opposed to electrically coupling. This paper analyzes the computational modeling approaches currently being pursued for NRHES. Initially, the thesis begins by reviewing past research to determine the necessary software capabilities for an NRHES model. Then, with the help of an expert survey and the risk assessment techniques of Preliminary Hazards Analysis and Analytic Hierarchy Process, I determine the best industrial process to couple with a generic NRHES model. I then develop Aspen HYSYS models of a Palo Verde Generating Station reactor coupled to both a thermal multi-stage flash distillation water purification system as well as an electrically coupled reverse osmosis system. To compare the different couplings, I apply an economic exergy analysis to the system. Finally, results and future research are discussed.