A Multi-Stochastic SMR Siting Model Applied to the Province of Saskatchewan, Canada: Emphasis on Technological Competition and Policy Impacts

Abstract

Existing electric power systems have been being faced with great concerns on climate change mitigation through the reduction of greenhouse gas emissions in recent decades. Small modular reactors (SMRs) are considered the next generation of power technologies, offering stable, safe, and environmental-friendly power. This research initially establishes a multi-stochastic SMR siting model (SSMRS) based on a dynamic mixed-integer left-hand-side chance-constrained multistage programming (DMLCM) method, aiming to provide solid bases for electric power system management to promote GHG mitigation under uncertainties and advance the practical application of SMRs in a regional electric power system. The model is applied to emission-intensive Saskatchewan power systems, which have a high reliance on fossil fuels. The commissioned coal-fired and gas-fired power plants in Saskatchewan are identified as potential sites for employing SMRs. A series of scenarios regarding technical development and carbon policies are analyzed to study the interrelationships among technological competition, policy efficiency, and system-failure risk. This is the first attempt to apply an optimization-based modeling approach for siting SMRs in Saskatchewan with detailed consideration of other new-emerging emission reduction technologies. We found that a carbon tax ranging from 30 to 40$/tonne might be reasonable in Saskatchewan after 2030 while the SMR would be partly commercially viable, occupying ∼>15% of total installed capacity. The solution obtained could provide scientific bases for decision-makers to determine optimal schemes for power supply, capacity expansions, and system costs under environmental targets, and particularly identify construction schemes for SMRs at specific sites in different periods under various risk levels.