Date of Award:
Master of Science (MS)
Mechanical and Aerospace Engineering
Nuclear hybrid energy systems (NHES) are a viable option to combine renewable energy sources, such as wind, with a less fluctuating energy source. Given recent development and their inherent safer and modular design, small modular reactors (SMRs), which are smaller versions of a nuclear reactor, can play an instrumental role in complementing renewables and supporting carbon-free power sectors in the coming decades. With increasing population and demand for clean water, Freeze desalination (FD), which uses freezing to separate water from salt, is a possible way to produce clean water while converting excess power from a SMR into stored thermal energy in an ice water tank. The stored thermal energy can then be used during peak hours to boost the power generation by improving the efficiency of the Rankine cycle of the SMR. Reverse osmosis (RO), which uses membrane and high water pressure to separate water from salt, is another possible way to use excess power generation to efficiently produce clean water.
This paper uses OpenModelica, an open source software package, to model two types of NHES to produce clean energy and water, both powered by SMRs and wind turbines. The first system uses FD and the second system uses RO to generate clean water. RAVEN and TEAL, an economic analysis plugin for RAVEN, are used to optimize both systems for two case locations, Salt Lake City, Utah and San Diego, California.
The results from the two cases show that for water prices less than $1.50 per m3, the FD system would be more economic. Since the RO system produced much more clean water, as water prices rise above $1.50 per m3, it becomes more advantageous to use the RO system, assuming that there are no negative impacts to increased water storage. The FD system is able to use the stored thermal energy to boost the power production by 12% during peak hours by increasing the efficiency of the Rankine cycle by 2%. This allows less capital investment on SMR/wind turbines, as well as less penalty due to mismatch of energy production and demand.
Hills, Stephen Michael, "Modeling, Simulation and Optimization of Nuclear Hybrid Energy Systems Using OpenModelica and RAVEN" (2021). All Graduate Theses and Dissertations. 8063.
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