Studies on Optimal Strategy to Adopt Nuclear Power Plants into Saudi Arabian Energy System Using MESSAGE Tool

Abstract

An optimal long-term electric power strategy for Saudi Arabia to adopt nuclear power was evaluated using the MESSAGE tool. Saudi Arabia is predicted to experience an electricity shortage by 2025 with the present energy system. This electricity shortage could be postponed until 2035 by rehabilitating the existing power plants. The MESSAGE model predicts that adopting a combination of renewable (i.e., solar and wind), advanced traditional power (i.e., gas turbine, steam, and combined cycle), and nuclear technologies is the most competitive future strategy to supply 43.7%, 41.6%, and 3.8%, respectively, of Saudi Arabia’s electricity needs by 2050. This paper proposes an optimal strategy for adopting nuclear power. The nuclear capacity of three scenarios was evaluated: a single APR-1400 nuclear reactor, a single SMART-100 nuclear reactor, and a combination of these two reactors. The results of this study indicate that the highest nuclear capacity was achieved by the combination of the APR-1400 and SMART-100 reactors followed by the single APR-1400 reactor and then the single SMART-100 reactor. However, the single G4ECONS nuclear reactor shows a higher capacity than the single APR-1400 reactor in other evaluated scenarios. The combined reactor strategy may be the most feasible option if the capital cost of a first-of-a-kind SMART-100 reactor is reduced by 62.3%. The cost reductions result from including factors like the time required to build the nuclear power plants in the MESSAGE tool calculation. Also, CO2 taxation will increase nuclear power’s feasibility in the Saudi Arabian energy system. However, the share of renewable energy is predicted to be more affected by the taxation of CO2. In this study, the proposed approach can provide more flexible strategic options for countries embarking on nuclear energy. These flexible strategic options can optimize their national energy mix for long-term planning.