Search NASA⌕ Search

SEARCH · Search NASA

Results for “grid life”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10

A Binomial Stochastic Framework for Efficiently Modeling Discrete Statistics of Convective Populations

Abstract Understanding the coupling between convective clouds and the general circulation, as well as addressing the gray zone problem in convective parameterization, requires insight into the genesis and maintenance of spatial patterns in cumulus cloud populations. In this study, a simple toy model for recreating populations of interacting convective objects as distributed over a two‐dimensional Eulerian grid is formulated to this purpose. Key elements at the foundation of the model include i) a fully discrete formulation for capturing discrete behavior in convective properties at small population sample sizes, ii) object age‐dependence for representing life‐cycle effects, and iii) a prognostic number budget allowing for object interactions and co‐existence of multiple species. A primary goal is to optimize the computational efficiency of this system. To this purpose the object birth rate is represented stochastically through a spatially aware Bernoulli process. The same binomial stochastic operator is applied to horizontal advection of objects, conserving discreteness in object number. The applicability to atmospheric convection as well as behavior implied by the formulation is assessed. Various simple applications of the BiOMi model (Binomial Objects on Microgrids) are explored, suggesting that important convective behavior can be captured at low computational cost. This includes i) subsampling effects and associated powerlaw scaling in the convective gray zone, ii) stochastic predator‐prey behavior, iii) the downscale turbulent energy cascade, and iv) simple forms of spatial organization and convective memory. Consequences and opportunities for convective parameterization in next‐generation weather and climate models are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Positive Role of Fluorine Impurity in Recovered LiNi 0.6 Co 0.2 Mn 0.2 O 2 Cathode Materials

Lithium-ion battery (LIB) recycling is considered as an important component to enable industry sustainability. A massive number of LIBs in portable electronics, electric vehicles, and grid storage will eventually end up as wastes, leading to serious economic and environmental problems. Hence, tremendous efforts have been made to improve the hydrometallurgical recycling process because it is the most promising option for handling end-of-life LIBs owing to its wide applicability, low cost, and high productivity. Despite these advantages, some extra elements (Al, Fe, C, F, and so forth) remain as impurities in the removal process and are retained in the solution, which is a great challenge to obtain high-quality cathode materials. In this work, the impacts caused by fluorine impurity on the LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) cathode are intensively investigated via hydrometallurgical coprecipitation for the first time. Our results show that up to 1 at. % fluorine impurity brings a positive influence on the recovered material due to a higher Ni 2+ ratio on the surface of cathode particles. In addition, the presence of fluoride ions during coprecipitation could lead to the formation of holes in cathode particles, which improves the rate capability and cyclability dramatically. Compared to the virgin material, the capacity of the NCM622 material with 0.2 at. % fluorine impurity is boosted by ~8% (167.7 mA h/g) with a remarkable capacity retention of 98.0% after 100 cycles at 0.33 C. Besides, the cathode with 0.2 at. % fluorine impurity shows a far better rate performance, especially at high rates (~7% increased at 5 C) than that of virgin. Furthermore, these results convince that a low concentration of fluorine impurity is desirable in the hydrometallurgical recycling process. More importantly, this study offers implications in the design of high-performance NCM622 cathode materials via coprecipitation production with ion doping in the near future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plant terpene specialized metabolism: complex networks or simple linear pathways?

From the perspectives of pathway evolution, discovery and engineering of plant specialized metabolism, the nature of the biosynthetic routes represents a critical aspect. Classical models depict biosynthesis typically from an end-point angle and as linear, for example, connecting central and specialized metabolism. As the number of functionally elucidated routes increased, the enzymatic foundation of complex plant chemistries became increasingly well understood. The perception of linear pathway models has been severely challenged. With a focus on plant terpenoid specialized metabolism, we review here illustrative examples supporting that plants have evolved complex networks driving chemical diversification. The completion of several diterpene, sesquiterpene and monoterpene routes shows complex formation of scaffolds and their subsequent functionalization. These networks show that branch points, including multiple sub-routes, mean that metabolic grids are the rule rather than the exception. This concept presents significant implications for biotechnological production.

60 APPLIED LIFE SCIENCES↗

Data for Carbon-negative Hydrogen: Aqueous Phase Reforming (APR) of Glycerol over NiPt Bimetallic Catalyst Coupled with CO2 Sequestration

Herein we report the production of high-pressure (19.3 bar), carbon-negative hydrogen (H2) from glycerol with a purity of 98.2 mol% H2, 1.8 mol% light hydrocarbons (mainly methane), and 400 ppm of CO. Aqueous phase reforming (APR) of 10 wt% glycerol solution was studied with a series of NiPt alumina bimetallic catalysts supported on alumina. The Ni8Pt1-450 catalyst had the highest hydrogen selectivity (95.6%) and the lowest alkanes selectivity (3.7%) of the tested catalysts. The hydrogen selectivity decreased in the order of Ni8Pt1-450 > Ni8Pt1-260 > Ni1Pt1-260 > Pt-260. The CO2 was sequestered with CaO adsorbent which formed CaCO3. We measured the adsorption capacity of the CaO adsorbent at different temperatures. Life cycle analysis showed that the APR of glycerol coupled with CO2 capture has net negative CO2 equivalent greenhouse gas emissions. The CO2 emissions are −9.9 kg CO2 eq./kg H2 and −50.1 kg CO2 eq./kg H2 when grid electricity and renewable electricity are used, respectively, and the CO2 is allocated respectively to the mass of products produced. The cost of this H2 (denoted as “green-emerald”) was estimated to be 2.4 USD per kg H2 when grid electricity is used and 2.7 USD per kg H2 when using renewable electricity. The cost of glycerol has the highest contribution of 1.71 USD per kg H2. Participation in the carbon credit markets can further decrease the price of the produced H2.

Catalysis↗

Complementary antibody lineages achieve neutralization breadth in an HIV-1 infected elite neutralizer

Broadly neutralizing antibodies (bNAbs) have remarkable breadth and potency against most HIV-1 subtypes and are able to prevent HIV-1 infection in animal models. However, bNAbs are extremely difficult to induce by vaccination. Defining the developmental pathways towards neutralization breadth can assist in the design of strategies to elicit protective bNAb responses by vaccination. Here, HIV-1 envelope glycoproteins (Env)-specific IgG + B cells were isolated at various time points post infection from an HIV-1 infected elite neutralizer to obtain monoclonal antibodies (mAbs). Multiple antibody lineages were isolated targeting distinct epitopes on Env, including the gp120-gp41 interface, CD4-binding site, silent face and V3 region. The mAbs each neutralized a diverse set of HIV-1 strains from different clades indicating that the patient’s remarkable serum breadth and potency might have been the result of a polyclonal mixture rather than a single bNAb lineage. High-resolution cryo-electron microscopy structures of the neutralizing mAbs (NAbs) in complex with an Env trimer generated from the same individual revealed that the NAbs used multiple strategies to neutralize the virus; blocking the receptor binding site, binding to HIV-1 Env N-linked glycans, and disassembly of the trimer. These results show that diverse NAbs can complement each other to achieve a broad and potent neutralizing serum response in HIV-1 infected individuals. Hence, the induction of combinations of moderately broad NAbs might be a viable vaccine strategy to protect against a wide range of circulating HIV-1 viruses.

60 APPLIED LIFE SCIENCES↗

From Bricks to Clicks: Mapping the White Space in Building Innovation

It is a critical national imperative to transform the buildings sector, yet innovation is impeded by deployment failures that leave promising technologies stranded. Conventional market reports and techno-economic analysis provide an insufficient understanding of markets and resource allocation for emerging building technologies. They omit crucial commercialization factors such as ecosystem maturity and adoption friction, where the coordinated participation of a network of suppliers, contractors, financiers, regulators, and integrators is required to scale solutions. This study addresses these gaps by introducing an evaluation framework grounded in front-line data from six years of the DOE's IMPEL incubator, comprising experience from 300 building-sector innovators and the adjacent, complex ecosystem. Our methodology synthesizes top-down market analysis with bottom-up, practitioner-level data across five megatrends: (M1) Affordable materials and industrialized construction; (M2) Healthy and efficient mechanical systems; (M3) Intelligent building operations; (M4) Buildings as grid assets; and (M5) High-density power and cooling for data centers and therein identify twelve "white space" technology opportunities. Next, we develop a multi-criteria scoring rubric to rank these opportunities based on parameters, i.e., Affordability, Quality of Life, Reliability, and Security, yielding composite ‘Demand’ and ‘Maturity’ indices. Our results indicate that the most significant white spaces may not be incremental products but a new class of ‘Ecosystem Enablers’, such as logistics platforms, orchestration layers, and automated compliance software that solve structural deployment gaps. This paper summarizes this transparent, evidence-based, practitioner-informed evaluation framework for policymakers and investors to re-evaluate policy and resource allocation and unlock scalable market transformation.

Singh, Reshma↗

Rechargeable alkaline zinc–manganese oxide batteries for grid storage: Mechanisms, challenges and developments

Rechargeable alkaline Zn–MnO 2 (RAM) batteries are a promising candidate for grid-scale energy storage owing to their high theoretical energy density rivaling lithium-ion systems (~400 Wh/L), relatively safe aqueous electrolyte, established supply chain, and projected costs below $100/kWh at scale. In practice, however, many fundamental chemical and physical processes at both electrodes make it difficult to achieve commercially competitive energy density and cycle life. In this paper, we present a detailed and timely analysis of the constituent materials, current commercial status, electrode processes, and performance-limiting factors of RAM batteries. We also examine recently reported strategies in RAM and related systems to address these issues through additives and modifications to the electrode materials and electrolyte, special ion-selective separators and/or coatings, and unconventional cycling protocols. We conclude with a critical summary of these developments and discussion of how future studies should be focused toward the goal of energy-dense, scalable, and cost-effective RAM systems.

25 ENERGY STORAGE↗

Development of Digital Twin Predictive Model for PWR Components: Updates on Multi Times Series Temperature Prediction Using Recurrent Neural Network, DMW Fatigue Tests, System Level Thermal-Mechanical-Stress Analysis

The long-term operation (LTO) of nuclear power plant (NPP) beyond their original design life of 40 years, can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Frequent NDE requirement may lead to frequent shutdown of the NPP. This in turn can lead to power outage and additional NDE-inspection-cost related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing more digital approach such as by using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. Towards this goal Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program is working on the development of a DT framework that can be used for real time environmental fatigue prediction of reactor components. The DT framework is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics such as finite element (FE) based modeling tools. Towards this overall goal, following are some of the major contributions made during the FY21: 1) Multiple 82/182 dissimilar metal weld (DMW) specimens (both solid-weld and joint-weld representing the actual reactor multi-metal nozzles) were fatigue tested. The resulting fatigue lives were compared to the NUREG-6909 based best-fit and design fatigue curves. Additionally, the results of 52/152 DMW fatigue specimens (which were recently tested at Republic of Korea under the sponsorship of International Nuclear Energy Research Initiative - INERI program) were compared to the NUREG-6909 based best-fit and design fatigue curves. From the comparison of 82/182 and 52/152 DMW test data with NUREG-6909 best-fit curve, most of the reported test data fall way away from the NUREG-6909 suggested best-fit or mean curve. The NUREG-6909 suggested best-fit curve is the best-fit curve of austenitic stainless steel and due to lack of enough data on Nickel-based welds, this is currently being used for predicting the life of Nickel-alloy-based welded components. However, the above observation may require higher scaling factor (e.g., ASME suggested factor of 20 on cycles rather than the current NUREG-6909 suggested factor of 12 on cycles) for scaling the austenitic-stainless-steel best-fit-curve for estimating the design or safe-life of a welded component. Accordingly, for example, if a DMW component experience a strain amplitude of 0.6% the PWR-water life of the component would be 52 cycles instead of 85 cycles. However, more DMW tests are required to further ascertain the above-mentioned observations. 2) A system level CAD and finite element model were developed which consists of reactor pressure vessel (RPV), part of steam generator (SG), part of pressurizer (PRZ), hot leg (HL), and surge line (SL). This is with detailed nozzle geometry and thermal-mechanical material properties of different metals to simulate realistic thermal-mechanical stress under connected system global thermal-mechanical boundary conditions. 3) Different system level heat transfer analyses were performed with estimation of relevant heat transfer coefficients. The resulting data were used in subsequent system level thermal-mechanical stress analysis and for generating spatial-temporal training and validation data for a system level digital-twin based temperature predictor. Transient heat transfer analyses were performed considering thermal boundary condition under design-basis (DB) loading and EDF (Électricité de France) data-based grid-load-following (EDF-GLF) loading cycles. 4) System level thermal-mechanical stress analysis was performed for identifying damage-prone hotspots and for future extension of the model for cyclic state prediction. From the system-level model simulation under DB loading cycle it is found that HL and the SL nozzle that connect to the HL can experience significant stress and strain and could be one of the weakest links in the overall reactor coolant system (RCS). 5) An AI/ML based DT model was developed for multi-time-series temperature prediction at any inside/outside thickness locations of PWR pressure boundary components. This is by using Recurrent-neural-network (RNN) and keras machine learning libraries. The RNN model was validated against two laboratory test-based data sets with one obtained through ANL’s in-air fatigue test system and other through PWR-water test loop. The experimentally validated DT model further validated against FE model results to predict thermal scarification related spatialtemporal temperatures at random locations of a component. The well validated DT model was then used for demonstrating spatial-temporal temperature prediction under 100+ years of reactor operation subjected to combined DB, EDF-GLF and randomized grid-load-following (RANDOMGLF) loading Cycles. The expert-elicitation DT model framework was developed assuming field/input/process measurements can be available from a few existing plant sensors and can readily be used by the NPP operators. The above temperature prediction model will feed to the next-step stress analysis model based on which the life of a component can be predicted in realtime, which is one of our future works.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Load-Shifting Strategies for Cost-Effective Emission Reductions at Wastewater Facilities

Significant hourly variation in the carbon intensity of electricity supplied to wastewater facilities introduces an opportunity to lower emissions by shifting the timing of their energy demand. This shift could be accomplished by storing wastewater, biogas from sludge digestion, or electricity from on-site biogas generation. However, the life cycle emissions and cost implications of these options are not clear. Here, we present a multiobjective optimization framework for comparing cost- and emission-minimizing load-shifting strategies at a California case study facility with a relatively low carbon intensity grid and high spread in peak and off-peak electricity prices. We evaluate cost and emission trade-offs from the optimal flexible operation of both existing infrastructure and optimally sized energy flexibility upgrades. We estimate energy-related emission reductions of up to 9.0% with flexible operation of existing infrastructure and up to 16.8% with optimally sized storage upgrades. Only a fraction of these potential savings are realized under actual industrial energy tariffs and the EPA’s recommended social cost of carbon. Energy flexibility may hold promise as a short-term emission-saving solution for the wastewater sector, but the extent of savings is heavily dependent on the cost of carbon, electricity tariffs, and emission intensity of the regional electricity grid.

climate↗

Designing Dynamic Wireless Power Transfer Corridors for Heavy Duty Battery Electric Commercial Freight Vehicles

The use of wireless power transfer systems, consisting of inductive electrical coils on the vehicle and the power source may be designed for dynamic operations where the vehicle will absorb energy at highway speeds from transmitting coils in the road. This has the potential to reduce the onboard energy storage requirements for vehicles while enabling significantly longer missions. This paper presents an approach to architecting a dynamic wireless power transfer corridor for heavy duty battery electric commercial freight vehicles. By considering the interplay of roadway power capacity, roadway and vehicle coil coverage, seasonal road traffic loading, freight vehicle class and weight, vehicle mobility energy requirements, on-board battery chemistry, non-electrified roadway vehicle range requirements, grid capacity, substation locations, and variations in electricity costs, we minimize the vehicle TCO by architecting the electrified roadway and the vehicle battery simultaneously. The idea optimizes battery size and chemistry so that the depth of discharge between recharge events and expected life are balanced, thus fully utilizing the energy available throughout the course of the battery system's life. The approach is illustrated by applying it to the I-75 freight corridor, where the framework developed may be expanded and applied to a larger interstate system, expanded regional corridor, or other transportation network.

Sujan, Vivek↗

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗

Renewable hydrogen horizon: Geospatial techno-economic feasibility and life cycle greenhouse gas analysis in the Middle East and North Africa

Renewable hydrogen is receiving increasing attention for its potential as a flexible energy carrier in sectors such as transportation and industry. Specific cost and carbon intensity (CI) of renewable hydrogen production vary largely based on the location, owing to differences in renewable energy resources, as well as the supply chain dynamics. This study maps the techno-economic and life cycle greenhouse gas emissions of renewable hydrogen production in the Middle East and North Africa region, leveraging abundant solar and wind resources. The work investigates the variability in hydrogen costs and CI, optimally sizing proton-exchange membrane (PEM) electrolyzers to account for partial and cyclic loading, and explores standalone versus grid-connected systems. PEM capacity ratios of 52 %–63 % for photovoltaic (PV) systems and 28 %–82 % for wind systems were identified as optimal, with hydrogen production costs ranging from $\$3.8$-$\$4.8$/kg for PV and $2.0-$7.0/kg for wind. CIs span from 1.9 to 3.7 kg CO 2 ,eq /kg H 2 for PV and 0.4–7.7 kg CO 2,eq /kg H 2 for wind systems. The study highlights significant cost and CI reductions achievable with technological advancements and co-product revenue from oxygen and excess electricity sales.

Carbon Intensity↗

Identification of pressure points in modern power systems using transfer entropy

Power shortages disrupt daily life, economic activity, and essential services. In modern power systems, weather is an increasingly important driver of reliability: high temperatures raise demand and limit transmission capacity, and calm or cloudy periods reduce wind and solar supply. Using a data-driven analysis, this study identifies grid infrastructure whose operating patterns help predict power shortages. The results show that reliability risks often emerge from interacting stresses across generation, transmission, and demand, rather than from single bottlenecks. By clarifying how system stress propagates through the grid, this diagnostic perspective helps explain why shortages occur under specific conditions and can complement traditional planning and operational tools to support adaptive reliability strategies, targeted monitoring, and coordinated infrastructure investments.

power systems↗

Defect-free-induced Na + disordering in electrode materials

For reaching high-performance of electrode materials, it is generally believed that understanding the structure evolution and heterogeneous alignment effect is the key. Presently, a very simple and universally applicable self-healing method is investigated to prepare defect-free Prussian blue analogs (PBAs) that reach their theoretical capacity as cathode materials for sodium-ion batteries (SIBs). For direct imaging of the local structure and the dynamic process at the atomic scale, we deliver a fast ion-conductive nickel-based PBA that enables rapid Na + extraction/insertion within 3 minutes and a capacity retention of nearly 100% over 4000 cycles. This guest-ion disordered and quasi-zero-strain nonequilibrium solid–solution reaction mechanism provides an effective guarantee for realizing long-cycle life and high-rate capability electrode materials that operate via reversible two-phase transition reaction. Unconventional materials and mechanisms that enable reversible insertion/extraction of ions in low-cost metal–organic frameworks (MOFs) within minutes have implications for fast-charging devices, grid-scale energy storage applications, material discovery, and tailored modification.

36 MATERIALS SCIENCE↗

Business Models for Scaling Demand Flexibility Volume III – Stakeholder ecosystem management challenges, and lessons learned from U.S. programs

Load growth at the grid edge is driving increased attention to the distribution system and its ability to enable customer technology adoption in an affordable and timely manner. Key industry stakeholders, including electric utilities and regulators, can benefit from strategies to manage and balance customer needs with infrastructure investments, such as demand flexibility. This report focuses on demand flexibility—the ability to reduce, shift, shed, generate, or modulate loads in response to building and grid needs—to reduce the need for costly grid upgrades by deferring investment needs and increase system reliability by shifting electricity usage during periods of high risk. Specifically, we focus on the emerging characteristics of business models for demand flexibility as a framework to understand how demand flexibility programs generate value. In this report, we focus on demand flexibility program stakeholder ecosystem management strategies, which provide information on value delivery and describe how program implementers leverage partner capabilities and collaborate to deliver customer and grid benefits. This report discusses the role of stakeholder ecosystem management in demand flexibility programs, identifies existing challenges to effective stakeholder management, and describes lessons learned. This report is part of a series that includes reports on value propositions, customer relationship management strategies, and program life cycle.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Carbon Footprint Analysis of Floating PV Systems

This report, conducted by the Dutch research organization TNO, presents the first detailed life cycle inventory (LCI) analysis of operational floating photovoltaic (FPV) systems. The study, focusing on two operational systems in Western Europe, reveals that FPV systems on small inland water bodies can be a valuable complement to ground-mounted PV systems in terms of greenhouse gas emissions reduction. If PV module degradation is limited, these systems' carbon footprint is 3-4 times lower than the EU grid mix target for 2030. The report compares two FPV systems with different floater compositions (HDPE and steel/HDPE) to hypothetical ground-mounted systems, using comprehensive background data. The findings highlight the necessity for long-term monitoring and thorough environmental assessments. Josco Kester, a scientist at TNO, underscores the potential environmental benefits of these systems, which could enhance the adoption of renewable energy technologies.

14 SOLAR ENERGY↗

Carbon-negative hydrogen: aqueous phase reforming (APR) of glycerol over NiPt bimetallic catalyst coupled with CO 2 sequestration

Herein we report the production of high-pressure (19.3 bar), carbon-negative hydrogen (H 2 ) from glycerol with a purity of 98.2 mol% H 2 , 1.8 mol% light hydrocarbons (mainly methane), and 400 ppm of CO. Aqueous phase reforming (APR) of 10 wt% glycerol solution was studied with a series of NiPt alumina bimetallic catalysts supported on alumina. The Ni 8 Pt 1 -450 catalyst had the highest hydrogen selectivity (95.6%) and the lowest alkanes selectivity (3.7%) of the tested catalysts. The hydrogen selectivity decreased in the order of Ni 8 Pt 1 -450 > Ni 8 Pt 1 -260 > Ni 1 Pt 1 -260 > Pt-260. The CO 2 was sequestered with CaO adsorbent which formed CaCO 3 . We measured the adsorption capacity of the CaO adsorbent at different temperatures. Life cycle analysis showed that the APR of glycerol coupled with CO 2 capture has net negative CO 2 equivalent greenhouse gas emissions. The CO 2 emissions are –9.9 kg CO 2 eq./kg H 2 and –50.1 kg CO 2 eq./kg H 2 when grid electricity and renewable electricity are used, respectively, and the CO 2 is allocated respectively to the mass of products produced. The cost of this H 2 (denoted as “green-emerald”) was estimated to be 2.4 USD per kg H 2 when grid electricity is used and 2.7 USD per kg H 2 when using renewable electricity. The cost of glycerol has the highest contribution of 1.71 USD per kg H 2 . As a result, participation in the carbon credit markets can further decrease the price of the produced H 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗