Feasibility and benefits of nuclear reactor hybrid energy systems: a remote community case study

Abstract

As Canada transitions to a new clean economy, many Canadian remote communities still rely on fossil fuels to meet their energy needs. Alternative energy solutions are required to make energy more affordable and to reduce environmental impacts. The Hybrid Energy System Optimization (HESO) model has been developed to study the feasibility and benefits of nuclear hybrid energy systems to support energy system planning. The model was formulated as a large-scale linear programming algorithm. By minimizing annual cost, it determines the optimal energy mix, subject to technology limitations and specifications. Different scenarios were analyzed to understand challenges and determine which alternative sources significantly reduced greenhouse gas (GHG) emissions while lowering energy costs. Each scenario considered electricity consumption and energy requirements for space heating, through either electrification or district heating. The scenarios showed that a nuclear-renewable system with diesel to cover peak loads and manage the variability of renewable was found to be the most economical while a nuclear-renewable system with battery storage was less economically competitive due to the high cost of the battery. The results suggested that nuclear and renewable energy had the potential to play a significant role in achieving the net-zero emissions by 2050.