Long-term energy system models—including electric sector capacity expansion models—are widely used tools for informing planning, technology assessment, and policy analysis. Recent decarbonization goals and rapid technological change have increased the need to appropriately represent economic characteristics and technical details of energy system resources, including variable renewable energy, energy storage technologies, carbon-capture-equipped capacity, and nuclear energy.
Nuclear power represents about 20% of electricity generation and 50% of carbon-free electricity in the United States as of 2021. However, there are many perspectives on the role of existing and new nuclear in the future U.S. energy system, which is reflected in the broad range of potential contributions reported in the literature.
This project aims to understand how issues central to nuclear energy are represented in long-term energy models. Building on earlier collaborations that focused on variable renewable energy and energy storage, this project convenes four modeling teams that use national-scale long-term energy system models from the Electric Power Research Institute, the National Renewable Energy Laboratory, the U.S. Energy Information Administration, and the U.S. Environmental Protection Agency to share methods and data, update models, run coordinated scenarios, and identify research needs. Improving tools can provide more insightful analyses and ensure that methods are more transparent.
Guided by inter-model comparisons and intra-model scenario analyses, we investigate how model structures and input assumptions impact projections, refine model representations of nuclear energy, and communicate findings to the research community and consumers of modeled scenario results. A greater understanding of model structures, assumptions, parameters, and limitations can improve model capabilities to effectively represent interactions under a variety of market and technology assumptions.
This report synthesizes our collective modeling experience, reviews the literature, and highlights research gaps—which results in recommendations on approaches for representing nuclear energy in long-term energy system models. Such comparisons can identify robust findings and critical assumptions impacting model projections.
Nuclear energy’s role in forward-looking scenarios varies due to differences in scenario assumptions, model structure, and regional characteristics. The scenario design assumptions that have the greatest influence on nuclear deployment are policies and technological cost. Details about a policy’s stringency, timing, and technology eligibility influence decarbonization outcomes and nuclear deployment. Higher shares of nuclear generation occur in scenarios and regions with favorable:
- Policy conditions: Deeper decarbonization targets and restrictions on other low-emitting options (e.g., constraints on carbon removal and carbon capture)
- Regional economic characteristics: Regions with supporting policies as well as lower wind and solar resource quality
- Financial assumptions: Lower nuclear capital costs and lower discount rates
- Combinations of these factors
Nuclear power can complement extensive additions of wind, solar, energy storage, and other resources by providing firm, zero-emissions electricity. The range of nuclear deployment in forward-looking scenarios highlights uncertainty moving forward, but it also stresses the importance of significant nuclear technology advancement and electric sector policies.
Overall, these findings point to the important roles that underlying model structure and input assumptions play in projections for nuclear energy in mitigating climate change and lowering multiple air pollutant emissions. The four participating models have undertaken a variety of nuclear-specific modifications and broader model updates over the course of this project, which have altered model outcomes and improved insights.
Model complexity can strongly impact projected electric sector investments and costs, and many considerations (e.g., parameterization of solar, wind, and storage technologies and temporal resolution) have more significant impacts with deeper decarbonization. Levelized-cost metrics are incomplete for evaluating the relative competitiveness of system resources, which requires detailed energy modeling to assess. The report also identifies several model development priorities and data needs related to nuclear and broader energy systems, including representing hybrid systems that support electric and non-electric applications, capturing integration across systems, linking modeling tools of different resolutions, and several others.
Authors John Bistline, Sowder, A.