Regulation of Small Modular Reactors (SMRs): Innovative Strategies and Economic Insights

Abstract

The advent of small modular reactors (SMRs) represents a transformative leap in nuclear technology. With their smaller size, modular construction, and safety features, SMRs address challenges faced by traditional reactors. However, these technological advancements pose significant regulatory challenges that must be addressed to ensure their safe and effective integration into the energy grid. This paper presents robust regulatory strategies essential for the deployment of SMRs. We also perform economic and sensitivity analysis on a notional SMR project to assess its feasibility, profitability, and long-term viability, pinpointing areas for cost optimization and determining the project’s resilience to market trends and technological changes. Key findings highlight market demand as the most influential factor, with public acceptance, regulatory clarity, economic viability, and government support playing critical roles. The sensitivity analysis shows that SMRs could account for 3% to 9% of the energy market by 2050, with a base case of 4.5%, emphasizing the need for coordinated efforts among policymakers, industry stakeholders, and regulatory bodies. Technological maturity suggests current designs are viable, with future R&D focusing on market appeal and safety. By synthesizing these insights, the paper aims to guide regulatory authorities in facilitating informed decision-making, policy formulation, and the adoption of SMRs.

1. Introduction

Small modular reactors (SMRs) are revolutionizing nuclear energy by offering significant technological innovations, enhanced safety, and economic feasibility [1] SMRs refer to a category of nuclear reactors with power generation capacities ranging from 10 MWe to 300 Mwe (see Appendix A.1). Reactor designs with power outputs below 10 MWe are typically classified as Micro Modular Reactors (MMRs) [2,3,4]. This classification is significant as it highlights the shift in nuclear technology towards more manageable and scalable solutions. Figure 1 gives an overview of the benefits of SMRs. Unlike traditional reactors, SMRs feature modular designs that enable reductions in construction time and costs, enable incremental capacity additions, and ensure higher quality control, leading to lower maintenance and operational costs over the reactor’s lifecycle [5]. Advanced passive safety systems, which rely on natural physical principles like gravity and convection, further distinguish SMRs by maintaining safe conditions without active controls or human intervention, significantly reducing the risk of accidents. Technological advancements in SMR designs, such as the use of novel coolants and advanced control systems, push the boundaries of efficiency and safety, exemplified by designs like the GE Hitachi BWRX-300 (Wilmington, NC, USA) and the NuScale Power Module (Tigard, OR, USA). Environmentally, SMRs offer benefits such as a smaller physical footprint, the potential for deployment in remote locations, and the exploration of innovative fuel cycles like thorium-based and mixed-oxide fuels, which enhance fuel utilization and reduce nuclear waste. Regulatory considerations are crucial for the successful deployment of SMRs, with regulatory authorities playing a pivotal role in developing streamlined licensing processes and supporting pilot projects [6].

This paper presents a comprehensive review of the global SMR landscape, focusing on key aspects such as licensing and regulation, grid integration, and economic considerations. Drawing from global SMR initiatives and lessons learned, it offers innovative regulatory strategies, an implementation roadmap, and detailed economic and sensitivity analyses. These insights and recommendations are designed to help the regulatory authorities effectively regulate and facilitate the integration of SMRs into the global energy landscape, supporting the transition to a sustainable and resilient energy future.

Comparative Analysis: SMRs Versus Large Nuclear Reactors

While SMRs offer promising advantages for nuclear power generation, regulatory authorities must carefully consider their challenges and limitations compared to traditional large reactors. This section examines key trade-offs to inform balanced decision-making across technical, economic, regulatory, and market dimensions.

The fundamental economic tension between SMRs and large reactors centers on the trade-off between economies of scale and modularity benefits. Large reactors have traditionally benefited from economies of scale, achieving lower costs per MW through size optimization [7]. SMRs attempt to counter this disadvantage through modular manufacturing, standardization, and learning effects from serial production, though these benefits remain largely theoretical until significant production volumes are achieved [4,8].

In terms of safety and operational considerations, SMRs and large reactors present distinct profiles. SMRs feature enhanced passive safety systems and smaller radioactive inventories, potentially reducing accidents’ consequences [9]. However, while large reactors benefit from decades of operational experience and well-understood safety protocols, SMRs introduce new challenges in multi-module operations and shared systems oversight that require careful regulatory consideration [10,11].

The economic comparison extends beyond simple capital costs. While SMRs require lower initial capital investment, enabling broader market participation, their cost per MW initially remains higher compared to that of large reactors [12,13]. Operating costs present a similar dichotomy: large reactors achieve lower operating costs per MWh through economies of scale, but SMRs offer potential advantages through optimized maintenance scheduling and reduced downtime in multi-unit configurations [14,15].

Regulatory challenges represent a critical area of distinction. Novel SMR designs require extensive review and validation, with limited operational experience creating uncertainty in safety assessments [16,17]. Multi-module configurations introduce new regulatory considerations that traditional frameworks may not adequately address. Emergency planning presents challenges, as SMRs may justify smaller emergency planning zones while requiring new approaches for multi-unit sites and distributed deployment scenarios [18,19].

Infrastructure and grid integration considerations reveal both advantages and challenges for SMRs. While large reactors typically require substantial grid infrastructure, SMRs offer better compatibility with smaller grids and remote locations [20,21]. However, multiple SMR units increase the complexity of grid connections and control systems, requiring careful technical and regulatory [22]. Site selection and environmental impact assessments must also consider the cumulative effects of multiple units, even though individual SMR units have smaller footprints [23,24].

While SMRs potentially offer shorter construction times and earlier revenue generation, one-of-a-kind projects face uncertain timelines and regulatory approval processes that may extend deployment schedules [25,26]. Market dynamics and deployment challenges may also add further complexity. While SMRs seek to capitalize on the benefits of factory production, they require substantial upfront investment in manufacturing facilities.

These comparisons have significant implications for regulatory decision-making. Regulatory authorities must develop frameworks that are both flexible enough to accommodate SMR innovations and robust enough to ensure public safety. This includes establishing clear criteria for evaluating safety cases with limited operational experience, creating efficient processes for multi-unit licensing, and adapting emergency planning requirements based on SMR-specific risk profiles [27,28]. The experience gained from existing nuclear power plants provides valuable insights, but new frameworks must be adaptable to address the unique characteristics of SMR deployment [29,30].

2. Literature Review

2.1. SMR Development and Grid Integration

Navigating the complexities of integrating SMRs into existing energy grids is a critical step in realizing their potential as a key component of the future energy mix. SMRs offer distinct advantages in terms of development and grid integration due to their smaller size, modularity, and operational flexibility. These reactors can be deployed incrementally, allowing for a more scalable approach to energy production that aligns with growing demand [31]. Moreover, their ability to operate at variable output levels makes them well suited for complementing intermittent renewable energy sources like wind and solar. This flexibility is crucial for maintaining grid stability, as SMRs can quickly ramp up production when renewable generation drops, providing a reliable backup without the need for fossil fuels.

SMRs’ ability to quickly ramp up production is facilitated by several factors, including the following: (i) Modular construction allows for factory prefabrication of components, which are then transported to the site. These components can either arrive fully functional and ready to be plugged in for immediate use or require on-site assembly. (ii) Scalability ensures additional modules can be added incrementally, offering a flexible investment approach. (iii) Design simplification reduces installation and testing time. (iv) Advanced technologies like passive safety systems decrease operational complexity. (v) Streamlined regulatory approvals are possible due to standardized and safe designs. (vi) Site flexibility enables rapid construction in diverse locations, collectively enhancing responsiveness and efficiency in nuclear power generation [31]. Despite the promising aspects of SMRs, research such as that by [8] highlights financial challenges, noting that the economic viability of SMRs in competitive markets remains uncertain due to high initial capital costs and the financial risks associated with new nuclear technologies [13].

As previously mentioned, ’modularity’ in the context of SMRs commonly refers to SMR components being fabricated off-site in a controlled factory setting, enabling faster, more reliable assembly on-site, similar to ’plug-and-play’ equipment [32]. This methodology significantly reduces on-site construction risks and timelines. Furthermore, SMRs can be differentiated by their fuel types and reactor technologies: from those using Low-Enriched Uranium (LEU) to High-Assay Low-Enriched Uranium (HALEU), and from traditional light-water reactors to advanced designs like Gas-cooled Fast Reactors (GFRs) and Molten Salt Reactors (MSFRs) [8,33]. Each of these distinctions influences the design, safety, regulatory, and economic factors that are critical to the adoption and success of SMR technologies. The development of SMRs also involves addressing challenges such as regulatory approvals, supply chain readiness, and the harmonization of standards across regions to ensure safe and efficient deployment. As SMRs move from conceptual design to commercial reality, their successful integration into the grid will depend on strategic planning, robust infrastructure, and adaptive regulatory frameworks that support their unique characteristics. By overcoming these challenges, SMRs have the potential to transform the energy landscape, contributing to a more resilient, low-carbon energy future [34].

2.2. Economic Imperatives

In addition to technological factors, the economic competitiveness of SMRs is crucial for their development and integration [7]. To gain market traction, SMRs must be cost-competitive with other energy solutions, driven by market demand for carbon-free electricity. Nuclear power, as a dispatchable, carbon-free source, will be pivotal in achieving deep decarbonization alongside renewable energy by providing flexible, reliable baseload power [15].

Economically, SMRs offer several advantages and disadvantages as seen in

Table 1. Advantages and disadvantages of the features of SMR modularization.

Features	Advantages	Disadvantages
Factory fabrication	✓ Enables efficient shipping and on-site assembly. ✓ Allows for simultaneous testing during fabrication and assembly, leading to reduced construction time and lower overall construction costs.	× Can lead to higher transportation costs. × Deploying SMRs to different locations may involve navigating varied regulatory environments, leading to potential delays and additional compliance costs.
Standardization	✓ Ensures consistent quality and minimizes defects. ✓ Allows for learning economies.	× Can lead to innovation constraints.
Scalability	✓ Can be scaled up to the minimum or maximum number of modules required.	× Although the upfront investment for a single SMR unit is lower, incremental expansion may lead to higher overall capital cost. × SMRs may not benefit from the same economies of scale, leading to higher Levelized Cost of Electricity (LCOE) per MW compared to large reactors.
Degree of modularization	✓ The higher the degree, the more costs can be reduced.	× Disruptions in the supply chain, shortages of specialized materials, transportation bottlenecks, or limited qualified manufacturers can significantly impact project timelines and costs.
Design simplification	✓ Allows for simplified plant layout and components. ✓ Lower costs associated with rework, leading to reduced construction costs and downtime.	× Oversimplification may lead to potential performance trade-offs and limit efficient optimization.
Harmonization	✓ Access to a global market fostering series-production economies. ✓ Unified codes and specifications resulting in lower integration costs.	× May pose regulatory challenges.
Flexibility	✓ Supports applications beyond electricity generation, including desalination, district heating, and industrial processes. ✓ Can provide siting flexibility for locations that cannot accommodate large reactors. ✓ Attractive replacement for aging fossil plants or to complement industrial processes or renewable generation.	× Each application may require additional licensing and approvals, delaying deployment.

. They feature lower upfront capital costs due to factory-based construction, reduced construction schedules, and modular designs that allow for phased investments, reducing financial risks [4]. Furthermore, governments benefit from job creation, economic growth, and energy security, with opportunities for export and local development [35]. SMRs are also ideal for remote areas, offering competitive energy prices and self-sufficient power systems [12].

As seen in Figure 2, larger reactors were developed to leverage economies of scale, but SMRs can overcome these diseconomies through modularization, enhancing quality and cost efficiency while reducing on-site safety requirements [14]. The modular approach allows for learning economies and scalability, making SMRs attractive for diverse applications such as industrial processes, desalination, and hydrogen production [3,7]. Another key advantage of SMRs is their lower absolute dollar risk for construction; for instance, a USD 4 B SMR with a 50% cost over-run results in a USD 6 B first-of-a-kind (FOAK) cost, whereas a USD 10 B large reactor with the same over-run would escalate to USD 15 B. This lower upfront capital requirement allows for cost-saving learning in subsequent units and reduces barriers to entry for potential customers who cannot commit to USD 6 B+ investments [36].

SMRs’ competitiveness is primarily evaluated through Levelized Cost of Electricity (LCOE), with capital costs forming a significant portion of these costs [4,13]. Despite higher first-of-a-kind (FOAK) costs, SMRs are economically viable for certain customers, such as smaller retiring coal plants and supporting industrial processes requiring high-temperature heat, due to their affordability, smaller capacities, and suitability for off-grid locations [14,36].

Government investment is key to lowering SMR costs and unlocking their potential to ensure SMRs’ viability; utilities should act quickly in licensing and site selection or at least keep their options open for future deployment. Building expertise and continuously monitoring SMR advancements will help utilities align with future energy needs [37].

2.3. Licensing, Regulatory Challenges, and Opportunities

Effective licensing and regulatory frameworks are essential for SMR adoption, but the novelty of SMR technology, diverse designs, and limited operational experience complicate standardization (Appendix A.2) [10,27,28]. Ref. [16] classify SMR regulatory issues into barriers (long-term, such as regulatory fragmentation and technological novelty) and challenges (short-term, such as high fees and prolonged licensing durations). Opportunities exist to streamline SMR licensing. International interest is growing, with countries like the U.S. and the UK investing in SMR programs and FOAK units [17]. The U.S. Department of Energy supports SMR companies through cost-sharing and access to national labs, while Canada and Finland are developing supportive policy frameworks. The International Atomic Energy Agency (IAEA) fosters SMR development by promoting collaboration to harmonize licensing, with the IAEA SMR Regulators’ Forum (SMR-RF) contributing valuable insights [18]. A balanced approach—standardizing safety requirements while considering site-specific factors—is necessary. For example, the U.S. Nuclear Regulatory Commission’s (NRC) early site permit (ESP) process addresses site-specific issues before finalizing reactor designs. As SMRs evolve, regulators must balance innovation with public safety through flexible frameworks that adapt to new technologies while maintaining rigorous standards. Global collaboration will be crucial for addressing challenges and leveraging opportunities for SMR deployment.

2.4. Environmental Considerations and Waste Management

2.4.1. Life Cycle Assessment (LCA)

LCA evaluates the environmental impact of SMRs across all stages, including resource extraction, manufacturing, transportation, construction, operation, decommissioning, and waste management. Studies have shown that SMRs can achieve lower environmental impacts per unit of electricity compared to traditional large reactors through several specific mechanisms. Ref. [23] demonstrated this advantage through an analysis of multiple factors: improved resource efficiency due to optimized manufacturing processes in factory settings, reduced construction material requirements per MW of capacity due to modular design and standardization, enhanced capacity factors enabled by shorter refueling outages and staggered maintenance schedules in multi-module plants, and decreased land use intensity and site disruption during construction. Additionally, advanced SMR designs incorporate features that can reduce nuclear waste generation per kWh, such as higher burnup fuels and improved neutron efficiency [24]. For example, some SMR designs achieve burnup rates of up to 60–70 GWd/MTU compared to 45–50 GWd/MTU in traditional reactors, resulting in more efficient fuel utilization and less waste per unit of energy produced [38]. Environmental profiles vary based on design features like coolant type, fuel enrichment, and site-specific factors.

2.4.2. Advanced Fuel Cycles: Implications for Waste Management

Advanced fuel cycles in SMRs offer benefits like waste reduction and extended fuel cycles but introduce challenges. Fast neutron reactors can reduce high-level waste by using spent fuel [39]. However, advanced cycles may produce waste with different radioisotopes, requiring new treatment approaches. On-site fuel recycling could reduce transportation but raises proliferation risks. Ref. [40] emphasize evaluating the entire nuclear fuel cycle, from front-end processes to back-end waste management.

2.4.3. Decommissioning in the Age of Modularity: New Approaches and Challenges

SMRs’ modularity presents both advantages and challenges for decommissioning. Advantages include smaller size, standardization, and modular components [7]. Challenges involve multi-unit sites, new technologies, and adapting regulatory frameworks [32] Innovative concepts like whole-module removal and advanced robotics may simplify decommissioning. Economic considerations and long-term planning are critical, with potential for standardized procedures across SMR fleets. Effective knowledge management will support future decommissioning efforts.

2.5. Security and Non-Proliferation

2.5.1. Cybersecurity for Digital SMRs: A Critical Challenge

The digitalization of SMRs introduces significant cybersecurity risks. Ref. [41] emphasize that while digital control systems enhance efficiency, they also increase vulnerabilities to cyber threats. Key challenges include the following:

• Increased attack surface: Digital systems expand potential entry points for cyberattacks [42].
• Supply chain security: Ensuring the integrity of complex supplier networks is crucial, as compromised components could introduce [43].
• Remote monitoring and control: Features for remote operation may be exploited by malicious actors if not properly secured [44].
• Evolving threat landscape: The nuclear sector requires adaptive cybersecurity strategies to address constantly evolving threats [45].

To mitigate these risks, the industry is implementing robust cybersecurity frameworks, including encryption, intrusion detection, training programs, and regular vulnerability assessments [46].

2.5.2. Physical Protection Strategies for Distributed SMR Deployment

The distributed nature of SMR deployment presents unique physical protection challenges. Unlike large nuclear plants, SMRs may be deployed in diverse and potentially remote locations [33]. Key considerations include the following:

• Perimeter security: Adapting physical barriers and surveillance systems for varied deployment scenarios [47].
• Insider threats: Implementing personnel reliability programs and access controls to mitigate insider risks [48].
• Transportation security: Securing the transport of fuel, components, and reactor modules [49].
• Emergency response: Coordinating with local law enforcement and emergency services for effective response [50].

Innovative approaches involve advanced sensors, AI-driven surveillance, modular security infrastructure, tamper-evident designs, and biometric access systems [51].

2.5.3. Safeguards by Design: Integrating Non-Proliferation into SMR Development

“Safeguards by Design” (SBD) integrates nuclear safeguards and non-proliferation measures into reactor design [52]. For SMRs, key aspects include the following:

• Material accountancy: Designing systems for easy monitoring and verification of nuclear material [53].
• Containment and surveillance: Simplifying the application of containment and surveillance by inspectors [54].
• Remote monitoring: Developing secure systems for remote transmission of safeguarding data [55].
• Proliferation resistance: Incorporating features like long-life cores or low-enriched fuel to enhance proliferation resistance [56].

SBD measures for SMRs include advanced sealing technologies, real-time monitoring, design features that limit access to sensitive areas, and standardized interfaces for inspection equipment [57]. Collaboration between industry, regulators, and international bodies is essential to ensure effective implementation [58].

2.6. Global SMR Initiatives: Lessons and Insights

2.6.1. United States

The United States, a leader in SMR development, actively participates in international forums such as the IAEA, NEA, and INRA [59]. The US Nuclear Regulatory Commission (NRC) oversees SMR licensing, ensuring adherence to safety and environmental standards. In 2023, the NRC introduced Title 10 CFR Part 53, focusing on advanced reactor licensing. This rule offers two pathways: Framework A uses a Probabilistic Risk Assessment (PRA), while Framework B employs a deterministic method with an alternative evaluation for risk insights (AERI), bypassing PRA in specific cases. The rule aims to accommodate diverse reactor technologies while maintaining safety and practicality [60]. Other regulatory efforts include the Advanced Nuclear Reactor Generic Environmental Impact Statement (ANR GEIS), currently proposed, and finalized Emergency Preparedness Requirements for SMRs, effective December 2023 [61]. These initiatives establish comprehensive frameworks for the licensing, manufacturing, construction, and operation of various reactor designs, including LWR, non-LWR, and non-power reactors.

Case Study: NuScale Power US600

The NuScale US600 SMR, a pressurized-water reactor by NuScale Power, LLC, received Standard Design Approval in 2020 after a five-year review [60]. Pre-application reviews began in 2008, aligning with NRC’s policy of early engagement with applicants to provide guidance and address issues before formal submission [62]. NuScale’s design is the first and only SMR licensed in the US, intended for deployment in a six-reactor plant at Idaho National Laboratory. However, the project was terminated in November 2023 due to rising costs and limited interest from Utah power providers [63]. NuScale’s project experienced significant cost escalations due to design modifications and underestimated expenses. Initially, in 2015, the plan involved constructing 12 reactor modules to generate 600 MW, with an estimated cost of USD 3 billion. In 2018, NuScale increased each module’s capacity to 60 MW, aiming for a total output of 720 MW, and projected a reduction in cost per kilowatt from USD 5000 to approximately USD 4200. However, by 2021, the overall capacity was reduced to 462 MW due to rising costs. Consequently, the estimated costs escalated to USD 4.2 billion in 2018, USD 6.1 billion in 2020, and, ultimately, USD 9.3 billion in 2023. These frequent design changes introduced technical uncertainties, and the economic models employed failed to account for additional risk factors, leading to significant budget over-runs [27]. This case underscores the necessity for rigorous cost assessments and transparent economic modeling in nuclear projects. Stakeholders should incorporate contingencies for design changes and potential delays. A study by [64] analyzing 180 nuclear power projects worldwide found that 175 exceeded their initial budgets by an average of 117% and experienced delays averaging 64%. Detailed risk analyses and realistic forecasting are essential to mitigate such challenges in future projects.

A 2022 NRC report outlined lessons learned from the NuScale licensing process.

• Best Practices for Future SMR Applications:
• Early Pre-Application Engagement: Early interaction allowed NRC to familiarize itself with the design and resolve issues pre-emptively.
• Focus on Highly Challenging Issues (HCIs): Early identification and resolution of HCIs led to efficient processing.
• Streamlined Safety Evaluation Report: A focused approach on critical safety issues provided a clearer regulatory basis.

2.6.2. Canada

Canada is advancing SMR development through the Canadian SMR Roadmap, focusing on regulatory readiness, public engagement, and partnerships. The GE Hitachi BWRX-300 project at Ontario Power Generation’s Darlington Nuclear Generating Station, Canada’s first grid-scale SMR, is designed for economic competitiveness, safety, and rapid deployment [5].

The Canadian Nuclear Safety Commission (CNSC) is streamlining the SMR licensing process by engaging early with developers, positioning Canada as a leader in global SMR development. The Pan-Canadian SMR Action Plan, launched in 2020, promotes SMR growth through a collaborative framework addressing regulatory frameworks, waste management, and public engagement, resulting in provincial commitments and increased private investment [65,66,67,68].

The Vendor Design Review (VDR) process, managed by the CNSC, reduces uncertainty for SMR developers and attracts international vendors to Canada [69]. The Darlington project, scheduled for 2028, tests Canada’s regulatory framework, offering operational experience and market validation [70,71].

Canada’s SMR strategy extends globally, participating in international initiatives and adhering to stringent safety protocols, establishing the country as a leader in next-generation nuclear power [72].

2.6.3. United Kingdom (UK)

The UK views small modular reactors (SMRs) as crucial to achieving net-zero carbon emissions by 2050, recognizing their potential for clean, reliable baseload power [73].

The UK’s Generic Design Assessment (GDA) has been adapted to accommodate the unique characteristics of SMRs:

• Streamlined Process: The Office for Nuclear Regulation (ONR) and Environment Agency now use a flexible, stepwise approach for earlier regulatory feedback [74].
• Increased Efficiency: The adapted GDA reduces assessment time and resources while maintaining safety standards [75].
• International Alignment: Bilateral agreements, such as with the Canadian Nuclear Safety Commission, harmonize SMR regulatory approaches [76].

These changes are expected to speed up SMR approval and reduce time to market [77]. In addition, the UK promotes Public–Private partnerships in SMR development through the following:

• Advanced Nuclear Fund: A GBP 385 million fund supports SMRs and Advanced Modular Reactors, underscoring the commitment to nuclear innovation [78].
• UK SMR Consortium: Led by Rolls-Royce, this consortium includes industry, academia, and government to develop a UK SMR design [79].
• Regulatory Engagement: Early developer–regulator interactions address potential challenges proactively [80].

These partnerships mobilize expertise and investment while aligning with energy policy objectives [81].

Case Study: Rolls-Royce SMR—From Concept to Commercialization. The Rolls-Royce SMR project illustrates the UK’s SMR approach:

• Design Philosophy: The design uses UK nuclear supply chain capabilities and modularity to cut costs and construction times [82].
• Government Support: The project received GBP 210 million in government funding, matched by private investment [80].
• Regulatory Progress: Rolls-Royce SMR entered the GDA process in 2021, testing the new regulatory framework [83].
• Market Potential: The design has domestic and export opportunities, with potential UK sites under consideration [84].
• Job Creation: The project could create up to 40,000 jobs, highlighting economic benefits [77].

The Rolls-Royce SMR project demonstrates the UK’s integrated SMR development approach, combining innovation, regulatory adaptation, and government support. The UK’s SMR strategy, incorporating public–private partnerships and regulatory adaptations, aims to advance SMR technology, enhancing domestic energy security and international exports.

2.6.4. China

China’s nuclear energy sector is expanding rapidly, with a total nuclear power plant (NPP) capacity of approximately 40 GW(e) in 2020 and an additional 18% under construction [85]. The country is a leader in the development of small modular reactors (SMRs), a movement that began in 1970 and has led to significant advancements in the nuclear industry [86]. China’s High-Temperature Gas-Cooled Reactor Pebble Bed Module (HTR-PM) is a major milestone as one of the world’s first commercial SMR designs approaching operating status [87]. Various SMR designs are being developed by Chinese companies, including HTR-200 and ACP100, created by Tsinghua University and the China National Nuclear Corporation, respectively. Additionally, China is advancing its nuclear capabilities with a new generation of pressurized-water reactors (PWRs) [85].

In China, the demand for small modular reactors (SMRs) is primarily driven by their applications in supplying electricity to small grids, providing process and district heating, and desalinating seawater [85]. China uses their own reactor designs, and this plays a key role in their energy security. Although China’s energy imports are expected to rise in the short term, it is expected to reduce its dependency on energy imports through further growth in domestic capabilities in renewable energy and nuclear power [22]. By 2030, China’s share of electricity from nuclear energy in its energy mix is expected to rise from 4% in 2022 to 10% and reach 20% by 2050 [22]. In the near future, China is projected to remain a major player in the SMR market.

2.6.5. Russia

Russia is advancing its nuclear energy agenda with plans to expand its role in the energy sector, including the development of new reactor technologies [86]. In the area of SMRs, Russia is enhancing its capabilities to deliver reliable energy to small regional systems in remote, hard-to-reach areas. These areas, particularly in the eastern and northern parts of the country, experience extremely low temperatures and have sparse populations [88]. Russia operates 11 nuclear power plants with a total of 37 power units. These units collectively have an installed capacity exceeding 29.5 GW, contributing to approximately 20% of the country’s total electricity generation [89]. Today, in 2022, Rosatom operates the world’s only floating nuclear power plants based on a floating power unit, Akademik Lomonosov, with two 35 MWe KLT-50 unit (70 MW total) reactors [86]. Some analysts believe that Russian energy companies primarily aim to focus on European markets by constructing new export pipelines supported by long-term contracts and extending loans on the international market to support these ventures [22]. However, despite being a leading manufacturer of nuclear reactors, Russia’s invasion of Ukraine and the attacks on nuclear power plants have cast doubt on whether other countries will continue to import nuclear technology from Russia [86].

2.6.6. Korea

Korea is another key player to keep an eye on in the international nuclear reactor market, particularly with the anticipated shift in government policy towards nuclear energy following the election of President Yoon Seok-youl. While Korea has had only one international customer for its reactor technology—the Barakah Nuclear Power Plant in the UAE—the new administration seems to be promoting both a revival of domestic nuclear energy use and an expansion of nuclear reactor exports. The reactor Korea is exporting is KEPCO’s APR-1400, a pressurized-water reactor (PWR) with a capacity ranging from 1000 MW to 1400 MW and a lifespan of 40 to 60 years [22]. In March 2015, the Korea Atomic Energy Research Institute (KAERI) signed a memorandum of understanding (MOU) with King Abdullah City for Atomic and Renewable Energy (KA-CARE) to assess the potential for building two SMART reactors in Saudi Arabia [1]. Other Emerging SMR Markets include Japan, Argentina, India, and the Philippines. A regulatory framework comparison matrix of SMRs has also been included in Appendix B.

3. Materials and Methods

The analysis in this report is based on a thorough and meticulous review of scientific literature, industry reports, and regulatory documents, encompassing a wide array of sources to ensure comprehensive coverage. Data from recent SMR projects and pilot programs have been meticulously integrated, providing a holistic and up-to-date view of the current state of SMR technology. This includes an examination of various SMR designs, their operational performance, and safety records, ensuring that the analysis is grounded in real-world applications and experiences. To further enrich the analysis, we provide recommendations on innovative regulatory strategies and a structured implementation roadmap to facilitate a smooth transition, minimize disruptions, and maximize the benefits of SMRs.

Finally, we perform a detailed economic and sensitivity analysis. The economic analysis of an SMR project assesses its feasibility, profitability, and long-term viability by evaluating key drivers like capital and operational costs. It models various scenarios to identify financial risks, cost-effectiveness, and potential returns on investment. A sensitivity analysis examines SMR adoption rates in the global energy market from 2020 to 2050, identifying critical drivers such as market demand, public perception, and regulatory frameworks. This integrated approach ensures robust insights into SMR deployment, providing actionable recommendations for stakeholders to optimize adoption and implementation strategies.

3.1. Data Sources and Collection

Our analysis draws from multiple data sources to ensure comprehensive coverage and reliability. Primary data sources include industry reports and technical documentation from organizations such as the [11,17,90] and the International Atomic Energy Agency (IAEA). We also incorporate industry-specific cost and performance data of SMRs and regulatory filings. Academic sources include peer-reviewed journal articles on SMR economics and technology, complemented by market data from existing nuclear projects and energy market projections.

3.2. Data Processing and Validation

Data validation involved cross-verification of values across multiple sources and expert consultation for anomalous data points. This rigorous approach to data processing enhances the reliability of our analysis and provides a solid foundation for our economic and sensitivity analyses.

3.3. Economic Analysis

As stated earlier, the LCOE is a crucial parameter in determining the competitiveness of an SMR project. It indicates the minimum electricity price required for the project’s revenue to sufficiently meet all operational costs, both fixed and variable, recover the capital invested during construction and decommissioning (along with associated direct costs and interest expenses), and offer a fair return to investors, compensating for the risks involved in the project. For our LCOE model, we use equation 1 as defined by [25].

$$\mathrm{L}\mathrm{C}\mathrm{O}\mathrm{E}={\displaystyle \frac{{\sum }_{\mathrm{y}=0}^{\mathrm{n}}\mathrm{D}\mathrm{i}\mathrm{s}\mathrm{c}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{A}\mathrm{n}\mathrm{n}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{C}\mathrm{o}\mathrm{s}\mathrm{t}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h}\mathrm{F}\mathrm{l}\mathrm{o}\mathrm{w}}{{\sum }_{\mathrm{y}=0}^{\mathrm{n}}\mathrm{D}\mathrm{i}\mathrm{s}\mathrm{c}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{A}\mathrm{n}\mathrm{n}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{E}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y}}}$$

(1)

where n = project period, y = year, and the LCOE is expressed in USD/MWh or c/kWh.

For this analysis, we consider an SMR with a capacity of 300 MWe, which aligns with current commercial designs such as the GE Hitachi BWRX-300 [5]. A critical consideration in SMR cost estimation is the distinction between first-of-a-kind (FOAK) and nth-of-a-kind (NOAK) costs. FOAK costs include additional expenses associated with initial design, licensing, testing, and manufacturing setup, while NOAK costs reflect the benefits of learning effects and economies of series production. Following [25], we account for this progression through a learning rate factor given in Equation (2):

$$\mathrm{N}\mathrm{O}\mathrm{A}{\mathrm{K}}_{\mathrm{C}\mathrm{o}\mathrm{s}\mathrm{t}}=\mathrm{F}\mathrm{O}\mathrm{A}{\mathrm{K}}_{\mathrm{C}\mathrm{o}\mathrm{s}\mathrm{t}}\times {\left(1-\mathrm{L}\mathrm{R}\right)}^{\mathrm{n}-1}$$

(2)

where LR represents the learning rate (typically 5–10% for nuclear components), and n is the nth unit in the series. For our analysis, we use conservative learning rates based on historical nuclear industry data: 5% for nuclear-specific components and 8% for conventional elements. This approach allows us to model cost reductions as production volumes increase, reflecting the transition from FOAK to NOAK economics. We estimate that NOAK costs could be 20–30% lower than FOAK costs based on manufacturing learning curves, standardization benefits, and supply chain optimization [8].

Assumptions

The following economic assumptions are made for the inputs detailed in

Table 2. Summary of SMR data assumptions required for economic model in 2020 dollars.

Category	Parameter	FOAK Values	NOAK Values
Capital Costs	Overnight Capital Cost (OCC)	USD 3800/kWe	USD 1198/kWe
	Licensing Cost	USD 40 M	USD 28 M
	Decommissioning Costs (At the end of Year 60)	USD 50 M	USD 50 M
Operating Costs	Fixed and Variable O & M Cost	USD 22/MWh	USD 18/MWh
	Fuel Cost	USD 8/MWh	USD 7/MWh
	Insurance	0.5% of CAPEX	0.5% of CAPEX
Timelines	Construction Period (No revenue generation)	3 years	2.5 years
	Operational Life	60 years	60 years
Operational Parameters	Capacity	300 MWe	300 MWe
	Capacity Factor	90%	92%
Revenue Assumptions	Electricity Price	USD 50/MWh	USD 50/MWh
	Annual Electricity Generation	2,365,200 MWh/year	2,416,320 MWh/year
	Nominal Discount Rate (r)	5.5%	5.5%

. The table incorporates documented sources and methodologies to ensure transparency and rigor in the economic model presented, thereby aligning the theoretical assumptions with practical economic analysis frameworks.

• The SMR operating parameters, timelines, and FOAK values for capital and operating costs were obtained from the report [14], which presents an optimistic outlook and is representative of estimated costs and expected performance.
• We assume that the primary use of the SMRs will be electricity generation and, as such, a wholesale electricity price of USD 50/MWh is selected.
• The assumed electricity price is based on data provided by the [91], which reports that the average wholesale electricity price across the major trading hubs in the U.S. in 2020 ranged from USD 22/MWh to USD 77/MWh. The chosen price of USD 50/MWh is approximately the midpoint of this range, making it a reasonable estimate.
• We also assume the insurance cost to be 0.05% of the OCC.
• In our analysis, we do not factor in additional regulatory costs, taxes, or government support mechanisms and incentives, such as production tax credits, investment tax credits, or other similar financial support mechanisms.

Another useful economic assessment tool for assessing a project’s competitiveness is the Net Present Value (NPV). The NPV calculates the present value of all expected future cash flows (both incoming and outgoing) associated with the SMR project. The formula for NPV used in this study is given by Equation (3).

$$\mathrm{N}\mathrm{P}\mathrm{V}=\Sigma \left({\displaystyle \frac{{\mathrm{C}}_{\mathrm{t}}}{{\left(1+\mathrm{r}\right)}^{\mathrm{y}}}}\right)-{\mathrm{C}}_0$$

(3)

In this context, C_t represents the net cash flow for year t, while r denotes the discount rate applied to the project. The variable y corresponds to each specific year, ranging from 0 to the end of the project’s lifespan. Meanwhile, C₀ stands for the initial capital investment required at the project’s start.

The Internal Rate of Return (IRR) is a measure of the profitability of an investment over its entire duration. It is calculated by finding the discount rate at which the Net Present Value (NPV) of the project equals zero. A project is typically considered viable if its IRR exceeds the discount rate. It is typically given in %.

$$\mathrm{N}\mathrm{P}\mathrm{V}=\sum _{\mathrm{y}=0}^{\mathrm{n}}\left({\displaystyle \frac{{\mathrm{C}}_{\mathrm{t}}}{{\left(1+\mathrm{I}\mathrm{R}\mathrm{R}\right)}^{\mathrm{y}}}}\right)-{\mathrm{C}}_0=0$$

(4)

Finally, we calculate the payback period, which is used to determine the time it will take to recover the initial cost associated with our SMR project. It is typically given by Equation (5).

$$\mathrm{P}\mathrm{a}\mathrm{y}\mathrm{b}\mathrm{a}\mathrm{c}\mathrm{k}\mathrm{P}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{o}\mathrm{d}={\displaystyle \frac{\mathrm{C}\mathrm{o}\mathrm{s}\mathrm{t}\mathrm{o}\mathrm{f}\mathrm{I}\mathrm{n}\mathrm{v}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}}{\mathrm{A}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}\mathrm{A}\mathrm{n}\mathrm{n}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h}\mathrm{F}\mathrm{l}\mathrm{o}\mathrm{w}}}$$

(5)

3.4. Sensitivity Analysis—Technology Adoption Rate

This section presents a detailed sensitivity analysis of the adoption rate for SMRs in the global energy market from 2020 to 2050. We project potential adoption rates and identify key factors influencing SMR deployment. Our analysis employed a multi-faceted approach to capture the complexities and uncertainties surrounding SMR adoption:

• Scenario Development: We developed optimistic, base case, and pessimistic scenarios to provide a range of potential outcomes. These scenarios incorporate different assumptions about technological progress, regulatory environments, and market conditions.
• Monte Carlo Simulation: We conducted 10,000 simulations using Latin Hypercube sampling to account for uncertainties in key parameters and factors affecting SMR adoption.
• Sensitivity Analysis: We calculated correlation coefficients to determine the sensitivity of the adoption rate to each factor. This helps identify which factors have the most significant impact on SMR adoption rates.
• Distribution Analysis: We analyzed the probability distribution of adoption rates in I 2050 to understand the range and likelihood of various outcomes. This provides insights into the most probable adoption rates and the spread of possible results.

The combination of these methodological approaches provides a robust framework for analyzing SMR deployment potential and identifying key factors influencing adoption rates. Our analysis acknowledges several methodological limitations, including data availability constraints for commercial SMR projects, uncertainty in long-term market conditions, and regional variations in cost structures.

4. Recommendations for Advancing SMR Deployment

Given the growing interest in SMRs for decarbonizing energy systems, while ensuring reliable electricity supply and recognizing the need to adapt the existing regulatory framework for SMRs, we highlight a comprehensive approach to address their unique challenges and opportunities. Our recommendations emphasize innovative regulatory strategies and a structured implementation roadmap to facilitate a smooth transition, minimize disruptions, and maximize the benefits of these advanced technologies.

4.1. Innovative Regulatory, Licensing, and Economic Strategies

4.1.1. Risk-Informed Licensing

Regulatory authorities should adopt a risk-informed licensing approach for SMRs, tailoring safety requirements to each reactor’s design based on detailed risk assessments. AI, including machine learning (ML) and Natural Language Processing (NLP), can enhance regulatory efficiency by predicting safety issues and automating document reviews [35]. Probabilistic Risk Assessment (PRA) should remain central, prioritizing significant risks for resource allocation. A tiered licensing process, supported by AI, can streamline approvals, identifying issues early and reducing regulatory burden [92].

4.1.2. Adaptive Regulatory Framework

A “regulatory sandbox” approach, supported by the Treasury department would allow SMR developers to operate under a less stringent regime initially, adjusting as technology evolves. AI could assist in document review and safety modeling, with digital twin technology creating virtual SMR replicas for design certification and ongoing monitoring. The regulatory authorities should develop guidelines for digital twin submissions and maintain a continuous feedback loop with developers and operators [93].

4.1.3. Economic Viability Assessments

Regulatory authorities should develop advanced economic analysis tools, such as scenario-based modeling, to assess SMR projects under varying market conditions. Blockchain technology can enhance transparency and efficiency in reporting and interactions between regulators and operators (Andrianov et al., 2020) [94]. A feasibility study on blockchain, followed by pilot projects, could lead to full integration. Long-term cost–benefit analyses should include environmental and social benefits. Innovative funding mechanisms like public–private partnerships and green bonds could support SMR projects, alongside a dedicated fund for innovation [95].

4.1.4. Public–Private Partnerships

The regulatory authorities should foster public–private partnerships to share financial risks and benefits. Strategic alliances between public institutions, private companies, and research organizations can drive joint R&D efforts, incentivized by tax breaks or co-funding. Shared infrastructure investments, especially for grid connections and cooling systems, can reduce project costs. Regulatory risk-sharing mechanisms, like insurance against regulatory changes, could mitigate investment risks [96].

4.2. Next Generation Security and Non-Proliferation Strategies

Forward-Looking Security and non-proliferation measures involve proactive strategies to ensure SMRs and other nuclear facilities comply with security and non-proliferation standards. These measures use advanced technologies and international protocols to prevent the misuse of nuclear materials and technology, especially in diverse and remote locations.

4.2.1. Advanced Security Integration

The regulatory authorities should mandate advanced security technologies for SMRs, including remote monitoring systems, automated threat detection, and drone surveillance. These technologies offer real-time oversight, rapid threat detection, and aerial inspections of inaccessible areas. AI-enhanced systems can quickly identify breaches, while drones provide added security without risking personnel [92].

4.2.2. International Collaboration and Non-Proliferation Compliance

International cooperation is essential for unified security and non-proliferation protocols. The regulatory authorities should work with the IAEA to ensure SMR designs meet global standards, addressing modularity and fuel recycling challenges with frequent inspections and tight material controls. AI can assist in anomaly detection and material accounting using machine learning algorithms to identify unusual patterns [92].

4.2.3. Quantum-Resistant Cybersecurity Protocols

To counter emerging quantum computing threats, the regulatory authorities should implement quantum-resistant cybersecurity protocols, including Post-Quantum Cryptography and vulnerability assessments. Quantum Key Distribution (QKD) should be explored for ultra-secure communications, ensuring SMRs are protected from current and future cyber threats [92].

4.3. Public Engagement and Communication Strategies

Effective public communication is vital for gaining support and trust in SMRs. Regulatory authorities should use innovative strategies to inform and engage the public, focusing on understanding, transparency, and participation.

4.3.1. Utilizing Virtual Reality (VR) for Enhanced Public Understanding

Regulatory authorities should use Virtual Reality (VR) to make SMR technology more accessible and engaging. VR simulations of SMR facilities can allow people to explore these sites virtually and view safety systems, operational processes, and emergency protocols. Interactive VR scenarios could also demonstrate SMR safety features and virtual emergency drills, helping to educate and reassure the public about SMR safety and reliability [92].

4.3.2. Collaborative Educational Initiatives

Regulatory authorities should partner with universities and research centers to enhance public understanding of SMRs. This could include webinars and seminars on SMR technology, safety measures, and environmental impacts. Engaging students through research grants or competitions and organizing outreach programs with SMR experts in schools and universities would foster interest and inspire future professionals in the field [92].

4.3.3. Transparent and Continuous Public Engagement

Continuous and transparent communication is essential. Regulatory authorities should hold regular public forums and town hall meetings to update the community on SMR developments and address concerns. Dedicated online platforms should provide updates, safety assessments, and environmental impact studies, with features like FAQs, expert interviews, and feedback mechanisms such as surveys and direct communication channels [92].

4.4. Implementation Roadmap

• Deploying Small
  Modular Reactors (SMRs) requires a phased strategy that integrates regulatory innovations, security measures, public engagement, and economic planning. The Plan-Do-Study-Act (PDSA) method provides a structured approach that ensures these strategies are systematically tested, refined, and scaled for full deployment. Each phase aligns with the strategies discussed in previous sections:

• Regulatory and economic strategies (Section 4.1) are incorporated into the foundational phase. (Year 0–2)
• Security frameworks (Section 4.2) are tested in pilot projects before full-scale implementation. (Year 2–5)
• Public engagement efforts (Section 4.3) ensure community participation throughout the deployment process. (Year 5–10)
  The following roadmap details how these strategies are applied over a 10-year period.

4.4.1. The PDSA Cycle

• Plan (Years 0–2): Establish the regulatory foundation.
  • Form an innovation task force.
  • Develop training programs on AI, blockchain, and quantum technologies.
  • Partner with tech companies and research institutions.
  • Define success criteria and KPIs.
  • Evaluation: Collect baseline data, set timelines, and gather feedback from training.
• Do (Years 2–5): Test and refine strategies.
  • Launch pilots for AI-assisted regulation, digital twins, and quantum-resistant cybersecurity.
  • Implement blockchain in licensing.
  • Execution: Run pilots, collect performance data, and engage stakeholders.
  • Evaluation: Measure pilot effectiveness and feasibility for scaling.
• Study (Years 2–5): Analyze pilot results.
  • Compare results with KPIs.
  • Identify successes and areas for improvement.
  • Review training, partnerships, and technology use.
  • Evaluation: Analyze data, review findings, and document lessons learned.
• Act (Years 5–10): Full deployment and improvement.

  ○

  Scale successful pilots.

  ○

  Integrate AI, blockchain, and quantum-resistant technologies.

  ○

  Implement continuous improvement.

  ●

  Evaluation: Monitor performance, update PDSA based on new data, and adjust strategies.

4.4.2. Key Performance Indicators (KPIs)

• Speeding Up the Licensing Process: Monitor the time for licensing completion. A reduction indicates increased efficiency and faster SMR deployment.
• Catching Safety Issues Early: Track early detections of safety issues. An increase suggests effective early identification by AI and monitoring technologies.
• Obtaining Correct Economic Predictions: Compare predicted vs. actual economic outcomes of SMR projects. Greater accuracy indicates effective economic modeling.
• Staying One Step Ahead of Security Threats: Monitor the detection and neutralization of security threats by AI systems. Higher detection rates show effective security measures.
• Building Public Trust and Engagement: Use surveys and feedback to gauge public trust and participation. Increased trust indicates successful communication strategies.

5. Results

5.1. Economic Analysis

The economic analysis of the SMR project reveals nuanced differences between FOAK and NOAK implementations. The Monte Carlo simulation demonstrates LCOE distributions with notable characteristics. NOAK implementations show a slight leftward shift in the LCOE distribution, indicating marginally lower costs compared to FOAK implementations. The LCOE ranges from approximately 30 to 45 USD/MWh, with NOAK projects displaying a slightly more favorable distribution.

The Net Present Value (NPV) analysis reveals interesting insights, with both FOAK and NOAK projects showing symmetric distributions centered near zero, ranging from approximately USD −1000 to +1000 million. While both distributions are similar, NOAK projects exhibit a slightly more favorable NPV spread, suggesting incremental economic improvements through subsequent implementations.

The Internal Rate of Return (IRR) distributions demonstrate a more pronounced difference, with both FOAK and NOAK projects showing a bell-shaped distribution ranging from approximately −60% to +100%. NOAK implementations appear to have a slightly more positive skew, indicating potentially improved economic performance.

Payback period distributions highlight significant variations, with FOAK projects showing a concentration of returns in the 10–20 year range, while NOAK implementations display a broader, slightly more optimistic distribution extending across the project’s lifetime. This suggests some reduction in financial risk and improved investment recovery for subsequent deployments.

These results underscore the complex economic landscape of SMR technologies, demonstrating that while learning effects and standardization offer incremental improvements, the underlying economic uncertainties remain substantial across both FOAK and NOAK implementations.

Figure 3 presents a comprehensive NPV sensitivity analysis examining CAPEX, discount rate, electricity price, and capacity factor across installed capacities ranging from 300 MW to 2400 MW under NOAK conditions. The analysis reveals that larger installed capacities demonstrate superior NPV profiles and greater resilience to CAPEX variations. Project viability becomes challenged when CAPEX increases by 10–20%, though this threshold varies with installation size. The 2400 MW configuration shows particular robustness, maintaining positive NPVs under higher cost scenarios. The discount rate analysis reveals a strong negative correlation with the NPV, while electricity price shows a positive linear relationship with break-even occurring around 40 USD/MWh. Capacity factor demonstrates significant impact on project economics, with NPV improving substantially as operational efficiency approaches 100%.

Figure 4 illustrates the Monte Carlo simulation results for key economic parameters. The IRR distribution reveals a more complex picture, with both FOAK and NOAK implementations showing distributions ranging from approximately −60% to +100%, indicating significant economic variability. The payback period distribution demonstrates a notable difference, with FOAK projects concentrated in earlier years and NOAK implementations showing a broader, more extended distribution across the project lifetime.

The Levelized Cost of Electricity (LCOE) distribution spans from approximately 30 to 45 USD/MWh for both project types, with subtle variations between FOAK and NOAK implementations. Contrary to initial expectations, the cost differences are less pronounced than anticipated, suggesting that cost reductions from first-of-a-kind to next-of-a-kind deployments may be more incremental than previously hypothesized.

The Net Present Value (NPV) analysis reveals symmetric distributions for both project types, ranging from USD −1000 to +1000 million, centered near zero. This indicates significant economic uncertainty and the potential for both substantial gains and losses across SMR implementations.

These results highlight the complex economic landscape of small modular reactor (SMR) technologies. While learning effects and standardization offer some improvements, the underlying economic uncertainties remain substantial. The analysis suggests that successful SMR deployment requires robust risk management and careful economic modeling, with no guarantee of immediate economic advantages in subsequent implementations.

5.2. Sensitivity Analysis—Technology Adoption Rate

Figure 5 shows a median adoption rate for small modular reactors (SMRs) of approximately 4.5% by 2050, with a wide range between the 5th and 95th percentiles indicating significant uncertainty. The mean adoption rate closely follows the median, suggesting a symmetrical distribution of outcomes. By 2050, the 95th percentile reaches about 9% adoption, while the 5th percentile stays above 0.5%. The graph features an S-shaped curve, reflecting accelerated growth in later years and highlighting both the potential for SMR growth and the considerable uncertainties in long-term forecasting. Our analysis identified six key factors affecting SMR adoption, listed in order of impact based on Figure 6.

• Market Demand (correlation coefficient ≈ 0.58)

  ○

  Highest impact;

  ○

  Reflects the need and appetite for SMR technology in various energy markets;

  ○

  Suggests that identifying and developing suitable markets is crucial for SMR adoption.

• Public Acceptance (correlation coefficient ≈ 0.55)

  ○

  High impact;

  ○

  Reflects public perception, community support, and societal attitudes toward nuclear energy;

  ○

  Highlights the importance of public engagement and education in SMR deployment.

• Regulation (correlation coefficient ≈ 0.52)

  ○

  High impact;

  ○

  Encompasses licensing processes, safety standards, and policy frameworks;

  ○

  Suggests that streamlining regulatory processes could significantly accelerate SMR adoption.

• Cost (correlation coefficient ≈ 0.50)

  ○

  Moderate to high impact;

  ○

  Covers capital costs, operational expenses, and competitiveness with other energy sources;

  ○

  Indicates that economic factors play a significant role in adoption decisions.

• Government Support (correlation coefficient ≈ 0.48)

  ○

  Moderate impact;

  ○

  Includes financial incentives, research funding, and policy backing;

  ○

  Underscores the role of consistent government support in fostering SMR development.

• Technological Advancements (correlation coefficient ≈ 0.20)

  ○

  Lower impact;

  ○

  Encompasses improvements in design, efficiency, safety features, and manufacturing processes;

  ○

  This indicates that current SMR designs are seen as technologically viable.

5.2.1. Scenario Analysis

Our scenario analysis provides a range of potential outcomes:

• Optimistic Scenario: Shows strong growth, reaching about 9% adoption by 2050.

  ○

  Assumes strong market demand, favorable regulatory environment, high levels of public acceptance, and significant government support;

  ○

  Represents the potential for accelerated SMR deployment under ideal conditions.

• Base Case Scenario: Projects moderate growth, reaching about 4.5% by 2050.

  ○

  Reflects current trends and moderate assumptions;

  ○

  Suggests steady growth in SMR adoption with acceleration in later years.

• Pessimistic Scenario: Indicates slower growth, ending at about 3% by 2050.

  ○

  Assumes challenges in market development, regulatory approval, public acceptance, or government support;

  ○

  Highlights potential barriers to SMR adoption that could hinder growth.

Figure 7 shows the results of the base case and optimistic and pessimistic scenario analysis. In the base case scenario, the most likely projection based on current trends and moderate assumptions, the adoption rate is about 4.5% by 2050. This scenario follows an S-shaped growth pattern, with slow initial growth followed by accelerated expansion. It assumes gradual improvements in SMR technology, moderate market demand, government support, and incremental progress in regulatory frameworks and public acceptance. While this scenario indicates that SMRs will establish a presence in the global energy mix, they may not become a dominant technology within this timeframe under current conditions.

5.2.2. Distribution of Adoption Rates (2050)

The probability distribution of 2050 adoption rates (Figure 8) shows the following:

• A right-skewed distribution;
• Peak probability between a 2 and 4% adoption rate;
• Low probability of very low (<1%) or very high (>10%) adoption rates;
• A long right tail, suggesting potential for higher-than-expected adoption rates.

This distribution provides insights into possible outcomes’ range and relative probabilities, aiding in risk assessment and strategic planning.

5.2.3. Projected Installed SMR Capacity

According to IAEA reports from 2022, the global installed capacity of SMRs was about 313 MW, which has remained unchanged as of 2024. Therefore, all scenarios in this analysis begin with the same initial installed capacity. Based on our updated projections, we present the following graph (Figure 9).

• By 2040, the projected installed capacities are as follows:

  ○

  Base case: approximately 633 MW;

  ○

  Optimistic scenario: approximately 1.2 GW;

  ○

  Pessimistic scenario: approximately 512 MW.

• By 2050, these capacities are expected to increase to the following:

  ○

  Base case: approximately 983 MW;

  ○

  Optimistic scenario: approximately 2.9 GW;

  ○

  Pessimistic scenario: approximately 650 MW.

These projections differ from other estimates. The Idaho National Lab projects global SMR capacity to reach 6 GW by 2035 and 28 GW by 2050. Earlier estimates predicted much higher capacities: 65 GW to 75 GW by 2040 and, potentially, 375 GW by 2050 [97]. Our analysis suggests a more conservative growth trajectory, reflecting the complex interplay of market demand, regulatory environments, and public acceptance identified in our sensitivity analysis. The wide range between our optimistic and pessimistic scenarios highlights significant uncertainty in SMR adoption and the influence of various factors on deployment rates. This underscores the need for adaptive strategies and ongoing monitoring of market trends and policy developments in the SMR sector.

6. Discussion

6.1. Assessment Summary

• The results now appear much more realistic and in line with typical expectations for SMR projects.
• The NPV distribution suggests a generally positive economic outlook, but with acknowledged risks.
• The IRR, while positive, is modest, which is appropriate for a large infrastructure project with significant public benefit.
• The payback period now reflects the long-term nature of nuclear power investments.
• The LCOE distribution indicates that the project could be cost-competitive with other energy sources.

The economic analysis of small modular reactors (SMRs) reveals complex interactions between technical, economic, and market factors that influence their viability. Our Monte Carlo simulation results demonstrate a more nuanced economic outlook, with both FOAK and NOAK implementations showing significant variability. The Net Present Value (NPV) distribution reveals symmetric ranges from −1000 to +1000 million USD for both project types, centered near zero, indicating substantial economic uncertainty. The Internal Rate of Return (IRR) simulation presents a broader and more complex picture than initial estimates. The distribution spans from approximately −60% to +100% for both FOAK and NOAK implementations, challenging simplistic interpretations of project economics. This wide range emphasizes the critical importance of comprehensive risk assessment and robust economic modeling in SMR project development.

The Levelized Cost of Electricity (LCOE) analysis reveals a more moderate cost landscape, with distributions ranging from 30 to 45 USD/MWh for both project types. Contrary to initial expectations, the cost differences between FOAK and NOAK implementations appear more incremental than previously anticipated. This suggests that cost reductions through learning effects may be more challenging to achieve than initial projections suggested. Payback period distributions highlight the temporal complexity of SMR investments, with FOAK projects showing a concentration of returns in earlier years and NOAK implementations displaying a broader distribution across the project lifetime. This variability underscores the need for flexible investment strategies and comprehensive risk management.

While the simulation reveals less dramatic economic advantages than previous analyses suggested, it provides valuable insights into the economic uncertainties inherent in SMR technologies. The results emphasize that successful deployment requires nuanced understanding of multiple economic parameters, robust risk mitigation strategies, and adaptable investment approaches. The analysis suggests that SMR projects remain potentially viable investments, but with significantly more complexity and uncertainty than earlier studies may have indicated. Future research should focus on understanding the factors that can help narrow these economic uncertainties and improve project predictability.

6.2. Payback Period and Cost Considerations

The payback period analysis reveals nuanced insights into SMR investment dynamics. Our simulation results show a more complex distribution of payback periods, with both FOAK and NOAK implementations displaying significant variability across the project lifetime. Contrary to initial expectations, the payback period distributions do not show as clear a distinction between FOAK and NOAK plants as previously hypothesized. The simulation reveals that payback periods are influenced by multiple interconnected factors. The symmetric NPV distributions and broad IRR ranges suggest that traditional assumptions about project economics may oversimplify the complex financial landscape of SMR investments. While learning effects and technological improvements are anticipated, the actual economic benefits appear more incremental than previously projected.

Cost structure analysis highlights the challenges in achieving dramatic cost reductions. The Levelized Cost of Electricity (LCOE) distributions range from 30 to 45 USD/MWh for both project types, indicating that cost advantages between FOAK and NOAK implementations are less pronounced than earlier studies suggested. The overnight capital cost variations and operational cost reductions appear to have a more modest impact than anticipated. The analysis of financing requirements reveals the continued complexity of SMR project economics. The extended project timelines and significant upfront capital requirements remain critical challenges. While modular construction offers potential advantages, the simulation results emphasize the need for robust risk management and flexible investment strategies.

Insurance and decommissioning costs continue to represent significant fixed elements in project economics. The Monte Carlo simulation underscores the importance of these long-term cost considerations, demonstrating their substantial impact on overall project financial performance. The results challenge previous optimistic projections about SMR economic viability. While the technology shows promise, the economic uncertainties are more significant than earlier analyses suggested. Future research and development must focus on strategies to reduce these uncertainties and improve the economic predictability of SMR projects.

Key takeaways include the following:

• Economic variability is more pronounced than previously understood;
• Cost reductions between FOAK and NOAK are more incremental;
• Robust risk management is crucial for successful SMR investments;
• Multiple factors contribute to project economic uncertainty.

6.3. LCOE and Market Competitiveness

The Levelized Cost of Electricity (LCOE) analysis reveals a more nuanced economic landscape than previous projections suggested. The Monte Carlo simulation shows LCOE distributions ranging from 30 to 45 USD/MWh for both FOAK and NOAK implementations, challenging earlier expectations of dramatic cost reductions. Contrary to initial calculations, the cost differences between first-of-a-kind and next-of-a-kind plants appear more incremental than anticipated.

Market positioning analysis highlights the complex challenges facing small modular reactor (SMR) technologies. While the potential for baseload power and grid stability remains attractive, the economic uncertainties revealed by the simulation suggest more cautious investment strategies. The ability to provide reliable power is balanced against significant financial variability, as demonstrated by the broad Net Present Value (NPV) and Internal Rate of Return (IRR) distributions.

Cost competitiveness analysis reveals substantial economic uncertainties. The simulation shows symmetric NPV distributions ranging from −1000 to +1000 million USD, indicating significant investment risks. Sensitivity to capital expenditure (CAPEX) variations remains a critical concern, with the potential for substantial financial impact across different project scales.

The economics of multi-unit deployment appear more complex than previous analyses suggested. While standardization and learning effects were expected to provide significant cost advantages, the simulation results indicate more modest potential for cost reduction. The marginal differences between FOAK and NOAK implementations suggest that achieving substantial economic improvements will require more innovative approaches to design, construction, and operation.

Key insights include the following:

• Limited cost advantages between FOAK and NOAK implementations;
• Significant economic uncertainty across project lifecycles;
• The need for robust risk management strategies;
• The importance of flexible investment approaches.

The analysis suggests that while SMR technologies show promise, their economic viability depends on successfully managing multiple sources of uncertainty. Future development should focus on strategies to reduce financial variability and improve the predictability of project economics.

6.4. Technology Adoption Projections

Our analysis of SMR adoption rates reveals a complex interplay of market, technological, and regulatory factors influencing deployment trajectories. The base case projection of 4.5% market share by 2050 represents a balanced assessment of these various influences. This projection is supported by our Monte Carlo simulation results, which demonstrate the robustness of this estimate across multiple scenarios. The significant spread between optimistic (9%) and pessimistic (3%) scenarios reflects the uncertainty inherent in long-term technology adoption forecasting, particularly for capital-intensive infrastructure investments.

The sensitivity analysis identifies key drivers of adoption rates, with market demand emerging as the strongest influence (correlation coefficient 0.58). This finding suggests that market forces, rather than technological limitations, will primarily determine SMR deployment rates. Public acceptance follows closely (0.55), highlighting the critical role of stakeholder engagement and social license in nuclear technology deployment. The regulatory environment’s strong influence (0.52) underscores the importance of efficient, predictable licensing processes in facilitating adoption. Notably, technological advancement shows the lowest correlation (0.20), indicating that current SMR designs have achieved sufficient technical maturity for commercial deployment.

An analysis of adoption patterns reveals distinct market segments with varying deployment potential. Early adoption is likely in regions with existing nuclear infrastructure and expertise, as evidenced by current project developments in North America and Europe. Our projections indicate that by 2040, installed SMR capacity could reach approximately 633 MW in the base case, with the optimistic scenario suggesting the potential for 1.2 GW. These projections are more conservative than some industry estimates, reflecting our consideration of practical constraints in manufacturing capacity, regulatory approval timelines, and market development.

The simulation results indicate potential acceleration in adoption rates post-2035, driven by several factors identified in our analysis. First, the completion of FOAK projects will provide crucial operational data and cost validation. Second, supply chain maturation will enable more efficient production and delivery of components. Third, regulatory frameworks are expected to evolve to better accommodate SMR characteristics. Our modeling suggests that this acceleration could lead to installed capacities of 983 MW (base case) to 2.9 GW (optimistic scenario) by 2050.

6.5. Policy and Regulatory Implications

The regulatory framework analysis reveals several critical areas requiring policy attention to facilitate SMR deployment. Our findings indicate that regulatory efficiency significantly impacts project economics, with streamlined processes potentially reducing deployment times by 20–30%. The strong correlation between regulatory environment and adoption rates (0.52) quantifies this relationship and highlights the importance of regulatory reform. Current regulatory frameworks, designed primarily for large reactors, require adaptation to address unique SMR characteristics such as underground siting, passive safety systems, and multi-module configurations. International harmonization of standards emerges as a crucial factor in achieving economies of series production. Our analysis suggests that standardized designs and harmonized regulations could reduce engineering and licensing costs by up to 40% for subsequent units. This finding is particularly relevant for multi-unit deployments, where our economic analysis indicates potential operational cost reductions of 15–25% through shared infrastructure and staffing optimizations. The development of risk-informed, performance-based regulations appears essential for realizing these benefits while maintaining safety standards.

Economic support mechanisms play a vital role in early deployment phases. Our analysis of FOAK projects indicates that government support through loan guarantees, production tax credits, or carbon pricing mechanisms may be necessary to achieve financial viability. The extended payback periods identified in our analysis (20–25 years) suggest that long-term power purchase agreements and stable policy frameworks are crucial for investor confidence. The potential for cost reduction through learning effects (20–30% from FOAK to NOAK) provides a rationale for early policy support to accelerate industry development.

Nuclear liability and insurance requirements represent another critical policy consideration. Our analysis assumes insurance costs at 0.5% of CAPEX, reflecting current industry standards. However, the potential for risk-informed adjustments to insurance requirements for SMRs, given their enhanced safety features and smaller source terms, could further improve project economics. The development of international nuclear liability frameworks that specifically address SMR characteristics could facilitate cross-border deployment and investment.

6.6. Regional and Market-Specific Considerations

Regional analysis reveals significant variations in SMR deployment potential across different markets. Grid infrastructure characteristics emerge as a crucial determinant of SMR viability. Our analysis indicates that regions with smaller or isolated grids, where large nuclear plants are impractical, present particularly attractive opportunities for SMR deployment. The ability to match capacity additions more precisely to demand growth (300 MWe increments in our analysis) provides advantages in markets with moderate growth rates or grid stability concerns. Market structure analysis identifies distinct opportunities across different regions. In developed markets with high renewable penetration, SMRs can provide valuable grid stability services and reliable baseload power. Our economic modeling suggests that the load-following capabilities of SMRs become particularly valuable in markets with renewable penetration exceeding 30%. In emerging markets, the analysis indicates that SMRs could serve as enablers of industrial development, with potential applications in process heat, desalination, and hydrogen production creating additional value streams beyond electricity generation.

Geographical factors significantly influence SMR economics. Our analysis of site-specific considerations reveals that remote locations, particularly those currently dependent on diesel generation, could achieve payback periods 30–40% shorter than our base case projections due to high existing electricity costs. Industrial clusters present another promising market segment, where the potential for cogeneration and process heat applications can improve project economics substantially. The analysis indicates that such applications could enhance project IRR by 2–3 percentage points compared to electricity-only generation.

Supply chain considerations vary significantly by region. Countries with existing nuclear infrastructure demonstrate advantages in terms of regulatory readiness and workforce availability. Our analysis suggests that regions with established manufacturing capabilities could achieve learning rates at the higher end of our projected range (8% versus 5% base case), particularly for balance-of-plant components. The development of regional manufacturing hubs emerges as a potential strategy for optimizing supply chain economics while meeting local content requirements.

7. Conclusions

Analyzing small modular reactors (SMRs) presents a nuanced picture of opportunities and challenges in the evolving global energy landscape. Integrating SMRs into existing energy systems offers significant advantages, including modularity, operational flexibility, and scalability, making them well suited to complement intermittent renewable energy sources. However, their deployment faces regulatory approvals, supply chain readiness, and regional standardization challenges. Effective regulatory frameworks and global collaboration are essential in harmonizing standards and supporting innovation. Environmental and security considerations are also crucial, including advanced waste management, AI, cybersecurity, and Safeguards by Design (SBD) to enhance safety and monitoring.

Our economic analysis indicates a competitive LCOE of USD 43.63 per MWh and an NPV of USD 492.09 million, suggesting strong financial viability. Sensitivity analysis highlights that capital expenditure, discount rates, electricity prices, and capacity factors significantly impact profitability. The findings emphasize the need for a coordinated approach involving policymakers, industry stakeholders, and public engagement to overcome uncertainties and foster SMR adoption. Our analysis also reveals that the adoption of SMRs in the global energy landscape is projected to reach approximately 4.5% by 2050, with installed capacities ranging from 650 MW to 2.9 GW across different scenarios, driven primarily by market demand, public acceptance, and regulatory frameworks. The analysis underscores that while technological advancements have some role, the current SMR designs are already considered viable. Key findings highlight market demand as the most influential factor, followed by public perception and the need for streamlined regulatory processes. Economic considerations highlight the importance of demonstrating SMRs’ benefits beyond costs, such as energy security and grid stability.

As the global energy sector shifts towards low-carbon solutions, SMRs offer a promising avenue for energy security and sustainability. Realizing their potential requires coordinated efforts. Policymakers, industry stakeholders, and regulatory bodies must work together to create a supportive environment for the adoption of SMRs. By fostering international collaboration and ensuring adaptable regulations, regulatory authorities can shape the future of nuclear energy. The path forward demands sustained effort and strategic action. Now is the time to lay the groundwork for a future where SMRs significantly contribute to a diverse, low-carbon energy mix. Let us take the necessary steps today to ensure SMRs meet tomorrow’s energy challenges.

Limitations and Future Work

Our analysis acknowledges several important limitations that warrant consideration in interpreting the results. The limited operational experience with commercial SMRs introduces uncertainty in cost and performance projections. While our Monte Carlo simulations account for this uncertainty through probability distributions, actual operational data from FOAK projects will be crucial to validate these projections. The learning rates assumed in our analysis (5–8%) are based on historical nuclear industry experience and may not fully capture the potential benefits of modern manufacturing techniques and digital technologies. Methodological limitations also merit consideration. Our economic modeling makes simplified assumptions about financing structures and discount rates that may not reflect the complexity of project-specific arrangements. The assumption of a constant 5.5% discount rate across different market contexts represents a particular simplification. Additionally, our treatment of construction schedules, while incorporating uncertainty through Monte Carlo simulation, may not capture all potential sources of delay or acceleration in project execution.

Data availability presents another significant limitation. The proprietary nature of cost data for advanced reactor designs restricts the ability to validate certain assumptions. Our reliance on publicly available information and industry benchmarks may not capture the full range of design-specific cost variations. Furthermore, the early stage of supply chain development for SMR components creates uncertainty in manufacturing cost projections, particularly for specialized components with limited supplier bases.

External factor considerations represent an additional limitation. Our market adoption projections may not fully capture the potential impact of disruptive technologies or significant policy changes. The sensitivity of our results to market demand (correlation coefficient 0.58) suggests that changes in energy market structures or carbon pricing mechanisms could significantly affect deployment trajectories. Geopolitical factors and changes in international trade relationships could also impact supply chain development and technology transfer.

Future research directions emerge from these limitations. First, detailed supply chain studies are needed to validate manufacturing capability assumptions and identify potential bottlenecks. This research should include analyses of advanced manufacturing techniques and their potential impact on learning rates. Second, comprehensive grid integration studies should address the technical and economic implications of multiple small units, particularly in systems with high renewable penetration. Third, investigations of hybrid energy systems incorporating SMRs with renewable energy and storage technologies represent a promising area for future work.

Research priorities should also include the following:

• The development of more sophisticated financial models incorporating project-specific risk factors;
• Analyses of potential cost reductions through advanced manufacturing and construction techniques;
• Investigations of non-electric applications and their impact on project economics;
• Assessments of regulatory frameworks’ evolution and their impact on deployment timelines;
• Evaluations of workforce development needs and their influence on deployment capabilities.

These research directions would help refine deployment projections and identify policy interventions that could facilitate successful SMR commercialization. The collection and analysis of operational data from FOAK projects will be particularly valuable in validating and improving the projections presented in this study.