ARKANSAS, Dec 17 (Future Headlines)- The Net-Zero Nuclear Initiative, backed by 22 countries at COP28, signals a global commitment to triple nuclear energy capacity by 2050. This move underscores the growing recognition of nuclear power as a dispatchable, carbon-free energy source crucial for achieving net-zero goals. However, despite increasing support, economic challenges persist, particularly in the context of small modular reactors (SMRs), seen as a solution to cost overruns in large-scale nuclear projects.
As the world pivots towards nuclear energy, there is a need to address the formidable economic barriers associated with nuclear projects, particularly the first-of-a-kind (FOAK) small modular reactor costs. Estimates suggest these costs could range from $6,000 to $8,000 per kilowatt (kW), posing financial risks for companies venturing into this space. To navigate these challenges, Terra Praxis, a nonprofit organization through its REPOWER initiative, is collaborating with Microsoft to explore the potential of artificial intelligence (AI) in expediting the regulatory processes involved in nuclear projects.
Traditional nuclear project licensing follows an extensive and time-consuming process, involving the creation of voluminous documentation, leading to multi-year timelines and substantial costs. Eric Ingersoll, Founding Director and Co-CEO of Terra Praxis, highlights the cost-driving factors, emphasizing the need for large teams to generate and review complex documents. The traditional approach involves hiring expensive experts to produce detailed documents and then employing additional experts to review and validate them.
In response to this challenge, Terra Praxis aims to leverage AI to streamline regulatory processes, reducing time, cost, and risk associated with nuclear projects. Through its partnership with Microsoft, the organization is exploring the application of generative AI to accelerate the drafting of critical documents, such as environmental impact statements. The goal is to provide specific site details to a large language model, facilitating faster and more efficient document preparation.
The potential applications of AI in the nuclear regulatory landscape extend beyond document preparation. Ingersoll envisions a transformative role for AI in the review and verification of license applications. This involves creating a more interactive and collaborative process between developers and regulators, harnessing the power of AI to expedite critical phases of the licensing process.
By introducing AI-driven solutions, developers can navigate the complex regulatory landscape with greater efficiency, allowing for more dynamic interactions and iterative improvements. The shift towards AI-powered regulatory processes could significantly reduce the time required for license approval, potentially achieving a more than 90% acceleration, according to Ingersoll.
Another focus area for Terra Praxis involves automated design using AI. By incorporating rules and smart design systems with built-in regulatory compliance, the organization aims to expedite the path to a compliant design that can undergo human review. This approach holds the potential to revolutionize the design phase of nuclear projects, making them more streamlined, efficient, and aligned with regulatory requirements.
Ingersoll sees AI-driven design automation as a pivotal factor in making large-scale projects, such as repowering coal fleets, more feasible. Leveraging AI in the design phase allows for the creation of standardized and compliant designs, accelerating the transition from concept to implementation.
Terra Praxis’s Repowering Coal solution targets a Levelized Cost of Energy (LCOE) in the range of $35-$40 per megawatt-hour (MWh). This solution aims to repower coal-fired plants with advanced nuclear power, capitalizing on existing coal plant infrastructure. The reuse of infrastructure, including office buildings, electric switchyard components, and transmission infrastructure, is a key aspect that contributes to potential cost savings.
The US Department of Energy (DOE) has previously explored the conversion of hundreds of coal-fired power plant sites to advanced nuclear sources. The reuse of existing infrastructure, coupled with the application of AI in design and regulatory processes, could result in significant capital cost reductions, ranging from 15% to 35% compared to greenfield construction projects.
Terra Praxis envisions its Repowering Coal solution, coupled with AI-driven tools and standardized applications, as a highly profitable investment opportunity. The incorporation of a production tax credit further enhances the economic feasibility, making advanced nuclear power a financially attractive option for repowering coal-fired plants.
As the nuclear energy sector navigates economic challenges and works towards expanding capacity, AI emerges as a transformative force. Terra Praxis’s collaborative efforts with Microsoft showcase the potential of AI in streamlining regulatory processes, expediting project timelines, and enhancing the economic viability of nuclear projects.
The exploration of generative AI for document preparation, coupled with AI-driven design automation, represents a paradigm shift in the nuclear industry. The ability to reduce time, cost, and risk through AI applications paves the way for unlocking the full potential of nuclear energy, especially in the context of small modular reactors.
Editing by Sarah White