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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ELECTRIFICATION OF A HEAVY-DUTY OFF-ROAD MATERIAL HANDLER: ENERGY SAVINGS AND EMISSION REDUCTIONS

Federal regulations are driving the adoption of electrification technologies to reduce carbon dioxide equivalent (CO2e) emissions, a metric that quantifies the global warming potential of various greenhouse gases in terms of carbon dioxide (CO2). Although no specific CO2 regulations exist for heavy-duty off-road machines, future reductions are likely, given stricter emissions standards for on-road vehicles. The heavy-duty off-road sector offers significant fuel-saving potential, as its focus has traditionally been on reliability and performance rather than fuel efficiency. This dissertation examines fuel and CO2e savings opportunities on a heavy-duty off-road material handler, the Pettibone Cary-Lift 204i, from stock configuration to simple modifications to a complete teardown and reconfiguration of the machine with a plug-in series hybrid architecture using electrified hydraulics. The study begins by modeling the baseline machine’s fuel and energy consumption, calibrating with experimental data from custom operating cycles. An energy analysis identifies key areas for fuel savings. Two simple powertrain modifications result in a combined 16.2% fuel savings. Next, a Pugh-style analysis narrows a list of electrified architectures, leading to high-fidelity models that evaluate total lifetime CO2e and costs. Higher electrification levels reduce CO2e emissions but increase costs, and electricity grid emissions significantly impact CO2e for plug-in architectures. A plug-in series hybrid is chosen for the project. In its base control form, 49% fuel and 29% CO2e savings are expected from the plug-in series hybrid compared to the baseline machine. Further savings are pursued through regenerative braking (6.3%) and load-following hydraulic control (17.8%), totaling 24.1% fuel savings, and leading to a total of 61% fuel and 41% CO2e savings compared to the baseline. Battery chemistries and charging strategies are also analyzed for cost and CO2e impacts, finding LFP batteries as superior due to longevity, and overnight level 2 charging usually at a lower cost but resulting in higher emissions than opportunity DC fast-charging (DCFC). DCFC emissions are highly dependent on grid emissions, and DCFC cost is highly dependent on grid demand charges. Finally, artificial intelligence is applied to operating cycle recognition. Neural network accuracy ranges from 81% to 99%, with applications to worksite efficiency and safety improvements.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Providing Levelized Cost and Waiting Time Inputs for HDV Hydrogen Refueling Station Planning: A Case Study of U.S. I-75 Corridor

Widespread use of diesel fuels in freight transportation leads to greenhouse gas (GHG) emissions that play an important role in air pollution. The air pollution, as well as the energy crisis, drives the transition from diesel fuel to cleaner and more energy-efficient fuels such as hydrogen fuels. With such a transition, the strategic planning and optimization of supporting refueling infrastructure along the national highway for heavy-duty vehicles (HDVs) become a necessity. Cost and service level are two essential factors to be considered in hydrogen refueling station location and capacity optimization. The service level in this study is assessed by the delay (waiting time) at fueling stations as well as the fueling demand fulfilled. To this end, this study presents a methodology to provide waiting time (delay) and levelized hydrogen fuel cost inputs under different station configurations (number of dispensers and fill rates) for hydrogen refueling station planning. Determining the station configurations based on the trade-off between the two inputs is further discussed. Particularly, this study points out that the levelized cost and waiting time are affected by hourly demand patterns and estimates the two inputs under different peak hour fueling demand scenarios. The results suggest that, with the same daily demand, the cost, as well as the waiting time, increases obviously with the peak hour demand. In the case study, the cost grows at least 30% when the peak hour visit frequency of the daily total visits increases from 5% (evenly distributed pattern) to 10% (the most common pattern for existing diesel fueling stations along I-75). Accounting for this peak hour effect in hydrogen refueling station planning is recommended. Overall, the waiting time model and cost analysis provide key inputs for optimizing hydrogen refueling station location and configurations based on anticipated refueling demand patterns. The paper is the second in a series that aims to build a comprehensive modeling plan and optimize hydrogen refueling infrastructure along the Interstate 75 (I-75) corridor for HDVs.

Liu, Yuandong↗
DOE OSTI2024

A Hybrid Heavy Duty Diesel Power System for Off-Road Applications—Concept Validation

A multiyear power system R&D program was completed with the objective of developing an off-road hybrid heavy duty diesel engine with front end accessory drive-integrated energy storage. This system was validated to deliver 10.5–25.6% reduction in fuel consumption over current Tier 4 Final-based 18L diesel engines, over various off-road machine application cycles. The power system consisted of a downsized heavy-duty diesel 13L engine containing advanced combustion technologies, capable of elevated peak cylinder pressures and thermal efficiencies, thermal barrier coatings, exhaust waste heat recovery via SuperTurbo™ turbocompounding, and hybrid energy assisting and recovery through both mechanical and electrical systems. Following the concept definition, design, and analysis phases of the program, the final phase focused on building and validating the performance and efficiency in laboratory tests. While aspects of the system such as start/stop and reduced off-road cooling package energy losses were only analytically evaluated, the main 13L concept engine with full hybrid system was successfully built and tested in steady-state and in transient certification and real-world application cycles. Extensive simulations in Caterpillar's DYNASTY™ software environment utilized the validation test data to assess performance more fully and confidently over varied cycles and strategies. An average fuel consumption reduction of 17.9% was realized, and the majority (~13%) of the benefit stemmed from the core concept 13L engine. In conclusion, a total cost of ownership analysis provides context to commercial viability and where adoption focus should be placed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Understanding how single-atom site density drives the performance and durability of PGM-free Fe–N–C cathodes in anion exchange membrane fuel cells

One of the most important needs for the future of low-cost fuel cells is the development of highly active platinum group metal (PGM)-free catalysts. For the oxygen reduction reaction, Fe–N–C materials have been widely studied in both acid and alkaline media. However, reported catalysts in the literature show quite different intrinsic activity and in-cell performance, despite similar synthesis routes and precursors. Here, two types of Fe–N–C are prepared from the same precursor and procedure – the main difference is how the precursor was handled prior to use. It is shown that in one case Fe overwhelmingly existed as highly active single-metal atoms in FeN4 coordination (preferred), while in the other case large Fe particles coexisting with few single metal atoms were obtained. As a result, there were drastic differences in the catalyst structure, activity, and especially in their performance in an operating anion exchange membrane fuel cell (AEMFC). Additionally, it is shown that catalyst layers created from single-atom-dominated Fe–N–C can have excellent performance and durability in an AEMFC using H 2 /O 2 reacting gases, achieving a peak power density of 1.8 W cm -2 – comparable to similar AEMFCs with a Pt/C cathode – and being able to operate stably for more than 100 h. Finally, the Fe–N–C cathode was paired with a low-loading PtRu/C anode electrode to create AEMFCs (on H 2 /O 2 ) with a total PGM loading of only 0.135 mg cm -2 (0.090 mg Pt cm -2 ) that was able to achieve a very high specific power of 8.4 W mg PGM -1 (12.6 W mg Pt< sup>-1 ).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Microchannel Reactor for Ethanol to Butene: CRADA 503 [Abstract only]

A key challenge facing most bioprocessing operations is that multiple unit operations are required, thereby resulting in complex, energy-intensive, and expensive processes. Further, biomass transportation costs drive the need for smaller, distributed processing plants. To incorporate the smaller scales desirable for biomass, novel processes must be developed with reduced capital costs. With over 20 years of experience in the development and commercialization of microchannel reactor technology, Oregon State University will partner with Pacific Northwest National Laboratory to demonstrate a microchannel reactor with lower capital costs for an alcohol-to-jet (ATJ) process technology that is currently being commercialized by LanzaTech. Ethanol can be produced from biomass feedstocks such as LanzaTech’s proprietary biochemical process using carbon from a number of possible feedstocks; syngas generated from biomass resources (e.g., MSW, organic industrial waste, agriculture waste) or reformed biogas, or from other biomass feedstocks such as corn kernel fiber. Ethanol then undergoes catalytic dehydration to form ethylene followed by a two-step oligomerization, hydrogenation, and fractionation to control the hydrocarbon product slate to the jet-range. Successful process development aided by a market pull for low carbon aviation fuel has spurred scale-up and commercial demonstration. However, Sustainable Aviation Fuel is a very price sensitive market and improved economics through process intensification will make the current ATJ process even more attractive. Recent efforts at PNNL have culminated in the development of a new catalyst technology for the conversion of ethanol to n-butene-rich olefins. A greater than 90% conversion, total olefin selectivity of 80-90% (n-butene selectivity ~60%), and good stability over a 100 hour test duration has been demonstrated at the bench scale. Producing butene-rich olefins directly from ethanol with high yield is new and impactful because the higher olefins can be selectively oligomerized to distillate-range hydrocarbons, thus eliminating one process step from the current ATJ process. Further, coupling the severely endothermic ethanol dehydration with exothermic C-C bond formation results in more energy efficient processing. Additional intensification and energy savings will stem from incorporating this new ethanol to n-butene catalyst technology within the ATJ process implemented using a microchannel reactor platform. Due to recent advances in microchannel manufacturing methods and associated cost reductions we believe the time is right to adapt this technology toward new commercial bioconversion applications.

02 PETROLEUM↗
DOE OSTI2020

An Assessment of the Influence of Uncertainty in Temporally Evolving Streamflow Forecasts on Riverine Inundation Modeling

Continental-scale river forecasting platforms forecast streamflow at reaches that can be used as boundary conditions to drive a local-scale flood inundation model. Uncertainty accumulated during this process stems not only from any part of the forecasting chain but can also be caused by the daily variations in weather forcing that keeps evolving as the event advances. This work aims to examine the influence of the evolving forecast streamflow on predicting the maximum inundation for extreme floods. A diagnostic case study was made on the basis of a hindcast of Hurricane Matthew striking the eastern U.S. in 2016. The U.S. National Water Model was one-way coupled to a hydrodynamic inundation model through a developed automated workflow. Although the river forcing has significantly mismatched hydrographs versus observations, the simulated peak water surface elevations and maximum extents were validated to be comparable with the observations, which indicates that the inundation model may not be sensitive to the inherited uncertainty from the weather forcing. Moreover, the uncertainty of the forecast streamflow time series caused only one order of magnitude fewer variations in inundation prediction; this dampening effect may become clearer for extreme events with large areas inundated. In addition, the forecast total volume of stream discharge appears to be an important metric for assessing the performance of river forcing for inundation mapping, as a linear correlation between the total volume and the accuracy of the predicted peak water surface elevation and maximum extent was found, with the coefficients of determination all above 0.8. Extra best-practice experience of running similar operational tasks demonstrated the tradeoff between the cost and accuracy gain.

flood, national water model, RIFT↗
DOE OSTI2022

Single-column cryogenic air separation: enabling efficient oxygen production with rapid startup and low capital costs—application to low-carbon fossil-fuel plants

The rapid integration of intermittent renewable sources into the electricity grid is driving the need for more flexible, low-carbon fossil-fuel plants with lower capital costs. This then drives the need to improve the cryogenic air separation unit (ASU). To address this changing landscape, we explore a Praxair single-column ASU (PSC-ASU) design with the goal of reducing costs and improving flexibility, compared to a conventional double-column ASU. The PSC-ASU incorporates partial air condensation and air pre-separation in the bottom reboiler with a phase separator as well as N2-enriched vapor condensation in the upper reboiler to decrease energy consumption, as compared to Linde's single-column ASU. All three of the above-mentioned ASU designs are simulated in Aspen Plus and analyzed. An economic analysis is applied to evaluate the relative cost savings of the PSC-ASU compared to the double-column ASU. Results suggest that the specific energy consumption of the PSC-ASU is significantly lower than that of Linde's single-column ASU due to a drastically improved oxygen recovery rate. Although this improved oxygen recovery rate is still lower than that of the double-column ASU, the required pressure ratio of the main air compressor is 21% lower than that of the double-column ASU. As a result, the specific energy consumption of the PSC-ASU is only 1.9% greater than that of the double-column ASU for producing 95.1 mol% O2. However, the PSC-ASU reduces the hourly capital cost by 19% due to the elimination of a high-pressure column. This would effectively decrease the total hourly cost of the ASU, and thus the total hourly cost of low-carbon, fossil-fuel power plants that require oxygen.

Cheng, Mao↗
DOE OSTI2021

Single-column cryogenic air separation: Enabling efficient oxygen production with rapid startup and low capital costs—application to low-carbon fossil-fuel plants

The rapid integration of intermittent renewable sources into the electricity grid is driving the need for more flexible, low-carbon fossil-fuel plants with lower capital costs. This then drives the need to improve the cryogenic air separation unit (ASU). To address this changing landscape, we explore a Praxair single-column ASU (PSC-ASU) design with the goal of reducing costs and improving flexibility, compared to a conventional double-column ASU. The PSC-ASU incorporates partial air condensation and air pre-separation in the bottom reboiler with a phase separator as well as N 2 -enriched vapor condensation in the upper reboiler to decrease energy consumption, as compared to Linde’s single-column ASU. All three of the above-mentioned ASU designs are simulated in Aspen Plus and analyzed. An economic analysis is applied to evaluate the relative cost savings of the PSC-ASU compared to the double-column ASU. Results suggest that the specific energy consumption of the PSC-ASU is significantly lower than that of Linde’s single-column ASU due to a drastically improved oxygen recovery rate. Although this improved oxygen recovery rate is still lower than that of the double-column ASU, the required pressure ratio of the main air compressor is 21% lower than that of the double-column ASU. As a result, the specific energy consumption of the PSC-ASU is only 1.9% greater than that of the double-column ASU for producing 95.1 mol% O 2 . However, the PSC-ASU reduces the hourly capital cost by 19% due to the elimination of a high-pressure column. This would effectively decrease the total hourly cost of the ASU, and thus the total hourly cost of low-carbon, fossil-fuel power plants that require oxygen.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

A robust deep learning workflow to predict multiphase flow behavior during geological C O 2 sequestration injection and Post-Injection periods

Simulation of multiphase flow in porous media is essential to manage the geologic CO 2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO 2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO 2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO 2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO 2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO 2 as a deep learning feature, leads to the most accurate prediction of CO 2 saturation. For the post-injection period, it is key to use cumulative CO 2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.

58 GEOSCIENCES↗
DOE OSTI2022

Silver Nanowire-Indium Zinc Oxide Composite Flexible Transparent Conducting Electrodes Made by Spin- coating and Photonic Curing

Realizing high-throughput, low-cost perovskite solar cell (PSC) manufacturing is highly sought-after in photovoltaic (PV) research in recent years. To fully achieve roll-to-roll (R2R) manufacturing of PSCs, it is important to consider the flexible transparent electrode (TE). PET/ITO is a commonly used substrate for making flexible PSCs. When optimizing transparent conducting materials, there is a tradeoff between sheet resistance (Rsh) and optical transparency. Because commercial PET/ITO substrates are made with slow (~1 m/min) vacuum deposition processes, they tend to be expensive. Therefore, it would be advantageous to develop a high-throughput, R2R compatible, solution-deposition approach for fabricating the TE on PET substrates. While various solution-deposition processes, such as blade coating or slot-die coating, can achieve the desired web speed of > 10 m/min, there is still a need to improve the post-deposition annealing step. One promising post-deposition processing technique is intense-pulsed-light processing, also known as photonic curing. Photonic curing delivers short (0.01 – 100 ms) pulses of broadband (200 – 1500 nm) light from a xenon flash lamp to the samples. Any materials in the sample stack that absorb light will convert the impinging light pulse into heat within the sample, which drives changes in the sample (calcination, phase change, crystallization, etc.). Photonic curing has three main advantages over thermal annealing: 1. Faster processing speed (milliseconds or seconds). 2. Compatibility with plastic substrates. 3. Smaller physical footprint and less wasted energy. Since the light pulses are on for a short time, the intensity can be high while the total energy delivered to the sample is low, minimizing damages to the plastic substrates. In this work, a hybrid TE material is fabricated on PET substrates using photonic curing. The hybrid TE material contains a layer of silver nanowires (AgNWs) and a layer of metal-oxide (InOx, ITO, IZO, etc.). The AgNWs increase the light absorbed by the film during the photonic curing process, which leads to higher processing temperatures, possibly improving the conversion of the metal-oxide layer. The AgNWs also enhance the electrical conductivity of the final TE layer after photonic curing. A AgNW and metal-oxide bilayer is formed by spin coating each solution onto the PET substrate sequentially followed by a single photonic curing process. We use average optical transmittance (Tavg) from 400 to 700 nm and average Rsh to evaluate the TE performance. The following photonic curing parameters are varied to optimize Tavg (maximize) and Rsh (minimize): Pulse voltage, pulse envelope, number of micro-pulses, duty cycle, number of pulses, and pulse repetition rate. Preliminarily, we also observe a significant impact on the TE properties by the volume of AgNW deposited during the spin coating deposition step. Using dispense volumes of 80 µL and 20 µL, we achieve samples with Tavg = 73%, Rsh = 19 Ω/sq, and roughness = 9 nm, and Tavg = 83%, Rsh = 58 Ω/sq, and roughness = 5.6 nm, respectively, after photonic curing.

14 SOLAR ENERGY↗
DOE OSTI2021

Development of a new control rod drive mechanism design for the ISU AGN-201M reactor

The Aerojet General Nucleonics (AGN) model 201-Modified, known as the AGN-201M reactor, plays an essential role in the educational and research activities at Idaho State University (ISU). The ISU AGN-201M's original Control Rod Drive Mechanism (CRDM) has been in operation for more than fifty years with no large-scale redesigns. The CRDM is required to eject the fuel rods within one second during a SCRAM event (also known as a 'reactor trip') and adjust the control rods' insertion speed, and keeps the rod insertion sequence correct. The existing control rod drive mechanisms meet these criteria but experience a few concerns due to aging. Concerns include complex maintenance and costly repairs for old electromechanical components, rod position feedback errors, and the impediment of the plate during a SCRAM due to binding of the lead screws of the existing mechanism. During a binding event, the drive mechanism becomes locked, preventing the control rod's magnetic plate from moving in or out under the reactor's normal and emergency operating conditions. Although, the binding has no effect on the ability of the rod to exit the core during the SCRAM. To counteract the concerns and issues with the current CRDM, a new design has been proposed using newer components and a simplified design. The new design utilizes more advanced electric and mechanical components that are commercially available. The new CRDM system is divided into four main aspects: (1) control rod movement design (motor, lead screw, guide rods), (2) control rod ejection (springs, electromagnet), (3) control rod position and feedback (position transducer, microswitches), and (4) material selection and structural analysis. The new design aims to reduce the overall complexity and probability of failure to improve the reactor's overall reliability. With proper material selection and improved structural design, the new drives are lighter with little to no change in structural integrity. The new control rod drive mechanism eliminates binding scenarios by using a single lead screw and implementing additional guide rods. An advanced linear position sensor and microswitches replace the existing and aging synchro system for accurate rod position feedback resulting in better reactivity control. The new design meets the reactor's operational limits by having an average reactivity insertion of 0.065% Δk/k per second, which corresponds to a total control rod insertion time of 19.23 s, while the control rod's ejection time remains less than one second during a SCRAM event. The new design ensures the reactor's long-term viability for educational and research activities by increasing the reliability and safety of operation for years to come.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Liquid Salt Combined-Cycle Pilot Plant Design

The work described in this report is responsive to the Office of Fossil Energy program ‘Energy Storage for Fossil Power Generation.’ This Phase I report has been prepared by Pintail Power LLC, with support from Nexant ECA, Electric Power Research Institute (EPRI) and Southern Company Services as a deliverable for the U.S. Department of Energy for NETL Award DE-FE-00320016. The Liquid Salt Combined Cycle™ (LSCC™) technology provides large-scale energy storage integrated with Fossil Electric Generating Units (FEGUs) to meet critical needs in the energy transition by providing: • the lowest cost large-scale storage for time-shifting of renewable energy, • superior fuel efficiency to reduce GHGs from dispatchable resources, • flexible capacity and ramping to balance variability of wind and solar resources, • essential grid stability services to assure reliability of a low-carbon grid. The LSCC approach: • employs equipment that has already been proven in utility service, • uses safe, non-toxic, non-degrading, perpetual-life storage medium, • leverages and repurposes existing FEGU assets, • expands the value stack of energy storage to reduce market, financing, and commodity risks. Pintail Power has developed the LSCC technology to meet the need for reliable, efficient, and cost-effective integration of Variable Renewable Energy (VRE) into a low-carbon electric grid by coupling proven thermal energy storage with proven gas turbines, steam turbines, and heat transfer equipment. This novel approach is intended to address the key issues facing the grid and operators of renewable and fossil generating units including: • Overgeneration and curtailment of renewables, • Need for fast ramping dispatchable resources, • Improved efficiency and flexibility of fossil units, • Additional peaking capacity to support electrification of transportation and heating, • Provision of reliability services to support high penetration of VRE, especially synchronous inertia and fast frequency response. A Technology Readiness assessment by EPRI confirmed that LSCC technology consists of commercially proven hardware used in industrial and utility applications. Although the novel LSCC approach has not yet been demonstrated as a complete system, interfaces between major components have been conservatively specified. A Phase III pilot is planned to demonstrate equipment integration and operation. The patented innovation is removal of the evaporator section from the exhaust heat recovery system, with the evaporation performed by stored energy in a separate steam generator. This arrangement couples renewable and fossil power generation via long-duration energy storage to deliver cost, performance, and operational synergies, including superior charging and discharging flexibility, reduced fuel consumption and lower CO 2 emissions compared to conventional Combined Cycle Power Plants, and low-cost, large-scale energy storage. The LSCC technology is composed of proven equipment integrated with gas turbine exhaust heat in a novel system. During charging, electric heaters raise the salt temperature as it flows from the Cold Salt Tank to the Hot Salt Tank. During discharging, hot salt produces steam from feedwater that is heated with gas turbine exhaust, which also superheats steam to drive a steam turbine. LSCC technology can be added to any combustion-turbine to integrate renewable energy, provide needed grid services, and increase the value of fossil electric generating units based on the technology’s following attributes: • Long-duration storage enables time-shifting of VRE to avoid curtailment and impairment of renewable assets. • Long storage duration combined with fast-charging capability increases arbitrage opportunities by storing more energy when the price is low and discharging more hours when the price is high. • Long storage duration allows resource adequacy to be supplied across multiple days to increase reliability and reduce risk. • The stored energy reduces fuel heat rate and GHG emissions, and increases merit, so the LSCC dispatches earlier and longer to increase the plant’s capacity factor and asset value. • The stored energy enables pre-heating and startup of the steam cycle, without operating the gas turbine, to enable fast startup and ramping when dispatched for discharge. • The steam turbine can operate without the gas turbine so it can provide valuable synchronous inertia during charging without consuming fuel. • Fast frequency response and regulation services can be provided during charging using solid-state heater and pump controls to vary the charge power input in response to grid signals. • The LSCC system can be configured for resilience including black start, islanded/micro-grid operation, and even self-recharging of storage using either gas turbine power or gas turbine exhaust heat. The commercialization plan is to add LSCC technology to existing simple cycle gas turbine power plants with the 50MW GE LM6000 aero-derivative gas turbine as the reference design basis. A Techno-economic assessment of the reference design evaluated the benefits (Levelized Avoided Cost of Energy) and costs (Levelized Cost of Energy). The plant definition included all major systems and budgetary vendor quotes. Pintail Power and NexantECA developed the overall cost estimate for the LSCC plant up to the total plant cost level, following the DOE-NETL cost estimate guidelines at AACE Class 3 (-20%/+30%). This includes the equipment cost, bulk material, direct and indirect labor costs to arrive at the bare erected cost. Engineering costs are factored from the BEC and added to it to arrive at the EPC cost. Process and project contingencies were then factored from the EPC cost and rolled-up to yield the total plant cost of $\$$184 million for 1746 MWh of discharge electricity. • At $\$$105/kWh, the reference plant costs less than any of the Energy Storage Systems evaluated by PNNL in 2020 for the Energy Storage Grand Challenge. Operations and Maintenance cost estimates were scaled from combined cycle practice, assuming that the LSCC unit was co-located with and sharing some labor expense with other units, to arrive at $\$$2.2 million per year. Plant economics were evaluated using prices from the ERCOT Day-Ahead Market for calendar year 2019 (excluding the market disruptions from the COVID pandemic and the February 2020 deep freeze event). Assuming economic dispatch in the ERCOT Day-Ahead market, the reference plant capacity factor would have discharged for 2777 hours at 91.9 MW, a 31.66% capacity factor, with a marginal cost of $\$$25.59/MWh, and a LACE of $\$$82.41/MWh. Fixed charges were calculated according to EIA guidelines to arrive at an LCOE of $\$$83.48. The benefit-to-cost ratio of 0.99 suggests that the reference plant would have been cost-effective and competitive in the market. EPRI interviewed selected utilities to gauge the need for, applicability of and interest in the LSCC system. Several utilities are currently managing increased load growth along with the inclusion of increasing levels of renewable generation, putting pressure on conventional generation by requiring increased turndown requirements and ultimately lower capacity factors. All of the utilities interviewed have CO 2 reduction targets in the 2030-2050 timeframe that will severely limit the participation of fossil generation and require better utilization of carbon free generation. While there is limited opportunity for storage in the current markets, the utilities interviewed stated that there will be a substantial need for long duration energy storage in the future given the expected trends. Utilizing an energy storage system will generally be preferred over new gas capacity in some cases, with the capabilities of the LSCC system being a potential option for retrofit to existing simple cycle gas turbine units, allowing them to deliver greater participation in the market with lower carbon intensity. A technology gap assessment and technology maturation plan identified a pilot-scale demonstration as the final step before commercialization. Key gaps to be addressed during the Phase II FEED (Front-End Engineering Design) are component selection and design, commissioning procedures, and operational procedures and the control system for LSCC charging and discharging. The project team has been expanded to include Wood Group PLC as EPC. The proposed Phase II work leads to a pilot-scale engineering demonstration (TRL 6) to be conducted at Southern Company’s Plant Rowan, where the prototype system will perform “all the functions that will be required of the operational system.” The proposed pilot will facilitate commercialization (TRL-9) by scale-up to utility-scale systems integrated with peaking GTs or directly to facility scale systems using industrial GTs. The conceptual design for the pilot plant focuses on the novel integration aspects of LSCC technology. A slipstream of gas turbine exhaust will feed a waste heat recovery unit coupled to a molten salt steam generator heated by stored energy. The pilot is intended to demonstrate all key operating modes of the LSCC technology during charging, discharging and standby. The pilot equipment will be approximately one-seventh scale of the LM6000 commercial target and is expected to have commercial off-ramp potential for facility-scale applications.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Fission with Exotic Nuclei (Abbreviated Report)

Nuclear fission is a key mechanism involved in the synthesis of heavy elements in the Cosmos and is the primary explanation for the stability of superheavy elements. Nevertheless, our knowledge of fission remains extremely fragmented. Most experiments have been conducted only on a tiny number of stable actinide nuclei and are often incomplete, leading to gaps in our basic understanding of the process. For many radioactive isotopes, basic fission data such as the charge or mass distribution of the fragments is unknown. These gaps cannot always be filled by simulation alone. Common fission models contain too many free parameters and lack predictive power. In contrast, the fundamental theory of fission under development at LLNL is much more predictive, but its current computational cost is too high to be used extensively for data evaluations. A unique window of opportunity to resolve these limitations has recently opened: the U.S. nuclear science community is ramping up major experimental programs at the Facility for Rare Isotope Beams (FRIB, the DOE flagship facility in low-energy nuclear science), and techniques from machine learning have shown great potential to simplify the use of a fundamental, quantum-mechanical theory of fission. This project has two components. On the experimental side, we acquired and deployed at the HIGS facility a new dual Frisch-Grid ionization chamber to measure correlated fragment-mass, kinetic energy, and angular distributions of fission fragments from induced fission. This new device was used to perform measurements of charge, mass and total kinetic energy of fission fragments in the photofission of 238 U and eight gamma-ray beam energies between 6.2 and 13 MeV, which allowed extracting high-precision independent yields for this reaction. The device was also used to perform measurements of the same quantities in the neutron-induced fission of 234 U with monoenergetic beams of energy between 5 and 8 MeV. In parallel, we collaborated with a team at Commissariat à l’énergie atomique et aux énergies alternatives (CEA) to perform a series of measurements of fission yields in inverse kinematics for the two isotopes of 236 U and 240 Pu. The experiment took place at the Grand Accélérateur National d’Ions Lourds in France in June 2023. The deployment of the VAMOS spectrometer with a new array called PISTA allowed determining the excitation energy of the fissioning system within 1 Mega-electronvolts. The second component of the project involved using deep neural networks to build fast and reliable emulators of our current fission models. In an invited paper published in Frontier in Physics, we showed that autoencoders could successfully compress nuclear wavefunctions in nuclear density functional theory. We achieved a dimensionality reduction of the order of two orders of magnitude while keeping the error in the total energy to less than 0.01%. In a second paper submitted to Physical Review Letters in June 2023 with our collaborators at CEA, we showed that variational autoencoders can learn the collective degrees of freedom driving the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report

Utilities across the world are wrestling with evolving market dynamics, population growth and climate change. Distributed Energy Resources (DERs) such as solar photovoltaics, distributed generators and energy storage systems are becoming important parts of the U.S. energy mix. These factors are driving an increasing need for low-cost grid asset monitoring. Aside from being costly, traditional utility monitoring systems are not sufficiently robust and do not provide real-time visibility into the condition of grid assets such as transformers. Lack of accurate real-time measurements on performance has resulted in the use of lagging indicators, such as oil sample analysis. To address this need, an innovative embedded optical sensing technology, Transformer Real-time Assessment Intelligent System (TRANSENSOR) was developed, validated and demonstrated in this project. To date, TRANSENSOR has focused on transformers but is extendable to other grid assets. In addition to the technology being embedded into new transformers during manufacturing, a retrofit configuration that can be installed on existing transformers in the field was also developed. It is anticipated that the ability to retrofit existing transformers will help accelerate adoption of the underlying TRANSENSOR technology. Phase 1 of the project focused on laboratory development and qualification of the technology. Following iterations and exploration of relevant optical sensing modalities and multiplexed configurations of interest for the transformer environment, an effective candidate configuration was agreed upon, down-selected and custom-designed for embedding into General Electric (GE) network transformers. Two new GE 500 kilovolt ampere (kVA), 27 kilovolt (kV) distribution network transformers were built with embedded fiber-optic (FO) sensors and successfully qualified per industry standards at GE’s Shreveport, Louisiana facility during Phase 1 of the project. Following the successful completion of Phase 1, the team proceeded to Phase 2, which focused on a field demonstration of the technology. Over Phase 2, the first new GE transformer built with embedded fiber-optic sensors was installed in an above-ground cage and connected to the grid at Con Edison’s Astoria facility. A second transformer equipped with TRANSENSOR was installed in an underground vault. Additionally, an older (1982 year model) GE transformer in an above-ground cage was retrofitted with fiber- optic sensors and reconnected to the grid at ConEd’s facility. Analysis of data acquired from the sensors showed interesting correlations with transformer loading. Additionally, key events such as transformer low-voltage network connection, primary-side energizing, and a pressure loss event from an oil sampling were detected by the TRANSENSOR system. Online data processing/feature extraction algorithms for the second transformer in the underground vault detected key features and event alerts that were transmitted through a wireless 4G connection. The remote deployment concept showed promising results with data collection running for a total of 8 months across the three (3) GE transformers instrumented for the Phase 2 field demonstration. This sets the stage well for further development and commercialization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Adhesion Capabilities of Permanent Foaming Fixatives

DOE-EM have identified an operational requirement for a fixative that can immobilize and/or encapsulate residual contamination in 3D void volumes (pipes, gloveboxes, waste containers, etc.) during D and D activities. Failure to safely and effectively immobilize residual contamination can: Put workers at risk; Contaminate the public and environment; Drive up costs. Commercial-off-the-shelf (COTS) polyurethane (PU) foams is one possible solution and is currently being investigated by Savannah River National Lab (SRNL). Adhesion testing will dictate how well PU foams will adhere and immobilize residual contamination onto a substrate. Results can provide a performance criteria for Section 5 of ASTM E3191: Standard Specification for Permanent Foaming Fixatives Used to Mitigate Spread of Radioactive Contamination. Initial mechanical testing showed intumescent rigid PU foams were best in class (tensile, compression, TGA/DSC) Application of intumescent rigid PU foam in pipe scenario with 'contamination' showed excellent adhesion capabilities as long as foam had contact with pipe. The foam, however, was not able to penetrate 'contamination' but created pockets where the contamination interacted with the substrate. Pretreatment options of pipe were considered to produce better immobilization capabilities. Pretreatment options included COTS products like baking spray, rubber cement, and soap. Foam was still able to immobilize on a global sense, but not a local sense. Essentially acted as a mechanical plug. A tensile tester (MTS Criterion Series 43) was utilized to evaluate the tensile adhesion strength of 6 COTS PU foams. ASTM D1623: Tensile and Tensile Adhesion Properties of Rigid Cellular Plastics. Procedures: PU foams were cured between two smooth 2'' x 2'' 304 stainless steel coupons with hinges glued on plates for gripping support. Parameters Used: Pull rate of 0.1 in/min. Calculations: Tensile adhesion strength, elongation, and ImageJ analysis of how PU foam is left on substrate. Outcome: The PU foam with the best adhesion capabilities would be downselected for further evaluation to be used as a permanent foaming fixative. The rigid PU foams had the best adhesion capabilities with the R1 foam having a max load of 236 N. One of the I-R2 samples reached almost 450 N and another sample reached 2500 N before slipping. The other intumescent foam, I-F4, had the most coverage on the stainless steel coupon's surface from the ImageJ results (61.43% surface coverage). The intumescent foam, I-R2, will be the foam of choice for future testing due its fire retardant and adhesion capabilities. Future directions: Conduct the following experiment in a pipe scenario with the down-selected PU foam. Procedures: PU foam will be cured between in a 304 stainless steel pipe (ID: 4'', OD: 4.5'', Height: 4''). Parameters Used: Compression testing results will be referenced to determine if foam's adhesion strength would be greater its compression strength as its being compressed. Calculations: Compression strength, shear stress, total time elapsed. Conduct further adhesion testing with the down-selected PU foam (I-R2) to be treated as a permanent foaming fixative (PFF). Determine the minimum contact the PFF should have with the substrate for adequate results. Evaluate if PFF's adhesion capabilities is time dependent (3.1.5 of ASTM E3911). Subject PFF to seismic stressors addressed in Safety Basis of Interim Operation documents (SBIO) to further evaluate adhesion capabilities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System

The Inflation Reduction Act of 2022 (IRA) and the Infrastructure Investment and Jobs Act of 2021, commonly referred to as the 'Bipartisan Infrastructure Law (BIL),' collectively represent the largest commitment of the U.S. Federal Government to invest in the modernization and decarbonization of the U.S. energy system. The Congressional Budget Office (CBO) estimates that total support for the broad range of climate and clean energy programs, tax credits, and other incentives authorized through the two laws will exceed $430 billion from 2022 through 2031 (CRS 2022; CBO 2021, 2022). While the climate and clean energy provisions are numerous and have the potential to impact all aspects of the U.S. energy system from fuel and electricity production to final consumption in industry, transportation, and buildings, the provisions relevant to the electricity sector - in particular the suite of tax credits for clean generation, storage, and carbon dioxide ( CO 2 ) capture and storage - are expected to be some of the most consequential in terms of emissions reduction and clean energy deployment (Larsen et al. 2022; Jenkins, Mayfield, et al. 2022; Mahajan et al. 2022; Zhao et al. 2022). In this report, we detail the methods and results of a study estimating the potential impacts of key provisions of IRA and BIL on the contiguous U.S. power sector from present day through 2030. The analysis employs an advanced power system planning model, the Regional Energy Deployment System (ReEDS), to evaluate how major provisions from both laws impact investment in and operation of utility-scale generation, storage, and transmission, and, in turn, how those changes impact power system costs, emissions, and climate and health damages. While not exhaustive in capturing every provision, the analysis estimates the possible scale of power-sector impacts that could result from the modeled provisions in IRA and BIL. The study is structured around two scenarios to evaluate the potential impacts of both laws on the power sector: 1) No New Policy: A counter-factual scenario that reflects all Federal and state policies enacted as of September 2022, with exception to IRA and BIL, and assumes load growth consistent with the Energy Information Administration's Annual Energy Outlook 2022 (AEO22) Reference case (EIA 2022a); 2) IRA-BIL: A scenario reflecting all Federal and state policies enacted as of September 2022, including key IRA and BIL provisions, most notably the investment and production tax credits for zero-carbon emitting electricity generation and storage (ITC and PTC), the tax credit for CO 2 capture and storage (45Q), and the tax credit for existing nuclear plants (described further in Section 2.3). To account for the impacts of IRA and BIL on electrification, assumes increased load growth consistent with a scaled version of the Medium Electrification scenario from the Electrification Futures Study (Mai et al. 2018). These scenarios are simulated across seven sets of assumptions with varying projected future electricity market conditions, including technology costs and performance, natural gas prices, and the degree of availability, feasibility, and cost of development of renewable resources, electricity transmission, and CO 2 pipeline, injection, and storage infrastructure. In addition, we simulate two sensitivities on the 'policy' treatment in which we vary key assumptions pertaining to the realized value of the clean electricity ITC and PTC: 1) the cost of monetization of tax credits, and 2) the level of bonus crediting realized by project developers. We demonstrate that IRA and BIL have the collective potential to drive substantial growth in clean electricity by 2030, while reducing costs for consumers, mitigating climate change, and decreasing the human health impacts of power sector emissions. However, we also demonstrate that if expected cost improvements of clean technologies are not realized and/or constraints on deployment driven by factors such as supply-chain challenges, regulatory hurdles, and the social acceptability of energy infrastructure development limit the rate of clean energy and associated infrastructure deployment (such as transmission), then the share of clean generation achieved and the associated emissions benefits realized may be substantively reduced.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Hybrid Power Plants: Status of Operating and Proposed Plants, 2023 Edition [Slides]

Improving battery technology and the growth of variable renewable generation are driving a surge of interest in “hybrid” power plants that combine, for example, wind or solar generating capacity with co-located batteries. While most of the current interest involves pairing photovoltaic (PV) plants with batteries, other types of hybrid or co-located plants with wide-ranging configurations have been part of the U.S. electricity mix for decades. This annually updated briefing tracks and maps existing hybrid or co-located plants across the United States while also synthesizing data from power purchase agreements (PPAs) and generation interconnection queues to shed light on near- and long-term development pipelines. The scope includes “co-located hybrids” that pair two or more resources (e.g., multiple types of generation and/or generation with storage) that are operated largely independently behind a single point of interconnection, and “full hybrids” that also feature coordinated operations of the co-located resources. The focus is on plants with one megawatt (MW) or more of capacity; smaller (often behind-the-meter) projects are also increasingly common, but are not included in this data synthesis. Key findings from the latest briefing include: -At the end of 2022, there were 374 hybrid plants (>1 MW) operating across the United States (+25% compared to the end of 2021), totaling nearly 41 GW of generating capacity (+15%) and 5.4 GW/15.2 GWh of energy storage (+69%/+88%). PV+storage plants are by far the most common, dominating in terms of plant number (213), storage capacity (4.0 GW/12.5 GWh), storage:generator capacity ratio (49%), and storage duration (3.1 hours). But there are nearly twenty other hybrid plant configurations as well, including several different fossil hybrid categories (each dominated by the fossil component) as well as wind+storage, wind+PV, wind+PV+storage, geothermal+PV, and others. -Last year was another strong year for PV+storage hybrids in particular: 59 of the 62 hybrids added in 2022 were PV+storage. As of the end of 2022, there was roughly as much storage capacity operating within PV+storage hybrid plants as in standalone storage plants (~4 GW each). In storage energy terms, however, PV+storage edged out standalone storage by ~2 GWh (12.5 GWh vs. 10.4 GWh, respectively). -Interconnection queue data show continued strong developer interest in hybridization. At the close of 2022, there were 51% more hybrid plants—representing 59% more generating capacity—in interconnection queues across the United States than there were at the end of 2021. Solar dominates these proposed plants as well: at the close of 2022, there were 457 GW of solar capacity proposed as a hybrid (representing ~48% of all solar capacity in the queues), most typically pairing PV with battery storage. At the same time, there were 24 GW of wind capacity proposed as a hybrid (representing ~8% of all wind capacity in the queues), again most-often pairing wind with storage. Meanwhile, more than half of all storage in the queues is estimated to be part of a hybrid plant. While many of the plants proposed in the queues will not ultimately reach commercial operations, the depth of interest in hybrid plants—especially PV+storage—is notable, particularly in certain regions. For example, in CAISO, 97% of all solar capacity and 45% of all wind capacity in the queues is proposed as a hybrid. -The report also surveys power purchase agreement (PPA) price data from a sample of operating and proposed PV+storage plants. Though PV+storage PPA prices have fallen over time, “levelized storage adders” have recently increased somewhat to ~$\$ $7000/MW-month, ~$\$ $60/MWh-stored (assuming one full cycle per day), or ~$\$ $15/MWh-PV. Some of the recent price increase could simply reflect a trend towards higher battery:PV capacity ratios over time, which increases costs, all else being equal. The well-publicized impact of inflationary and supply chain pressures on battery prices is no doubt a contributor as well.

25 ENERGY STORAGE↗