Technoeconomic analysis of small modular reactors decarbonizing industrial process heat
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Like other industrial processes, the production of metallic nuclear fuels (MNF) requires that fabrication facilities be able to reliably meet production demands, operate efficiently, and adhere to federal and local safety regulations. In turn, the set of design variables employed by such a facility, such as operations policies, infrastructure and machinery purchased, and the type and number of staff hired, directly impact a facility’s ability to satisfy these goals. Therefore, facility designers must carefully determine which set of design variable values optimally satisfies these constraints. In this paper, we explore how values for these high-level design variables, namely hiring requirements, can be determined in the context of nuclear fuel manufacturing through the coupling of physics-based and discrete-event simulation technologies. Using the Versatile Test Reactor (VTR) program as a case study, we demonstrate how SCALE and MCNP nuclear physics model outputs can be integrated into ExtendSim discrete-event simulation (DES) models of the fuel fabrication process to determine the optimal number of staff hired to ensure fuel production goals are met, operations comply with effective dose limit regulations, and overall project costs are reduced.
Artificial intelligence (AI) and machine learning (ML) methods have had significant impacts in science and technology in recent years. These methods for generating models from datasets or logic-based algorithms that emulate aspects of human performance can similarly accelerate the fields of nuclear applications, science, and technology toward the IAEA goals of contributing to peace, health, and prosperity. In order to accomplish advances with AI in general and ML in particular across these fields, IAEA can play a significant role by establishing, hosting and curating centralised resources, including databases, adhering to FAIR (findable, accessible, interoperable and reusable) principles and Open Science best practices, providing stewardship of data sharing, supporting training efforts and development of relevant workforces, as well as enabling connections among the scientific, technology, mathematics, AI and ethics communities. Many areas can benefit from the use of AI in the realm of nuclear applications. In human health, these areas include clinical research, epidemiology, nutrition, medical imaging, radiotherapy and education of health professionals. AI-based tools are also being used to facilitate different clinical tasks in imaging, computer-assisted diagnosis in mammography and lung cancer screening programmes, and dose prediction in nuclear medicine procedures. ML methods in particular may also increase the efficiency and accuracy of the analysis of computerised tomography and dual-energy absorptiometry scans for body composition and bone analysis. The application of AI methods to nuclear and related technologies in food and agriculture can lead to significant advances and improved efficiency in the optimisation of agricultural production, food product development, management of supply chains, food safety and food authenticity control. In the water and environmental sector, AI can help inform policies to mitigate the world’s water problems. The application of AI techniques to hydrology and environmental sciences is expected to improve patterns identification and enable model predictions under a changing climate.
On March 11, 2011 the Great Tohoku Earthquake occurred approximately 70 kilometers off the coast of Japan. This magnitude 9.0 earthquake was closely followed by a massive tsunami that reached 7 meters in height. Using NASA Earth Observation Systems (EOS), we will assess the damage to the area impacted by this disaster. Landsat 5 Thematic Mapper (TM) will be used to create normalized difference vegetation index (NDVI) maps and MODIS on Aqua and Terra will be used to produce enhanced vegetation index (EVI) maps. CALIPSO and HYSPLIT will also be used to track smoke released from the Fukushima Daiichi Nuclear Power Plant to assess where the radioactive steam traveled to. An analysis of the economic impact of this disaster will be conducted to help policy makers in the United States and in Japan. This research will highlight the ability of NASA EOS in providing support for disaster response around the world.
NASA has completed a preliminary mission and systems study of nuclear electric propulsion (NEP) systems for 'split-sprint' human exploration and related robotic cargo missions to Mars. This paper describes the study, the mission architecture selected, the NEP system and technology development needs, proposed development schedules, and estimated development costs. Since current administration policy makers have delayed funding for key technology development activities that could make Mars exploration missions a reality in the near future, NASA will have time to evaluate various alternate mission options, and it appears prudent to ensure that Mars mission plans focus on astronaut and mission safety, while reducing costs to acceptable levels. The split-sprint nuclear electric propulsion system offers trip times comparable to nuclear thermal propulsion (NTP) systems, while providing mission abort opportunities that are not possible with 'reference' mission architectures. Thus, NEP systems offer short transit times for the astronauts, reducing the exposure of the crew to intergalactic cosmic radiation. The high specific impulse of the NEP system, which leads to very low propellant requirements, results in significantly lower 'initial mass in low earth orbit' (IMLEO). Launch vehicle packaging studies show that the NEP system can be launched, assembled, and deployed, with about one less 240-metric-ton heavy lift launch vehicle (HLLV) per mission opportunity - a very Technology development cost of the nuclear reactor for an NEP system would be shared with the proposed nuclear surface power systems, since nuclear systems will be required to provide substantial electrical power on the surface of Mars. The NEP development project plan proposed includes evolutionary technology development for nuclear electric propulsion systems that expands upon SP-100 (Space Power - 100 kw(e)) technology that has been developed for lunar and Mars surface nuclear power, and small NEP systems for interplanetary probes. System upgrades are expected to evolve that will result in even shorter trip times, improved payload capabilities, and enhanced safety and reliability.
This chronology covers the 32-year history of orbital debris and near-Earth environmental concerns. It tracks near-Earth environmental hazard creation, research, observation, experimentation, management, mitigation, protection, and policy-making, with emphasis on the orbital debris problem. Included are the Project West Ford experiments; Soviet ASAT tests and U.S. Delta upper stage explosions; the Ariane V16 explosion, U.N. treaties pertinent to near-Earth environmental problems, the PARCS tests; space nuclear power issues, the SPS/orbital debris link; Space Shuttle and space station orbital debris issues; the Solwind ASAT test; milestones in theory and modeling the Cosmos 954, Salyut 7, and Skylab reentries; the orbital debris/meteoroid research link; detection system development; orbital debris shielding development; popular culture and orbital debris; Solar Max results; LDEF results; orbital debris issues peculiar to geosynchronous orbit, including reboost policies and the stable plane; seminal papers, reports, and studies; the increasing effects of space activities on astronomy; and growing international awareness of the near-Earth environment.
The safe and secure management of Pu is a matter of international concern, with ∼250 t of separated Pu currently stockpiled worldwide. The UK's civil inventory of nuclear materials contains significant stocks of separated Pu from the reprocessing of Magnox and AGR spent fuels. The preferred option for the 138.5 tonnes of Pu is re-use as mixed oxide (MOx) fuel, although 5% is not suitable for re-use and is recommended for direct disposal. However, it will take more than 15 years to implement re-use, requiring that the Pu be kept in interim storage in its current state for that period, i.e. as PuO{sub 2} powder within inert steel storage cans at Sellafield. The focus of the work presented here is thus plutonium storage and the direct disposal of plutonium. The Research and Development needs of both are now pressing: in the case of storage due to it being the current default; in the case of immobilization and disposal because of a comparative lack of Research and Development on Pu conditioning and packaging due to policy uncertainty as to whether it would be disposed of in a Geologic Disposal Facility (GDF). Addressing these needs is complicated by Pu's high radioactivity, decay heat and radiotoxicity, criticality, nuclear safeguard requirements and, for some UK Pu contaminated materials targeted for disposal, poor inventory. Thus, there is also a critical requirement for underpinning research on Pu bearing materials in these two contexts. In response to these needs, the TRANSCEND Consortium (Transformative Science and Engineering for Nuclear Decommissioning, a multi-disciplinary collaboration of 11 universities and 8 key industry partners from across the UK's civil nuclear sector) is seeking to provide technical underpinning to ongoing option development for the UK's civil Pu stockpile. Whilst understanding the behaviour of plutonium during its re-use as MOx is beyond the scope of the TRANSCEND Consortium work plan, the main objectives of the work are: (1) For interim storage: to understand how the surface structure and properties of pristine and radiation damaged PuO{sub 2} change with time in the absence and presence of water; and (2) For immobilization and disposal: to understand the mechanisms of incorporation of Pu into ceramic and glass-ceramic waste-forms, as well as the effect on these of self-induced radiation damage. Each objective is being addressed through separate work packages, the details of which are discussed in this paper. (authors)
This report presents the results of technoeconomic analysis that advances understanding of the potential of small modular reactors and microreactors, collectively referred to as small reactors (SRs) in this report, in microgrids. This analysis was conducted using a proxy model for SR in microgrids based on the datapoints that were identified and explored in a predecessor report “Small Reactors in Microgrids: Technical Studies Guidance.” The results and the subsequent comparative analysis in this report show that SRs could be a cost-competitive generation option when capital costs are modeled considering potential economies of scale in sizing. If the CO 2 tax is imposed on carbon fuels, SRs would be even more attractive than gas generators. Then, SRs in microgrids would play a pivotal role in reducing the carbon footprint at the local distribution level. However, it is particularly important to identify the most suitable use cases for early adoption and the right balance of generation mix with other clean technologies as SRs achieve a level of technological and financial maturity.
This report demonstrates the capabilities of the net-zero microgrid (NZM) Xendee platform for modeling an SR module with electricity, heat extraction and thermal storage in microgrids configurations. The model effectively captures the most important technical and economic considerations for SR technology specific analysis: cost and operational characteristics of SR technology and financial costs and incentives. The model can analyze multiple scenarios to establish metrics for cost-competitive and zero-carbon microgrids connected to the grid or completely isolated. The model is fully integrated within the Xendee platform for modeling and analysis of clean energy microgrids with storage and generation from renewable energy sources. The model captures the capabilities, constraints, and nuances of SR by incorporating parameters related to plant economics, design efficiency and performance, plant operation and component and fuel lifespan. The cost and operational parameters modeled in the SR module are specific to the technology selected for integration in the microgrid. Cost parameters recognize advanced nuclear technology for modular production and installation based on economies of scale from factory manufacture and related commissioning, and cost reduction through technology maturation—first-of-a-kind (FOAK) and nth-of-a-Kind (NOAK). The cost parameters include installation, operations and maintenance (O&M), fuel refueling cycle, and reactor life. Installation cost reflects economies of scale due to unit sizing at scale and colocation. O&M economies of scale for both fixed- and variable-cost fuel life-cycle costs are incurred at every refueling interval, with separate front- and back-end fuel costs, as well as waste-handling and disposition costs. This report investigates key characteristics of different SR technologies suitable for microgrid applications, including design principles, sizing, coolant properties, temperature ratings, fuel structures, and life-cycle considerations. This also includes fuel technologies applicable to these SR systems, alongside strategies for nuclear-waste and spent-fuel management and approaches to address safety, security, and proliferation challenges. Four primary groups of SR technologies are examined: water-cooled, liquid-metal-cooled, high-temperature gas-cooled, and molten-salt-cooled systems. In this report, an initial guideline for technology selection is established, aligning the characteristics of the technologies with the requirements of microgrids. The selection of technology in a microgrid is influenced by various factors, including financial capacity, location and accessibility, demand type and characteristics, reliability and resilience requirements, area constraints, and the lifespan of the microgrid. The types of electrical and non-electrical applications within the microgrid also play a significant role in technology selection. The characteristics of SRs, such as their smaller size, modularity, transportability, long refueling interval, improved safety features, ability to operate in autonomous or semi-autonomous mode, and provision of high-grade heat, are particularly appealing for microgrids. Furthermore, a list of considerations for implementing SRs in microgrids is outlined. The SR model is created to be continuously improved with the acquisition of actual data on investment and operational costs, experience with supply chains, production at scale, and field deployments. In the near term, performance data on applications in microgrids will become available from lessons learned from laboratory tests, such as those planned for the Microreactor Applications Research Validation and Evaluation Project (MARVEL), led by Idaho National Laboratory (INL). The SR model incorporates scenario data and known SR design specifications, enabling technoeconomic analysis for SR deployment in microgrids. It specifically considers the distinctive attributes of SRs as generators in technoeconomic studies. SRs can be modeled and analyzed with generation from renewable-energy sources, energy storage, and flexible loads over a range of functionality and applications. This offers a comprehensive tool for feasibility studies, scenario development, and sensitivity analysis for “what-if” consideration of any range of assumptions about SRs in microgrids and other aggregations of distributed-energy resources, including virtual power plants.
As the global push towards net zero carbon gains momentum, the demand for clean hydrogen is expected to grow rapidly across various sectors, including transportation, industries and electrical grids. To meet this growing hydrogen demand, baseload hydrogen production facilities capable of providing a continuous and reliable supply of hydrogen will be necessary throughout the world. This paper explores the technoeconomic feasibility of establishing baseload electrolytic hydrogen production facilities in the United States, utilizing different clean generation resources. The key criteria include maintaining a consistent supply of clean hydrogen without putting baseload demand stress to already vulnerable power grid. In order to do that, the proposed facilities will host onsite clean power generation and energy storage technologies. The proposed facilities can capitalize on available investment and production incentives and have ability to export excess electricity to the utility at a bulk price. Several scenarios are considered based on the clean energy resources to support the electrolysis process including light water reactors (LWRs) currently evaluating retirement options, wind, solar PVs, and advanced small modular reactors (SMRs). For each scenario, a hypothetical hydrogen production facility is considered in a location in the US where the primary generation resource is at its peak strength. Comparative analysis in this paper reveal that the nuclear power plants are most economically viable for baseload hydrogen production facilities, outperforming renewable-based facilities with significantly lower levelized cost of hydrogen (LCOH). Even under best-case scenarios for resource availability, incentives and export prices, renewable-based facilities face challenges due to daily and seasonal generation variability, resulting in large installation sizes and lower capacity factors. Among renewable-based facilities, complementarity hybrids, providing more stable power supply, demonstrate superior economics compared to facilities based on a single renewable technology. While LWR-powered facility can achieve a negative LCOH with incentives, SMR-powered facilities can provide economic hydrogen supply with LCOH below $1/kg with high temperature electrolysis option. The analysis in this paper underscores the pivotal role of nuclear energy in the future hydrogen economy.
Defense Technical Assistance (TA) Infographic designed to inform potential pilot partnerships with military installation about the TA opportunities available. - Secure and reliable energy is crucial for the operational readiness and resilience of military installations. The Department of Energy’s Grid Deployment Office has funded a new initiative at Idaho National Laboratory to conduct technical, on-site assessments that aim to secure the power infrastructure of military bases reliant on civilian utilities for their operations, both CONUS and OCONUS. Including how the assessments work and INL capabilities, partnership model as well as outcomes.
New ways to integrate energy systems to maximize efficiency are being sought to meet carbon emissions goals. Nuclear-renewable integrated energy system (NR-IES) concepts are a leading solution that couples a nuclear power plant with renewable energy, hydrogen generation plants, and energy storage systems, such that thermal and electrical power are dispatchable to fulfill grid-flexibility requirements while also producing hydrogen and maximizing revenue. Here, this paper introduces a deep reinforcement learning (DRL)-based framework to address the complex decision-making tasks for NR-IES. The objective is to maximize revenue by generating and selling hydrogen and electricity simultaneously according to their time-varying prices while keeping the energy flow in the subsystems in balance. A Python-based simulator for a NR-IES concept has been developed to integrate with OpenAI Gym and Ray/RLlib to enable an efficient and flexible computational framework for DRL research and development. Three state-of-the-art DRL algorithms have been investigated, including two-delayed deep deterministic policy gradient (TD3), soft-actor critic (SAC), proximal policy optimization (PPO), to illustrate DRL’s superiority for controlling NR-IES by comparing it with a conventional control approach, particle swarm optimization (PSO). In this effort, PPO has shown more-stable performance and also better generalization capability than SAC and TD3. Comparisons with PSO have demonstrated that, on average, PPO can achieve 13.9% more mean episode returns from the training process and 29.4% more mean episode returns from the testing process when different hydrogen-production targets are applied.
The DOE-NE NWM Cloud was designed to be a generic set of tools and applications for any nuclear waste management program. As policymakers continue to consider approaches that emphasize consolidated interim storage and transportation of spent nuclear fuel, a gap analysis of the tools and applications provided for spent nuclear fuel and high-level radioactive waste disposal in comparison those needed for siting, licensing, and developing a consolidated interim storage facility and/or for a transportation campaign will help prepare DOE for implementing such potential policy direction. This report evaluates the points of alignment and potential gaps between the applications on the NWM Cloud that supported SNF disposal project, and the applications needed to address QA requirements and for other project support needs of an SNF storage project.
Abstract not provided.
As part of a research program in the engineering of software for safety-critical systems, we are performing two case studies. The first case study, which is well underway, is a safety-critical medical application. The second, which is just starting, is a digital control system for a nuclear research reactor. Our goal is to use these case studies to permit us to obtain a better understanding of the issues facing developers of safety-critical systems, and to provide a vehicle for the assessment of research ideas. The case studies are not based on the analysis of existing software development by others. Instead, we are attempting to create software for new and novel systems in a process that ultimately will involve all phases of the software lifecycle. In this abstract, we summarize our results to date in a small part of this project, namely the determination and classification of policies related to software safety that must be enforced to ensure safe operation. We hypothesize that this classification will permit a general approach to the implementation of a policy enforcement mechanism.
The power sector is currently undergoing significant changes, driven by a combination of factors, including decarbonization and technology innovation. This study aims to assess implications of these drivers on U.S. power sector technology futures and the associated water and environmental implications for cooling thermoelectric power plants. Specifically, we evaluate four decarbonization scenarios for the contiguous United States that vary in assumptions concerning demand growth and technology costs, with technology costs driving alternative outcomes that prioritize either technologies that require low amounts of water (such as wind, solar, and battery) or high amounts of water (such as nuclear and carbon capture and storage). These scenarios are executed in a power sector capacity expansion model and compared to two reference scenarios that assume status quo with policy and cost drivers. Our analysis indicates that future U.S. thermoelectric water withdrawals could decrease by 25%–60%, but water consumption could more than triple in some scenarios. These changes are driven by a combination of retirement of some power facilities, shifts in cooling technologies, and new technology deployment. The water use patterns vary across the United States, with the eastern regions demonstrating a lot more variability in water consumption across scenarios than western regions. However, local concerns can influence these possible investments, since increased water consumption can exacerbate water scarcity, leading to conflicts among competing users and affecting regional social, environmental, and economic dynamics. Future work should consider possible costs associated with alternate water sources, as well as improve the representation of water constraints within simulations. Inclusion of extreme events and alternate modeling platforms (e.g. production cost modeling and resource adequacy) may also be warranted to further stress test the robustness of these possible technology futures. Such assessments will be critical for ensuring decarbonization and other infrastructure-oriented investments lead to a reliable and resilient power grid.
This paper describes categories of solar technologies and identifies those that are economic. It compares the private costs of power from solar, wind, nuclear, coal, oil, and gas generators. In the southern United States, the private costs of building and generating electricity from new solar and wind power plants are less than the private cost of electricity from a new nuclear power plant. Solar power is more valuable than nuclear power since all solar power is available during peak and midpeak periods. Half of the power from nuclear generators is off-peak power and therefore is less valuable. Reliability is important in determining the value of wind and nuclear power. Damage from air pollution, when factored into the cost of power from fossil fuels, alters the cost comparison in favor of solar and wind power. Some policies are more effective at encouraging alternative energy technologies that pollute less and improve national security.