Siting multiple advanced reactors within a region introduces decision-making challenges that differ from traditional large light-water reactor siting, including (i) the sequential nature of siting multiple reactors with smaller power outputs, where the location of one reactor can influence subsequent choices, and (ii) the presence of larger epistemic uncertainties due to a lack of prior experience. This paper reports on an ongoing exploratory study to evaluate how modeling and simulation techniques from the risk analysis domain can be leveraged to enhance siting selection for advanced reactors.

The authors have reviewed recent studies on siting selection for both light-water reactors and advanced reactors. The results of this literature review identify the state of the art in advanced reactor siting analysis, focusing on two aspects: (i) site selection criteria and (ii) decision analysis frameworks. For site selection criteria, population density and seismic risk are the most commonly considered siting criteria in the literature, while transportation access, connectivity to existing power infrastructure (e.g., replacing coal plants with advanced reactors), and colocation with other industry facilities (e.g., data centers) have been gaining more attention in recent literature. Decision analysis frameworks are categorized into three groups: qualitative, quantitative, and hybrid approaches. Each group is further classified into subcategories to analyze strengths and potential gaps of the existing approaches. One key finding is that existing studies do not explicitly quantify uncertainty in decision metrics and their relative weights. To address this need, uncertainty analysis methods from the PRA domain can be leveraged.

The authors are currently developing a geospatial decision-support platform using ArcGIS to evaluate candidate sites across the Western Pennsylvania region. The analysis incorporates a wide range of criteria, including population density, protected lands, seismic and landslide hazards, fault lines, hazardous operations, floodplains, wetlands, stream power, and slope, which are standardized and combined using a weighted overlay to generate a scored suitability map. Epistemic uncertainties associated with the relative weights of decision criteria and key inputs (such as the distance decay function, which represents distance from the population) are handled by constructing intervals rather than point estimates to represent imprecise knowledge using evidence theory. The impact of these uncertainty intervals on the decision outcome is then assessed through a systematic sensitivity analysis, providing decision-makers with insight into the robustness of the site rankings to uncertain inputs. This work contributes to the methodological foundation for risk-informed siting analysis of advanced reactors, an area that will grow in relevance as deployment of non-LWR technologies accelerates.