Computational modeling study demonstrates key economic sensitivities in hybrid nuclear systems, indicating cost thresholds for small modular reactor viability.
Given the inherent uncertainty in energy systems, understanding the impact of input parameters on the model’s output is critical in controlling the uncertainty and developing reliable energy systems. This paper addresses the lack of a well-defined framework for conducting global sensitivity analysis in nuclear hybrid energy systems by proposing a practical methodology that considers economic, technical, and operational parameters while tackling challenges in scenario generation and time-series data sampling. The presented framework was applied to a nuclear hybrid energy system optimization model using a case study on an off-grid nuclear hybrid energy system for a research campus. The levelized cost of electricity of the optimal energy system for this case was calculated at 102.99 dollars per megawatt-hour of electricity with 22.42 megawatt capacity of a small modular reactor. The sensitivity analysis highlighted the nuclear capital cost as the most influential parameter in the investigated scenario, with the total-order index value of 0.8. Additionally, when the nuclear capital cost exceeded 6 M $/MW-e, the likelihood of the nuclear being selected in the optimal solution reduced significantly. Furthermore, the proposed global sensitivity analysis framework proved robust in conducting the sensitivity analysis to nuclear hybrid energy systems.
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Tohidi et al. (2026) studied this question.
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