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DOE OSTI2017

Development of ITM Oxygen Technology for Low-cost and Low-emission Gasification and Other Industrial Applications

Air Products carried out a scope of work under DOE Award No. DE-FE0012065 “Development of ITM Oxygen Technology for Low-cost and Low-emission Gasification and Other Industrial Applications” with subcontractors Ceramatec, Penn State, and WorleyParsons. The scope of work under this award was aimed at furthering the development of the Ion Transport Membrane (ITM) Oxygen production process toward a demonstration-scale facility known as the Oxygen Development Facility (ODF). Specific activities will help to enable design and construction of the ODF through advancement of a number of challenging technical elements that are required to manage risk in the initial deployment of ITM technology. Major objectives of the work included developing ITM Oxygen ceramic membrane materials with improved performance and reliability, optimizing ceramic module geometry and fabrication methods, testing module performance, trialing the improved fabrication process at commercial scale in the Ceramic Membrane Module Fabrication Facility (CerFab), and advancing engineering development of the ITM oxygen production process, including vessel design and contaminant control measures to prepare for deployment of the ODF. The comprehensive report that follows details the team’s work, which includes several notable accomplishments: 1) compressive creep, a likely limiter of ceramic module lifetime in service, was demonstrated to be retarded by an order of magnitude by changes in material formulation, module joining dimensions, and internal wafer geometry; 2) two promising new materials were shown to be superior to the incumbent ITM material in a key material parameter related to oxygen flux; 3) module degradation mechanisms were identified following operation in large pilot-scale equipment; 4) options for utilizing ITM in a coal-to-liquids (CTL) facility to enable liquids production with carbon capture were identified and studied; and 5) the benefits of potential improvements to the technology were assessed for their cost impact on ITM Oxygen applications to clean power, fuels, and other applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Sustainable network design for multi-purpose pellet processing depots under biomass supply uncertainty

This work develops a two-stage stochastic mixed-integer programming model to manage multi- purpose pellet processing depots under feedstock supply uncertainty. The proposed optimization model would help to minimize cost and to mitigate emissions from the supply chain network. We consider three alternative Biomass Processing and Densi cation Depot (BPDD) technologies; namely, conventional pellet processing, high moisture pellet processing, and ammonia ber expansion. These three technologies pre-process/pre-treat and densify different types of biomass into more highly densi ed intermediate products for different markets in order to improve movability and overall supply network performance in terms of costs and emissions. A hybrid decomposition algorithm was developed that combines sample average approximation with an enhanced Progressive Hedging (PH) algorithm to solve this challenging NP -hard problem. Some heuristics such as Rolling Horizon (RH) heuristic, variable xing technique were later applied to further enhance the PH algorithm. Mississippi and Alabama were selected as a testing ground and ArcGIS was employed to visualize and validate the modeling results. The results of the analysis reveal promising insights that could lead to recommendations to help decision makers achieve a more cost-effective environmentally-friendly supply chain network.

09 BIOMASS FUELS↗
DOE OSTI2024

Modeling hydrogen markets: Energy system model development status and decarbonization scenario results

Hydrogen can be used as an energy carrier and chemical feedstock to reduce greenhouse gas emissions, especially in difficult-to-decarbonize markets such as medium- and heavy-duty vehicles, aviation and maritime, iron and steel, and the production of fuels and chemicals. Significant literature has been accumulated on engineering-based assessments of various hydrogen technologies, and real-world projects are validating technology performance at larger scales and for low-carbon supply chains. While energy system models continue to be updated to track this progress, many are currently limited in their representation of hydrogen, and as a group they tend to generate highly variable results under decarbonization constraints. Here, the present work provides insights into the development status and decarbonization scenario results of 15 energy system models participating in study 37 of the Stanford Energy Modeling Forum (EMF37), focusing on the U.S. energy system. The models and scenario results vary widely in multiple respects: hydrogen technology representation, scope and type of hydrogen end-use markets, relative optimism of hydrogen technology input assumptions, and market uptake results reported for 2050 under various decarbonization assumptions. Most models report hydrogen market uptake increasing with decarbonization constraints, though some models report high carbon prices being required to achieve these increases and some find hydrogen does not compete well when assuming optimistic assumptions for all advanced decarbonization technologies. Across various scenarios, hydrogen market success tends to have an inverse relationship to success with direct air capture (DAC) and carbon capture and storage (CCS) technologies. While most model-scenario combinations predict modest hydrogen uptake by 2050 – <10 million metric tons (MMT) – aggregating the top 10 % of market uptake results across sectors suggests an upper range demand potential of 42–223 MMT. The high degree of variability across both modeling methods and market uptake results suggests that increased harmonization of both input assumptions and subsector competition scope would lead to more consistent results across energy system models. The wide variability in results indicates strongly divergent conclusions on the role of hydrogen in a decarbonized energy future.

08 HYDROGEN↗
DOE OSTI2025

EVI-LOCATE User Manual

One of the longest stages in the deployment of electric vehicle supply equipment (EVSE) is the initial planning of the infrastructure itself. Engineers and fleet experts from the National Renewable Energy Laboratory (NREL) have supported dozens of charging infrastructure site plans over the past couple decades, including the generation of site schematics, determinations of electric capacity, and estimates for likely costs. As the market for electric vehicles (EVs) has matured, this approach should no longer require a time and personnel intensive process. In order to shorten the time taken to develop site plans and cost estimates, NREL developed a tool that fleet managers, facility managers, electricians, EVSE installers, and members of the public can use to develop initial schematics and ballpark pricing for charging station installations. The Electric Vehicle Infrastructure - Locally Optimized Charger Assessment Tool and Estimator (EVI-LOCATE) provides a structured and consistent way for users to enter information about their planned EVSE project in a relatively simple web-based format. EVI-LOCATE then calculates electrical equipment capacity, wiring runs, and project costs. It produces a site diagram optimized around surface characteristics with differential trenching costs for softscape such as grass compared to hardscape such as asphalt that can be adjusted by users in the tool. It also stores the resulting site plans and costs in a dashboard for access at a later date, including plan revisions if necessary. This document guides users through the EVI-LOCATE screens and associated questions. It contains tip text boxes throughout on how best to interface with the tool and find additional information or context. The appendices contain the assumptions and calculations underpinning the tool. Much of the information for EVI-LOCATE was gathered through industry engagements with EVSE installers, invoices from completed EVSE installations, Gordian's RS Means construction data, and the General Services Administration blanket purchase agreement for EVSE. For a visual tutorial of the tool, users can watch EVI-LOCATE Step-by-Step Video. The tool itself is available at https://evi-locate.nrel.gov.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Intersections of Disadvantaged Communities and Renewable Energy Potential: Data Set and Analysis to Inform Equitable Investment Prioritization in the United States

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where disadvantaged community indicators and high generation potential from cost-effective renewable energy opportunities intersect and deployment could lead to economic development and job creation. This presentation will highlight several of our findings. This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.

community energy planning↗
DOE OSTI2026

Optimizing Alabama’s CO 2 Storage in Shelby County (OASIS) (Final Report)

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS) is a CarbonSAFE Phase II designed to support the U.S. Department of Energy’s goals of reducing project risks and costs for future carbon dioxide (CO 2 ) capture, utilization, and storage (CCUS) projects, bringing more storage resources into commercial classifications that support business and financial decisions, and encouraging more rapid growth of a vibrant, geographically widespread industry for geologic carbon storage.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

A control-inspired approach for energy transition planning under uncertainty

As the global carbon footprint continues to grow, many countries are implementing carbon emission reduction policies which have incentivized the expansion of low-carbon and renewable technologies. However, the speed and scale of deployment falls short of that needed to meet climate goals. Energy system models serve as key tools for guiding investment decisions and helping policymakers evaluate the effects of various policies on the development of an energy system. This study focuses on the energy system of the United States and builds upon prior work by incorporating more geographic granularity to account for the trade of commodities and addresses transmission congestion through electricity price adjustments. Furthermore, real-world characteristics, such as delays in constructing new liquid fuel production and electricity generation facilities, are integrated using a sequential decision-making approach that better reflects how decisions can be updated as uncertainties unfold. Results demonstrate that stochastic programming combined with sequential decision-making produces energy transition pathways that are robust to multiple uncertain futures. Additionally, considering real-world characteristics significantly impacts the deployment of renewable technologies and the ability to meet carbon emission reduction goals while also reliably meeting demand. These findings highlight the importance of accounting for uncertainty and real-world characteristics to avoid overly optimistic projections in energy system planning.

energy systems↗
DOE OSTI2026

Long-Term Impacts of Constrained Transmission Deployment on the Cost-Reliability Tradeoff

Traditional Resource Adequacy (RA) frameworks in the U.S. undervalue the contributions of inter-regional transmission to resource adequacy during stress periods, focusing on the availability of nameplate capacity instead. However, availability of nameplate capacity does not always translate into electricity delivery, especially during tail events. Moreover, the rapid deployment of energy-limited resources and increasing electricity demand challenge existing resource adequacy frameworks and couple regional electricity demand and availability of supply via transmission. We propose a two-stage framework that goes beyond the existing capacity-centered approaches to reveal the RA contributions of transmission. In the first stage we introduce a multi-objective optimization framework to quantify the merits of transmission expansion via Pareto Frontiers under alternative futures of no transmission investment, primary energy resources availability and demand growth. The second stage focuses on tail events and leverages the results of the first stage to characterize the risk profile of regional consumers across the U.S. under the alternative energy futures. We find that no new transmission can lead to a more expensive and less reliable national grid across scenarios, however, the impact on regional RA can vary. The probabilistic analysis reveals that transmission investments can alleviate the tail risk of consumers, however, the availability of fuel resources does not always alleviate regional tail risks. Our findings inform policymakers and utilities on the prioritization of transmission investments to mitigate the risk of widespread outages, also for tail events, and ensure reliable and affordable electricity delivery to all.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

How Can Probabilistic Solar Power Forecasts Be Used to Lower Costs and Improve Reliability in Power Spot Markets? A Review and Application to Flexiramp Requirements

Net load uncertainty in electricity spot markets is rapidly growing. There are five general approaches by which system operators and market participants can use probabilistic forecasts of wind, solar, and load to help manage this uncertainty. These include operator situation awareness, resource risk hedging, reserves procurement, definition of contingencies, and explicit stochastic optimization. We review these approaches, and then provide a case study in which a method for using probabilistic solar forecasts to define needs for reserves is developed and evaluated. The case study has three parts. First, we describe building blocks for enhancing the Watt-Sun solar forecasting system to produce probabilistic irradiance and power forecasts. Second, relationships between Watt-Sun forecasts for multiple sites in California and the system's need for flexible ramp capability (flexiramp) are defined by machine learning and statistical methods. Third, the performance of present methods to defining flexiramp requirements, which are not conditioned on weather and renewables forecasts, is compared with that of probabilistic solar forecast-based requirements, using a multi-timescale production costing model with an 1820-bus representation of the WECC power system. Significant potential savings in fuel and flexiramp procurement costs from using solar-informed reserve requirements are found.

14 SOLAR ENERGY↗
DOE OSTI2021

BETO 2021 Peer Review - Enzyme Engineering and Optimization (EEO)

The FY2020 SOT economic model for the DMR BDO process indicates that the production and use of biomass degrading enzymes represents ~10% of the MFSP of BDO. We are thus working to enhance the performance of the dominant cellulase enzyme, Cel7A. In Fy2018-19, we selected 100 promising genes from the "Cel7A wheel of life" and cloned them into T. reesei using a constitutive promotor. This natural diversity screening resulted in the discovery of several enzymes exhibiting improved characteristics relative to the industry standard Cel7A from T. reesei (Tr). Growth of the transformed host on glucose insured that the Cre1 induced cellulase expression cascade was suppressed, thus enabling purification of the target gene product. The first top performing enzyme found was from P. funiculosum (Pf). Other top performing enzymes were identified from T. aculeatus, T. terrestris, and A. oryzae. Computational modeling predicted the structural subsites responsible for the improvements, which were cloned into the sequence of PfCel7A. The recombinant enzymes were expressed in T. reesei, purified, and tested. Testing was not possible with SOT relevant substrates, so the best-case substrate was used; solids from the DMR process subjected to a novel dilute alkaline wash to remove the "lignin shield." Two chimeric Cel7A enzymes show improved performance (1.2 to 1.35x) relative to PfCel7A, which in turn showed considerable improvement (1.6x) relative to T. reesei Cel7A. These new enzymes have been provided to our industrial partner for evaluation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Final Report on Community Solar Design Models for Consumer, Industry, & Utility Success

Since the inception of the first community solar program in 2006, a number of different utility, solar industry and consumer driven community solar program models have emerged across the country with varying regulatory and solar market frameworks behind them. There is little consistency in how programs are administered, participant benefits are assigned, and customers are charged for participation. Further, while it is regularly speculated that community solar programs meet the needs of customers, no such consumer research has been completed against different community solar program models. This collaborative research effort addressed three primary issues: Program design models are numerous and evolving, with varying degrees of applicability across different state policy, utility regulatory, and solar market types. The agents, transaction methods, and accruing costs and benefits are highly variable and largely built on anecdotally successful model evolution. ‘Community solar’ (shared/group solar, solar gardens, etc.) has become a catch-all concept that means different things to different stakeholders, limiting constructive program development and growth. Everything from green pricing programs to remote net metering to metering aggregation has been framed as community solar. Consumer research on individual concepts and program models has been done, but no comprehensive and comparative market research on the broader design models and attributes has been performed. SEPA’s collaborative research effort on Community Solar Design Models for Consumer, Industry, & Utility Success is premised on the principle that greater standardization of community solar models and better understanding of consumer interests are key underpinnings of increased community solar deployment. Utilizing a cross-sectional multi-stakeholder working group, as well as focus groups and surveys, webinars, targeted outreach, and other tools, this project aims to expand the community solar knowledge base, facilitate information exchange, identify opportunities for standardization and improvement, determine what consumers’ interests are and how best to message to them, promote the research results within the solar and utility industries, and advance key opportunities for strategic deployment plans for community solar. A summary of these key takeaways/lessons learned during the grant period include: Siting of system should be evaluated up-front in the process Engage stakeholders collaboratively and early to help ensure the best chance for a successful program IT/billing departments must have a seat at the design table Establish upfront target objectives with respect to residential and commercial program access levels helps ensure program success Balance trade-offs to manage utility and developer risk with customer participation carefully to optimize pricing and sizing the program offering Over the course of the 42 month grant period, SEPA and its project team conducted a series of activities all designed to accelerate the number and size of community solar programs across the country. These activities included: Community Solar Program Design Models (2 reports) – SEPA, in collaboration with its projects team, the Coalition for Community Solar Access, and over 60 administrators of actual community solar programs, developed two reports providing hard data on the developments of community solar. These reports touched on program performance, quantity and type of programs, and program design steps, among other aspects. The reports collectively received over 2000 unique downloads. Market Research Report – SEPA, in collaboration with The Shelton Group, conducted a series of national surveys and focus groups to identify what customers were looking for in a community solar offering. The resulting report, “What the Community Solar Customer Wants”, received over 1,000 unique downloads. Technical Assistance Projects – SEPA supported 8 organizations who were pursuing community solar programs. Based on this support, over 5.7 MWs of new solar capacity have been developed. Technical Assistance Case Studies – SEPA developed two case studies detailing the technical assistance work in Fremont, NE Department of Utilities and the public power arm of Minster Ohio. These two reports have received 1,002 unique downloads. Webinar – SEPA hosted two webinars on community solar which collectively received 743 participants. The webinars focused on disseminating the findings of the research conducted under this project, as well as the research conducted in separate solar market pathways projects. Community Solar Design Workshops – 120 registrants learned about the trends in community solar and participated a business case exercise to design their own programs.

14 SOLAR ENERGY↗
DOE OSTI2024

Microgrid Controller Survey Report: 2024 Update

In the past decade, the number of microgrids deployed by electric utilities, end-use customers, and third parties has been increasing significantly both in the US and worldwide. The increase is driven by various reasons, such as carbon emission reduction, energy efficiency improvement, reliability and resilience enhancement, energy infrastructure modernization, and more. Microgrid controllers, as the most important components in these deployed microgrids, optimally coordinate the operation and control of the microgrid assets (e.g., distributed energy resources [DERs], energy storage systems, demand response, and even electric vehicles) and ensure that the microgrid is being operated in an efficient, clean, and resilient manner. To that end, the market for microgrid controllers has been growing rapidly in recent years. Various microgrid controllers have been released and continuously updated by vendors to satisfy the different needs of microgrid customers. However, the functionalities demonstrated by microgrid controllers released by different vendors show a huge difference because of a lack of widely known and accepted industrial standards, and various microgrid customers have specific requirements for different applications and scenarios. To obtain a clear view of the current state of the commercial microgrid controllers’ functionalities and identify potential research gaps, a survey of the functionalities of commercial microgrid controllers and the Advanced Distribution Management System (ADMS) developed by vendors and national laboratories was conducted in 2023. The results of the survey are presented in this report with the current status of commercial microgrid controllers analyzed, potential research gaps identified, and future research trends revealed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Kinetic phase evolution of spinel cobalt oxide during lithiation

Spinel cobalt oxide has been proposed to undergo a multiple-step reaction during the electrochemical lithiation process. Understanding the kinetics of the lithiation process in this compound is crucial to optimize its performance and cyclability. In this work, we have utilized a low-angle annular dark-field scanning transmission electron microscopy method to visualize the dynamic reaction process in real time and study the reaction kinetics at different rates. We show that the particles undergo a two-step reaction at the single-particle level, which includes an initial intercalation reaction followed by a conversion reaction. At low rates, the conversion reaction starts after the intercalation reaction has fully finished, consistent with the prediction of density functional theoretical calculations. At high rates, the intercalation reaction is overwhelmed by the subsequently nucleated conversion reaction, and the reaction speeds of both the intercalation and conversion reactions are increased. Phase-field simulations show the crucial role of surface diffusion rates of lithium ions in controlling this process. Furthermore, this work provides microscopic insights into the reaction dynamics in non-equilibrium conditions and highlights the effect of lithium diffusion rates on the overall reaction homogeneity as well as the performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

CSP Systems Analysis - Final Project Report

The CSP Systems Analysis project was a three-year effort supporting the Concentrating Solar Power (CSP) Subprogram within the Solar Energy Technologies Office of the U.S. Department of Energy (DOE). The goal of the CSP Systems Analysis project was to provide timely and accurate CSP cost data to the DOE and predict performance and cost for emerging technologies that may impact research directions and industry investment. The project consisted of six, mostly independent tasks. Major accomplishments over the three-year period of performance were as follows. The NREL team maintained current cost estimates for CSP technologies by annual updates to the cost input parameters within NREL's System Advisor Model (SAM). SAM is a performance and cost simulation software that includes technology models for the primary CSP technologies. During the period from 2016 to 2018, the estimated cost within SAM's default CSP molten-salt power tower technology dropped from 13.0 to 11.1 cent/kWh (real dollars without incentives). Power cycle models for the supercritical carbon dioxide (sCO2) Brayton Cycle were developed and made an option within SAM's molten-salt power tower model. These models were subsequently used to evaluate the cost reduction potential of alternative salts. The partial-cooling model was found to provide the greatest cost-reduction potential due to its combination of efficiency and temperature differential across the turbine and thermal energy storage (TES) system. These studies were documented in two journal articles. NREL's optical modeling software SolTrace and SolarPILOT were made more versatile and released as open-source software to the CSP community. These tools help researchers and developers to model and optimize the optical performance of CSP collector systems. The new features were highlighted in a recorded webinar that can be accessed from the NREL SAM website. New models for solar-thermal systems, that is, applications for solar industrial process heat, were developed, validated, and installed within SAM. The analysis includes a 2018 review of linear collectors in the market that are tailored for solar process heat applications. In 2018 the NREL team also developed an annual simulation for a direct steam generation system integrated with a latent-heat TES system. This analysis was submitted for journal publication. The NREL team continued to support the exchange of information and development of CSP guidelines within the international CSP community of SolarPACES. Much of the work under this project was presented at SolarPACES, including the development of a modeling checklist to help CSP stakeholders standardize the models used for estimating CSP performance and cost. The CSP Systems Analysis project also supported DOE requests for tracking and reporting programmatic targets for the CSP Subprogram.

14 SOLAR ENERGY↗
DOE OSTI2021

Optimal Transactive Energy Trading of Electric Vehicle Charging Stations With On-Site PV Generation in Constrained Power Distribution Networks

This paper presents a two-level transactive energy market framework, that enables energy trading among electric vehicle charging stations (EVCSs). At the lower level, the discharging capability of EVs and on-site PV generation are leveraged by individual EVCS for participating in the transactive trading with their peers. Once the lower-level trading is completed, EVCSs trade energy at the upper level through the power grid network managed by the distribution system operator (DSO). The upper-level market is cleared while satisfying the power distribution network constraints. A cooperative game-based model is proposed to model the energy trading among EVCSs. To this end, the asymmetric Nash bargaining method is applied to allocate the grand coalition's payoff to each EVCS at the upper-level market, while a weighted proportional allocation method is used to allocate individual EVCS's payoff to its respective EVs at the lower-level market. In this work, the upper-level market formulation is further decomposed into two subproblems representing an energy scheduling and trading subproblem which maximizes EVCS payoffs, and a bargaining subproblem which allocates EVCS payoffs. The effectiveness of the proposed framework for incentivizing transactive trades among EVs and EVCSs is validated in case studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Cognitive barriers during monitoring-based commissioning of buildings

Monitoring-based commissioning (MBCx) is a continuous building energy management process used to optimize energy performance in buildings. Although monitoring-based commissioning (MBCx) can reduce energy waste by up to 20%, many buildings still underperform due to issues such as unnoticed system faults and inefficient operational procedures. While there are technical barriers that impede the MBCx process, such as data quality, the focuses of this paper are the non-technical, behavioral and organizational, barriers that contribute to issues initiating and implementing MBCx. In particular, this paper discusses cognitive biases, which can lead to suboptimal outcomes in energy efficiency decisions, resulting in missed opportunities for energy savings. This paper provides evidence of cognitive biases in decisions during the MBCx process using qualitative data from over 40 public and private sector organizations. The results describe barriers resulting from cognitive biases, listed in descending order of occurrence, including: risk aversion, social norms, choice overload, status quo bias, information overload, professional bias, and temporal discounting. Building practitioners can use these results to better understand potential cognitive biases, in turn allowing them to establish best practices and make more informed decisions. Finally, researchers can use these results to empirically test specific decision interventions and facilitate more energy efficient decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

Models for Facilitating Government-Funded Activities in the Post-ISS LEO Ecosystem

The International Space Station National Lab (ISSNL) was established through Congressional authority in 2005 and has been managed by a nonprofit called the Center for the Advancement of Science in Space (CASIS) since 2011 to support research, development, education, and commercial activities in low-Earth orbit (LEO). NASA leadership is considering next steps for microgravity and orbital activities in LEO in preparation for the retirement of the International Space Station (ISS) and transition to Commercial LEO Destinations (CLDs) in the 2030 timeframe. Specifically, our study team within the NASA Office of Technology, Policy, and Strategy addressed the question: What are potential models for an ISS National Lab facilitating government-funded or subsidized activities on a commercial LEO platform after the transition of the ISS to one or more private platforms? To inform the trade space of potential models, we conducted over 40 discussions with stakeholders internal and external to NASA and reviewed over 35 documents related to LEO legislation, commercialization, models, and activities. Following the extensive literature review and discussions with diverse stakeholders, we defined and evaluated six models, in addition to the current ISSNL model. We assessed each model across three possible future scenarios (dynamic, steady, and limited growth of the commercial LEO market and activities) and across five stakeholder-driven model evaluation criteria (ability to meet NASA’s needs, adaptability, opportunity for collaboration, market sustainability, and equity and accessibility). The six models in the future trade space were: • Government Research Broker: Customizable research efforts on transport vehicles and CLDs • Innovation Campus: Modern terrestrial campus with workforce focus • Anchor Tenant: Long-term, substantial agreement for leasing space on a single CLD • Fee for Service: Free market approach with NASA-sponsored grants and service/data buys • Matchmaker: Neutral third-party connecting users to platforms • Institute Network: Network of separate but related efforts to enable commercial scaling The Government Research Broker model performed best across the scenarios, followed by Innovation Campus, Anchor Tenant, and Fee for Service. While Matchmaker and Institute Network exhibited positive aspects, the two models performed most favorably in future scenarios with well-established communities and markets. The six models presented in this study are representative of the potential trade space and are illustrative examples. NASA leadership can adjust models as desired to align to their priorities more closely by using combinations of the unique model features provided in our analysis. The optimal model is likely a combination of features from multiple models. Building upon this work to best position NASA and the diverse stakeholders of LEO activities for success post-ISS, further work will explore the near-term impact of preparing for the transition of the ISS to CLDs by identifying opportunities for modifying the current ISSNL-CASIS partnership. ACKNOWLEDGEMENTS We thank the many reviewers and discussants, internal and external to NASA, that contributed to the work.

Erica Rodgers↗
DOE OSTI2024

Assessment of Technoeconomic Opportunities in Automation for Nuclear Microreactors

Achieving full decarbonization of all economic sectors remains a challenge, especially in niche markets. For example, remote communities and industrial or mining activities detached from the main electric grid heavily rely on fossil fuels, similar to urban and industrial microgrids with combined heat and power needs. A combination of renewables and energy storage is often not suitable due to cost, reliability, intermittency, and large storage requirements. Small nuclear reactors with a flexible purpose could serve these applications. Microreactors (MR) are a class of reactors that are compact, factory manufactured, transportable, and self-regulating. Typically, they generate much less power than their large reactor counterparts. The main advantages of microreactors include the versatile nature of the energy produced, the reliability of supply, and freedom from having to transport and store large quantities of fuels on-site, coupled with the absence of dependence on an electrical grid. A strong business case is needed to move from the microreactor prototype to the commercialization phase. In fact, fossil fuels are still relatively inexpensive, and in the near term, carbon credits will be available to virtually compensate for emissions. For microreactors, one of the main costs in operation and maintenance (O&M) is their staffing levels. In this study, we investigate how to optimize the number (and thus the cost) of workers, moving from a traditional, fully manned, on-site personnel approach to an unmanned, remote personnel approach. We examine four different staffing models that can be implemented as the technology matures and evolves. We estimate the staffing needs of each model and build a business case to justify the substitution of on-site personnel with adequate technologies. To do so, we propose a cost model to quantify potential cost reductions from automating O&M activities. The model accounts for both the reduction in cost derived from the reduced number of full-time-equivalent (FTE) employees and the increase in cost derived from the need to buy new control hardware as needed. Applying the cost model that we created to different scenarios, an on-site O&M cost reduction exceeding 80% can be expected. Additionally, we found that it is more impactful to focus on automating routine O&M tasks rather than attempting to automate transient management (shutdowns, restarts, monitoring condition deviations). In fact, transients typically account for less than 1% of the total FTE time spent on the reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗