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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hydrogen-Battery Hybrid Energy System on Repurposed Offshore Platforms for Efficient Clean-Energy Transition

Due to the rising global energy demand and enhanced awareness of the environmental impact of fossil fuels, the Gulf of Mexico, traditionally known for oil extraction, offers a distinct chance to repurpose the existing offshore infrastructure. With the depletion of oil reserves, it is feasible to adapt previously utilized floating platforms for extraction to generate renewable energy, specifically through wind-generated power and hydrogen production. This adaptation seeks to promote a transport system that is more ecologically friendly in the future. Offshore wind turbines serve as the main energy source, with help from battery storage and hydrogen production to enhance the overall system performance, hydrogen creation, fuel, and electricity delivery for sustainable energy production. The system is divided into two distinct cases, each evaluated for cost, performance, and feasibility, with a focus on minimizing both the Levelized Cost of Energy (LCOE) and the Levelized Cost of Hydrogen (LCOH). The first case examines the integration of offshore wind turbines with hydrogen production. Excess electricity generated by wind turbines is directed toward hydrogen production via electrolysis. The hydrogen produced can be used as fuel for vehicles or transported to the shore via pipelines. The second case investigates a technology that combines wind turbines with battery storage. The batteries possess an ability to supply electricity for a continuous duration of 4 hours maximum each day. The main objective is to reduce the LCOE by considering the battery's charging and discharging cycles, together with the uncertain attributes of wind power and battery deterioration. The produced energy can be distributed for onshore applications or utilized for the purpose of offsetting offshore loads such as subsea oil and gas production, transportation, etc. The offshore hydrogen-battery hybrid system is improved via three advanced algorithms, Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). In Case 1, PSO improves hydrogen production by efficiently managing the electrolyzer’s power consumption, decreasing production costs significantly. Particle Swarm Optimization (PSO) is applied to improve the efficiency of the electrolyzer, reducing production costs and achieving an optimized CAPEX of $240.00 million (from an initial $300.00 million) and OPEX of $9.60 million per year. This system produces 4,720,000 kg of hydrogen annually, with a Levelized Cost of Hydrogen (LCOH) of $6.40/kg and an annual profit of $9.27 million. In Case 2, GWO effectively reduces the overall energy cost by improving the charge-discharge management of batteries, which extends battery life and optimizes their use. The second case focuses on integrating battery storage, optimized using the Grey Wolf Optimizer (GWO), which enhances battery charge-discharge cycles, extending battery life and lowering costs. This system achieves an optimized CAPEX of $204.80 million (from an initial $256.00 million) and OPEX of $9.29 million per year, producing 310883.39 MWh of electricity annually at a Levelized Cost of Energy (LCOE) of $86.13/MWh, with an annual profit of $6.25 million. The implementation of a comprehensive strategy results in a substantial reduction in costs, improved energy efficiency, and a dependable supply of both electric power and hydrogen, emphasizing the benefits of converting offshore oil platforms for clean energy transition. This study explores a clean strategy to enable cost-effective repurposing of offshore O&G platforms. Both cases highlight the economic and technical feasibility of transitioning offshore oil platforms to clean energy systems, demonstrating substantial cost reductions and reliable energy and hydrogen supplies for sustainable energy production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Assessing the technical aspects of ocean-alkalinity-enhancement approaches

Ocean alkalinity enhancement (OAE) is an emerging strategy that aims to mitigate climate change by increasing the alkalinity of seawater. This approach involves increasing the alkalinity of the ocean to enhance its capacity to absorb and store carbon dioxide (CO 2 ) from the atmosphere. This chapter presents an overview of the technical aspects associated with the full range of OAE methods being pursued and discusses implications for undertaking research on these approaches. Various methods have been developed to implement OAE, including the direct injection of alkaline liquid into the surface ocean; dispersal of alkaline particles from ships, platforms, or pipes; the addition of minerals to coastal environments; and the electrochemical removal of acid from seawater. Each method has its advantages and challenges, such as scalability, cost effectiveness, and potential environmental impacts. The choice of technique may depend on factors such as regional oceanographic conditions, alkalinity source availability, and engineering feasibility. This chapter considers electrochemical methods, the accelerated weathering of limestone, ocean liming, the creation of hydrated carbonates, and the addition of minerals to coastal environments. In each case, the technical aspects of the technologies are considered, and implications for best-practice research are drawn. The environmental and social impacts of OAE will likely depend on the specific technology and the local context in which it is deployed. Therefore, it is essential that the technical feasibility of OAE is undertaken in parallel with, and informed by, wider impact assessments. While OAE shows promise as a potential climate change mitigation strategy, it is essential to acknowledge its limitations and uncertainties. Further research and development are needed to understand the long-term effects, optimize techniques, and address potential unintended consequences. OAE should be viewed as complementary to extensive emission reductions, and its feasibility may be improved if it is operated using energy and supply chains with minimal CO 2 emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2026

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2020

Development of Two-Phase Dense Fluid Expander for Advanced Cryogenic Air Separation and Low-Grade Heat Recovery

Cryogenic air separation represents the state-of-the-art technology to produce oxygen to feed coal gasification units. Given the maturity of this technology, it is difficult to identify opportunities to improve process efficiency and reduce the cost of the oxygen produced. However, Air Products conducted research and a feasibility investigation into the use of a two-phase (liquid-vapor) dense fluid expander (DFE) to improve the overall efficiency of cryogenic air separation. Demonstration of this novel concept was intended to allow two important process improvements: 1) elimination of the need for the DFE discharge to be single phase 2) expansion of the operating region of expanders in ASU service. Expanding the scope of turboexpander application beyond current application limits and traditional device designs would allow an increase in power recovery, and application of refrigeration and power recovery at new locations in process cycles would also enable the implementation of new process concepts. These new process concepts include power recovery from compression waste heat and refrigeration extraction and power recovery by replacing let-down valves with two-phase DFEs. Considering the maturity of cryogenic air separation, these new process options could represent a step change in power reduction and provide significant savings in operating costs. These new concepts would be particularly well-suited to large-scale oxygen production by cryogenic air separation and would enhance the economics of producing oxygen for use in coal gasification processes. Rotoflow, an Air Products business unit, manufactures dense fluid expanders in Pennsylvania for sites around the world. This project was executed in two phases, which are illustrated in Figure 1 below. Phase 1 consisted of a feasibility investigation of multiple applications of two-phase DFEs. In Phase 2, devices were identified, designed, fabricated and tested to explore the feasibility of commercial applications of DFEs operating in two-phase service. Engineering and testing were performed by personnel in Air Products’ Rotoflow business unit, with coordination with other Air Products business units.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

EERC Final Topical Report – Findings on Subtask 3.2 – Produced Water Management Through Geologic Homogenization, Conditions, and Reuse

The Energy & Environmental Research Center (EERC) was awarded a contract by the North Dakota Industrial Commission (NDIC) Oil and Gas Research Program (NDIC No. G-051-101) to conduct a study on the recycling of water used in oil and gas operations, also known as produced water, from oil- and gas-producing regions of North Dakota as directed by Section 19 of North Dakota House Bill 1014. This final report provides a compilation of results of the study, which include regulatory, scientific, technological, and feasibility methods and considerations associated with North Dakota produced water management. The report provides a synopsis of this project’s previously submitted produced water assessment report entitled “Produced Water Management and Recycling Options in North Dakota” (Energy & Environmental Research Center, 2020), with updated values provided as appropriate. The report provides the results from the investigation of a novel produced water management strategy, referred to as geologic homogenization, conditioning, and reuse (GHCR), which aims to use a subsurface geologic formation as a natural medium for managing produced water recycling and reuse. Water management is a significant technical and economic challenge for sustainable oil and gas production, and water volumes are intrinsically linked to oil production volumes. North Dakota oil production rose to over 1.5 million barrels (MMbbl)/day in 2019, and despite a downturn in oil price in early 2020, North Dakota oil production has recovered to 1.1 MMbbl/day as of August 2021. Bakken petroleum system development between 2008 and 2020 has resulted in a nearly fourfold increase in produced water volumes to 642 MMbbl/yr in 2020 after peaking at 740 MMbbl/yr in 2019 and a fivefold increase in saltwater disposal (SWD) volumes to 565 MMbbl/yr in 2020 after a peak of 682 MMbbl/yr in 2019. Produced water and SWD volumes are forecasted to double by 2030. SWD is the primary method of produced water management used in North Dakota, with approximately 95% of the SWD volume occurring through subsurface injection into sandstones of the Dakota Group (Dakota). Localized pressurization of the Dakota resulting from SWD and projected increases in produced water volumes could impact the economics of North Dakota oil production. As a result, there is an emerging need to pursue alternative produced water management approaches, including recycling and reuse. While produced water recycling is not yet widespread, commercial operators are making strides in overcoming the technical challenges of using high salinity produced water in completion operations (Marathon Oil, 2020). As water management continues to be a key focal point in companies’ environmental, social, and governance (ESG) initiatives, focus on water management, including recycling, will likely continue to increase. Laboratory column testing, field sample collection, geologic modeling and numerical simulation, and techno-economic analysis all indicate that GHCR could feasibly be implemented as a potential water management option. Laboratory column testing and field sample collection indicate that the Inyan Kara sandstone and native formation fluid are capable of homogenizing with the Bakken produced water to a point where the fluid composition appears to stabilize. Extracting that stabilized fluid could be considered homogeneous and capable of providing individual batches of hydraulic fracturing fluid. Numerical simulation results indicate that extraction of fluids from the Inyan Kara in a GHCR implementation scenario is capable of reducing formation pressure, which would help ease localized pressurization of the Inyan Kara and extend the available capacity for nearby existing SWD wells. Economic analysis indicates that there are scenarios where GHCR implementation can be a competitive or even lower-cost option than a conventional water management approach. Site-specific conditions will dictate the economic potential of GHCR, but potentially attractive sites for GHCR implementation will be those that are located above a pressurized zone of the Inyan Kara, need six or more Bakken infill wells, and face high costs for conventional SWD and/or freshwater. Based on the regulatory review, drilling into the Inyan Kara for SWD and to harness as a source water for industrial use have precedent in North Dakota, and a workable regulatory solution for GHCR seems likely. However, restrictions in the state regarding surface storage and transport of produced fluids may limit some activities, which will affect how GHCR could ultimately be implemented. In summary, this study reveals pursuing GHCR can be a viable approach to water management in North Dakota. The GHCR concept addresses some of the challenges that hinder the more traditional approaches to recycling in the industry. Furthermore, an assessment of the current landscape of water management within the state reveals the ongoing trend of increasing volumes of produced water and SWD. Projections reveal that the volumes of produced water that need to be managed are expected to double over the next decade (Energy & Environmental Research Center, 2020). With the continued development of the Bakken and continuing driving factors related to ESG initiatives, implementing a practice such as GHCR is a feasible approach to adding recycling of produced water to industry within the state. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission Oil and Gas Research Program. References Energy & Environmental Research Center, 2020, Produced water management and recycling options in North Dakota: Final Report for North Dakota Legislative Management Energy Development and Transmission Committee and North Dakota Industrial Commission. Marathon Oil, 2020, Sustainability report: https://cdn.sanity.io/files/ghcnw9z2/website/ 91744eb6ef8fbe59505a911c6b8d2e8dd9a537fa.pdf?dl (accessed November 2021).

02 PETROLEUM↗
DOE OSTI2022

OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets: Preprint

Increasing levels of renewable generation motivate a growing interest in data-driven approaches for AC optimal power flow (AC OPF) to manage uncertainty. However, a lack of disciplined dataset creation and benchmarking prohibits useful comparison between approaches in the literature. To instigate confidence, models must be able to reliably predict solutions across a wide range of operating conditions. This paper develops the OPF-Learn package for Julia and Python which uses a computationally efficient approach to create representative datasets that span a wide spectrum of the AC OPF feasible region. Load profiles are uniformly sampled from a convex set that contains the AC OPF feasible set. For each infeasible point found, the convex set is reduced using infeasibility certificates, found by utilizing properties of a relaxed formulation. The framework is shown to generate datasets which are more representative of the entire feasible space versus traditional techniques seen in the literature, improving machine learning model performance.

dataset↗
DOE OSTI2022

Sustainable Synthesis of Green Methanol Poster

This project examines the technical, economic and environmental feasibility of Flexible Chemical Manufacturing to produce green methanol. It is believed that the catalytic production of fuels and chemicals will not only be technically feasible but also economically feasible, and more importantly, environmentally sustainable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

The Qualification of Sealability and Creep Relaxation of Additively Manufactured Zytel Gaskets for PEM Fuel Cells

The purpose of this thesis is to study the feasibility of low-cost additive manufacturing of gaskets for proton exchange membrane fuel cells exposed to extreme temperature conditions ranging from -55°C to 100°C. With the growing popularity and decreasing costs of additive manufacturing technologies, specifically Material Extrusion (ME), research is being conducted to determine the feasibility of ME components. Thermally cycled PEMFCs may exhibit accelerated gasket deterioration, therefore, the mechanical stability of material extruded gaskets following a harsh thermal cycle must be assessed. The feasibility of the material extruded gaskets will be proven by manufacturing optimization and mechanical testing. The target material for this study is Zytel by DuPont Chemical. The mechanical stability will be assessed via sealability and creep relaxation testing according to ASTM F37B and ASTM F38B respectively. Because the capabilities to conduct sealability testing at temperature were not available, each specimen was thermally soaked and allowed to return to room temperature prior to testing. As a result of sealability experiments, the 100°C-soaked specimens resulted in lower leak rates with a higher precision when compared to specimens soaked at -55°C and 22°C at across all compressive loads. It was observed from results from creep relaxation testing that there is thermal contraction and expansion occurring at 55°C and 100°C respectively, which can be observed by the resultant graphs. The recoverability of thermally cycled specimens are better than those that just experienced a high temperature hold. After the seven-day thermal cycle, the samples stabilized and maintained their structure.

Lazarin, Robert↗
DOE OSTI2022

Cyber risk assessment and investment optimization using game theory and ML-based anomaly detection and mitigation for wide-area control in smart grids

The electric power grid is increasingly becoming susceptible to cyber attacks that exploit vulnerabilities in the smart grid control, information, and physical layers. Successful cyber attacks can have catastrophic impacts on the social and economic well-being of any nation all over the globe. It has, thus, become imperative to secure the smart grid against such adversarial actions to ensure stable, secure, and reliable operation of the grid. The existing research and industry practices prove to be inadequate in terms of providing pragmatic and effective defense methodologies and measures for long-term cybersecurity planning and real-time cybersecurity for grid operation. For example, existing works lack models that incorporate uncertain behavior of cyber-attackers and pragmatic defense measures for cyber risk assessment and cybersecurity investment optimization which often provide unreliable and strictly qualitative solutions to these problems. At the same time, with the growing number of cyber incidents in the grid, there still exists a need to develop attack-resilient algorithms for wide-area monitoring, protection, and control (WAMPAC) applications like the wide-area voltage control systems (WAVCS) for Flexible AC Transmissions Systems (FACTS) that lack in scalable and feasible solutions from the cybersecurity perspective. This dissertation proposes novel models and methodologies for: (1) Cybersecurity planning, and (2) Cybersecurity for system operation. The cybersecurity planning is achieved through cyber risk assessment and cybersecurity resource investment optimization for long-term cybersecurity of the grid using game theory and attack-defense trees. Cybersecurity for system operation consists of development of cyber anomaly detection and mitigation algorithms for flexible AC transmission system (FACTS) controller-based wide-area voltage control systems (WAVCS) using machine learning (ML), and software defined networking-based moving target defense network routing for achieving real-time cyber-physical security for grid operations. This is followed by hardware-in-the-loop (HIL) implementation and evaluation of these attack prevention, detection, and mitigation algorithms and methodologies showcasing their feasibility in a close to real-world environment. For cybersecurity planning, a novel approach involving a combination of game theory and attack defense trees (ADT) for optimal cybersecurity resource allocation in the smart grid is proposed. This methodology involves modeling of the cyber-physical smart grid substations as ADTs, defining attacker costs, defense costs, and attack probabilities for attack access points. Using game theoretical formulation, optimal defense strategies for the defender of the system to invest cybersecurity resources in the grid are obtained. Additionally, a game-theoretic framework is developed for quantitative cyber-physical risk assessment of the grid under a dynamically changing cyber threat space and uncertain behavior of cyber attackers which is further used to optimize investments in the smart grid's cybersecurity resources. The attacker, defender, and the smart grid system are modeled while incorporating attacker-stochasticity and federal guidelines for smart grid cybersecurity. This allows quantification of threat, vulnerabilities, and attack impact of the grid for quantitative risk assessment. The defender's budget to invest in the security resources in the grid is optimized based on the strategies leading to minimum system risk. The evaluation of the proposed solutions highlight the feasibility for practical implementation of these methodologies and algorithms in the smart grid, while taking the federal requirements and guidelines for smart grid security into consideration. For achieving cybersecurity for system operation, attack prevention, detection, and mitigation algorithms and methodologies are developed specifically for FACTS-based WAVCS. Anomaly detection and mitigation in the WAVCS are achieved using algorithms based on machine learning which involves offline training and testing of ML models with CPS datasets incorporating physics-based features that allow accurate distinction between system faults and cyber attacks. For attack prevention, a methodology based on software defined network (SDN)-based moving target defense (MTD) network routing is proposed that enables prevention of Denial of Service (DoS) type attacks on the smart grid communication system. Subsequently, these methodologies and algorithms are implemented and evaluated on an HIL testbed that allows for real-time attack prevention, detection, and mitigation of emulated cyber attacks on the WAVCS in a close to real-world environment. The results show highly accurate and efficient performance of the implemented algorithms and methodologies with the smart grid system operating within the NERC's system operation limits even in the presence of DoS and data integrity cyber attacks. This work opens up future research opportunities in other directions such as (1) Expanding cybersecurity planning methodologies to real-time cyber contingency analysis with different game formulations; and (2) Applying the cybersecurity for system operation algorithms to broader categories of wide-area control applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Identifying Opportunities and Recommendations for the Integration of Advanced Reactors for Industrial Heat and Electricity Users

Nuclear power in the United States has been used traditionally to provide baseload electric power to the grid. Advancements in nuclear power to create smaller and safer reactors have renewed interest in nuclear as a source of both heat and electricity for a variety of applications. There is great interest in coupling nuclear reactors with industrial applications because nuclear power is a low carbon energy source that can be utilized for process heating, hydrogen generation, on-site electricity demand, and more. Idaho National Laboratory is developing guidelines to identify and assist industrial heat and electricity decarbonization by integrating with nuclear power plants (NPPs) to provide clean, abundant, and dispatchable energy. Considerations include specific industrial hazards which impact NPP siting, heat transport requirements and associated technologies, and implementation feasibility based on site-specific demand profiles. To assess integration feasibility, facility process models are developed based on real data obtained from a survey of baseline requirements and process information from industrial facilities in the United States. An assessment of safety and siting requirements is also performed to determine how nuclear industrial pairings could meet licensing requirements for NPPs. In addition, site characterization of an industrial plant is essential to determining the feasibility and suitable integration methods for each industry. Characterization includes facility distance from the nearest population center, site size, rail or water transport availability, and proximity to undeveloped land. These characteristics are important to determine reactor- or industry-side design requirements for safe, efficient operation. The siting and technical data assessment will reveal opportunities for single-use nuclear integration and co-location opportunities for industries to share benefits from a single reactor. In addition to existing facilities, this “energy-park” style cooperation could include new construction like data centers which can cost-share energy investments or provide a stable demand-and-revenue stream to the investor. Deliverables will contain a library of documents and models to guide various industries toward understanding nuclear technologies based on their users’ needs. This paper is a summary of the current project status, and provides insights on suitable pairings for specific industries and reactor technologies

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

DEM and MELT In-Can Vitrification Process for Fukushima Daiichi Water Treatment Secondary Waste - 20034

Fukushima Daiichi Nuclear Power Station was severely damaged by a tsunami induced by the earthquake on March 11, 2011. A large amount of water treatment secondary waste has been generated from the purification work of contaminated water that consists of the water flowing into the reactor building. The Mid and Long-Term Road map specifies that solid waste at Fukushima Daiichi Nuclear Power Station should be stored safely and reasonably according to its characteristics. In order to meet this goal, a versatile treatment solution is needed, and the In-Can vitrification seems to be a suitable solution. The DEM and MELT In-Can vitrification process is being developed and qualified in France to treat waste arising from decommissioning and dismantling operations. This qualification is carried out through the consortium of the DEM and MELT project coordinated by CEA which gathers Orano, ECM technologies and Andra. The DEM and MELT In-Can vitrification process is a robust, simple and versatile in situ vitrification process. It is designed for high or intermediate level waste and is compact enough to be implemented in an existing facility or close to the waste to be treated. It is developed to treat liquid and solid waste, to produce a small amount of secondary waste and to minimize investment and operating costs. The DEM and MELT In-Can vitrification process is also developed with a modular design in order to be adapted to nuclear operators needs and requirements. The In-Can melting process has already been developed and fully qualified by the CEA for Alpha liquid waste and can be rated TRL 7 for this scope. The In-Can vitrification technology is considered as a qualified solution that could be applied for the treatment of waste resulting from the D and D work in Fukushima Daiichi Nuclear Power Station. The feasibility evaluation of the DEM and MELT In-Can vitrification process for Fukushima Daiichi water treatment secondary waste is a project led by Orano, CEA and ANADEC. This R and D project is performed by the funds from the Ministry of Economy, Trade and Industry as The Subsidy Program 'Project of Decommissioning and Contaminated Water Management'. This paper presents the first results of this feasibility evaluation, from the scenarios and glass formulation definition to the industrial implementation feasibility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Development of New Reactor Core Configuration for Power Uprate - Fuel Reload & Heat Processing Analyses, Core Design, System Safety Assessments, and Fuel Performance Analyses

With the passage of the Infrastructure Investment and Jobs Act in 2021 and the Inflation Reduction Act (IRA) in 2022, the United States stands at a critical juncture for the future of nuclear power. These landmark policies provide significant support for clean energy initiatives, positioning nuclear power as a key component of the nation’s strategy to reduce carbon emissions and achieve energy security. This growing emphasis on nuclear energy is driven by the need for reliable, low-carbon power sources as the country transitions away from fossil fuels. Federal policy, along with increasing state-level support, is encouraging investment in nuclear technology advancements to meet these demands. Building new nuclear power plants (NPPs), however, presents significant challenges due to high costs and long construction timelines. As a result, increasing the power output of existing NPPs through power uprates has emerged as a more feasible and cost-effective strategy. One key area of advancement is the development of accident-tolerant fuel (ATF), such as chromium-coated zirconium alloy cladding, which offers enhanced material performance, enabling power uprates in light water reactors (LWRs). Given the growing demand for nuclear energy fueled by federal policies and state initiatives, it is essential to evaluate the feasibility and benefits of significant power uprates in existing pressurized water reactors (PWRs) using advanced fuel technologies. The introduction of ATF concepts opens new opportunities for safely and economically achieving these power increases. Assessing whether these innovations can support substantial power uprates while maintaining operational safety is crucial to maximizing the potential of the nation’s existing nuclear infrastructure. This project aims to explore how power uprates can be achieved by boosting reactor thermal power output and optimizing reactor core design, while ensuring the safety and economic viability of NPPs. Specifically, it will focus on demonstrating the technical and economic feasibility of power uprates in a PWR using low 5-10% enrichment uranium (LEU+) high burnup (HBU) fuel combined with ATF concepts. In fiscal year 2024 (FY24), the research and development focus on building foundational models and conducting multi-physics performance and safety analyses to support the power uprate. The findings of the study would be shared through LWRS Seasonal Meetings, conferences and workshops with utility companies and researchers. These also serve as a basis for further study of fuel reloading optimization with ATF claddings.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Decarbonizing Industrial Heat and Electricity Applications Using Advanced Nuclear Energy

Idaho National Laboratory (INL) is investigating the technical pathways to assist industrial heat and electricity users to meet their decarbonization goals through integration with advanced nuclear power plants (NPPs). This project will deliver a library of process models and accompanying documents that guide specific industries in choosing potential nuclear technologies based on their needs. Considerations in providing this guidance include specific hazards from the industrial facility, heat transport requirements and associated technologies, and feasibility with site-specific demand profiles. The library of facility process models will be based on real data from industrial facilities in the United States. The industrial processes will be identified in this project based on the following: (1) operational heat characteristics that nuclear systems can provide, (2) sufficient energy requirements to merit the capital investment for nuclear plant construction, and (3) environmental benefits of replacing existing energy production with carbon-free nuclear power. Other decarbonization opportunities considered are the addition of nuclear-powered electrolysis processes or high-temperature electric heating where the thermal requirements exceed nuclear generation conditions. In addition to assessing the technical feasibility, INL is evaluating the impact of hazards introduced by the industrial facilities on the siting requirements of advanced NPPs. Site characterization of an industrial plant is essential to determine the feasibility and suitable integration methods for each industry. The assessment of siting and technical data will reveal opportunities for a single-use nuclear integration as well as integration of multiple industrial facilities with a single NPP.

02 PETROLEUM↗
DOE OSTI2026

NuMI Graphite Target Fin Removal Assembly

Materials scientists want to study the irradiated graphite target from the Neutrino at the Main Injector (NuMI) beam line. In order to gather these irradiated graphite fins from the target canister, it will have to be done remotely. Therefore, a removal assembly will need to be created in order to do this efficiently and well. This project aims to make progressive steps towards deploying the final target removal assembly. Furthermore, calculations related to the removal assembly design were done, and tests were planned to discover further information about the feasibility of this design. The main result from this project is the deflection of the cantilever arm, which is 0.354 inches due to the weight of the beam and cutting tool. Additionally, more results of this project are the testing assembly CAD model and the feasibility of design. This project concludes that there is still more work that needs to be done for the removal assembly to be deployed, but there were foundational steps that were made in the implementation of this design. Finally, there should be further steps and tests to determine the feasibility of this removal assembly.

Malovski, Azra [NIU, DeKalb]↗
DOE OSTI2021

OPFLearn.jl v0.1.2 5/18/2023 [SWR-21-109]

OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). It was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. Over time this input space tightens around the relaxed AC OPF feasible region to increase the percentage of feasible load profiles found while uniformly sampling the input space. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, "OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets". To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower ".m" files) to define the network the dataset is being created for.

Joswig-Jones, Trager↗
DOE OSTI2026

Integrated geological, economic, and risk assessment of underground hydrogen storage

Underground hydrogen storage (UHS) is a promising option to buffer variable renewable power and support the hydrogen economy. Yet this technology is early-stage, and key uncertainties remain about how coupled processes such as geochemical and geomechanical impacts affect long-term storage security. In this paper, we seek to integrate the results from a large, multi-scale research program to quantify core feasibility metrics and situate these studies within ongoing efforts. Through this work, we evaluate hydrogen recoverability during storage by assessing diffusive losses, losses to geochemical interactions and their subsequent impact on geomechanical properties, and losses to residual saturation during injection and withdrawal. Molecular and laboratory studies show that lithologic heterogeneity, pore geometry, and mineral surface chemistry govern hydrogen–rock interactions, controlling loss pathways. High-pressure coreflooding is used to estimate relative permeabilities and measure parameters needed for reservoir-scale sensitivity analyses. These core-scale experiments found early hydrogen breakthrough at low saturations driven by capillary and viscous fingering, which limits pore-space utilization at early times, while repeated injection and withdrawal cycles improve deliverability over time. Technoeconomic factors and purity requirements for end uses are also considered as part of our comprehensive feasibility analysis. Finally, we underscore the importance of geophysical monitoring and tailored injection strategies to maintain integrity and efficiency. Together, these results provide a quantitative foundation for safe, scalable deployment of UHS and highlight priorities for future integrated studies.

08 HYDROGEN↗
DOE OSTI2023

Techno-economic and environmental assessment of solar-based electrical vehicles charging stations integrated with hydrogen production

With the growing interest in adopting both commercial and residential electric vehicles (EVs) utilizing green renewable energy, the techno-economic assessment of EV charging stations with solar energy is a critical aspect of the transition to sustainable transportation. However, battery storage capacity for variable solar energy production is becoming increasingly less cost-effective due to the higher Lithium price. Complementing solar energy production and battery storage, the potential of combining green hydrogen fuel energy integration with solar energy for EV charging stations can provide a sustainable alternative to reach carbon-free transportation. This research aims to assess the technical and economic viability of grid-connected Photovoltaic (PV)-based EV charging stations across Kentucky based on existing EV load profiles. The study considers different PV system sizes, locations, orientations, and the impact of net metering policies and electricity tariffs on the profitability of the PV systems. Further, using excess PV energy, Lithium-Ion batteries will be charged, which will be assessed considering the techno-economic and environmental impacts of green EV charging stations. To further enhance green renewable energy production, we also investigated the feasibility of on-grid PV-based EV charging stations with Lithium-Ion batteries charged during low tariff periods. In comparison with these scenarios, we studied the potential benefits of integrating green hydrogen energy production using excess solar energy with and without governmental incentives. Furthermore, we assess the environmental impact of these green EV charging stations across Kentucky. Our study indicates that EV stations across Kentucky have similar techno-economic feasibility with insignificant deviation in the levelized cost of electricity, payback period, and PV energy fraction with/without Li-Ion batteries. However, with green hydrogen production, the marginal H 2 production cost indicates the first scenario (on-grid PV energy charging) is the most significant, roughly 10 USD/Kg, which is similar to 1.5 times higher than the second (charging during low-tariff periods) and the third scenarios (power grid to satisfy the demand deficit - approximately 6.5 USD/Kg). From the environmental perspective, the second scenario would be a good option for either hybrid EV/H 2 or EV charging stations in Kentucky, factoring in the hydrogen production cost and the carbon footprint.

08 HYDROGEN↗