Economic analysis of a nuclear hybrid energy system in a stochastic environment including wind turbines in an electricity grid

Epiney, Aaron; Rabiti, Cristian; Talbot, Paul; Alfonsi, Andrea

doi:10.1016/j.apenergy.2019.114227

Economic analysis of a nuclear hybrid energy system in a stochastic environment including wind turbines in an electricity grid

Journal Article · Tue Dec 10 00:00:00 EST 2019 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2019.114227· OSTI ID:1593858

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Idaho National Lab. (INL), Idaho Falls, ID (United States)

The electricity market in the U.S. is moving toward an energy mix including more variable renewable energy (VRE) sources like wind and solar. This increasing VRE penetration is altering the profile of the net electricity demand. Normally, flexible generators (e.g. gas turbines) are used to absorb fluctuations in the electricity demand. Therefore, an increase in VRE also leads to an increase in installed capacity for such flexible generators which, in turn, may increase the price of electricity. Nuclear-Renewable Hybrid Energy Systems (N-R HES) are seen as a solution to this problem. The N-R HES contains a nuclear power plant electrically and/or thermally linked to an industrial process (IP). This paper demonstrates a new methodology and presents the corresponding RAVEN/Modelica-based software framework to evaluate the financial performance of N-R HES. The novelty of the method is that it explicitly incorporates the stochastic nature of N-R HES inputs such as electricity demand and wind speeds. The method is applied to a generic (rather than region-specific) N-R HES. The analysis shows that under the right market conditions, economic benefits can be achieved by adding a suitable IP to the base-load generator. In particular, there exists an optimal relationship between the IP capacity and the demand. Furthermore, global trends indicate VRE penetration raises the cost of electricity due to the added volatility, an issue only mitigated when operating with high profit margins for the IP.

View Accepted Manuscript (DOE)

Research Organization:: Idaho National Laboratory (INL), Idaho Falls, ID (United States)

Sponsoring Organization:: USDOE; USDOE Office of Nuclear Energy (NE)

Grant/Contract Number:: AC07-05ID14517

OSTI ID:: 1593858

Alternate ID(s):: OSTI ID: 1703582

Report Number(s):: INL/EXT-18-44790-Rev000

Journal Information:: Applied Energy, Journal Name: Applied Energy Journal Issue: C Vol. 260; ISSN 0306-2619

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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