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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.

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At least 181 records · Page 10

Sparse Control Synthesis for Uncertain Responsive Loads With Stochastic Stability Guarantees

In this report, recent studies have demonstrated the potential of flexible loads in providing frequency response services, predominantly due to their availability and cost-effectiveness. However, uncertainty and variability in various weather-related and end-use behavioral factors often impact the reliability of demand-side control performance. This work addresses this problem with the design of a demand-side control to achieve frequency response under load uncertainties. Our approach involves modeling the load uncertainties via stochastic processes that appear as both multiplicative and additive in the power system dynamics. Recently developed mean square exponential stability (MSES) results for continuous-time linear stochastic systems are applied to pose the control synthesis problem which results in an LMI-based optimization problem. Additional costs and constraints are added to the LMI-based controller synthesis to ensure MSES, improve closed-loop transient performance, maximize tolerable uncertainties, and promote sparsity in the controller. Additionally, the fundamental limitations between the tolerable uncertainties and control efforts while ensuring MSES are discussed. Further, the control synthesis problem for the case of the full-state measurement is generalized to the case of partial-state measurements. The proposed control synthesis is illustrated on an IEEE 39 bus system with rigorous studies to demonstrate the role of sparsity, closed-loop transient performance, tolerable uncertainties, and control efforts while ensuring MSES and achieving frequency response.

42 ENGINEERING↗

Numerical analysis of dynamic load following response in a natural circulation molten salt power reactor system

The Molten Salt Reactor (MSR) concept is a rapidly evolving Generation IV design that has recently attracted favorable attention due to the potential for reducing waste generation, realizing passive safety features, and seizing on the opportunity for cost effective economics. An investigation into the power transient behavior of an autonomous load-following, closed-loop, natural circulation MSR system is important to quantifying operational and safety performance under dynamic conditions. This paper presents the results of a STAR-CCM+ and a comparatively simple asymmetric, one-dimensional, numerical model to solve the compound dynamic MSR power behavior subject to flow and temperature reactivity feedback only. Results show that reactor power is affected by fuel salt flow velocity (global) and temperatures (local bulk volume averages) in a coupled, time-delayed manner that results in a unique compound dynamic, closed-loop power feedback mechanism. The 1-D simulation approach opens the possibility of performing inexpensive computations to evaluate time-dependent reactor performance relative to thermo-physical fuel salt limitations. Results also potentially motivate a convincing conclusion that natural circulation MSRs provide a leap in safety and reliability.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Cyber‐physical system testbed for power system monitoring and wide‐area control verification

The electric power system is intrinsically a cyber‐physical system (CPS) with power flowing inthe physical system and information flowing in the cyber‐network. Testbeds arecrucial for understanding the cyber‐physical interactions and provideenvironments for prototyping novel applications. This study proposes afour‐layer architecture for CPS testbeds with emphases on communication networkemulation and networked physical components. A configurable software‐definednetwork is employed to bridge physical components with wide‐area applicationsfor closed‐loop control. In order to distribute physically coupled devices intomultiple software simulations, this study proposes a data broker setup based ona distributed messaging environment to achieve low‐latency data streaming. Thedecoupled design with data streaming allows for building testbed components asmodules and running them in a distributed manner. Case studies verify the databroker setup for low‐latency sensing and actuation, as well as the communicationemulation setup for the desired network latency. Also illustrated is a replayattack scenario using synchrophasors in the Western Electricity CoordinatingCouncil (WECC) 181‐bus system for demonstrating the closed‐loop cyber‐physicalsimulation capability of the testbed.

Cui, Hantao↗

Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)

Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.

01 COAL, LIGNITE, AND PEAT↗

Energy-efficient sorption-based gas clothes dryer systems

Standard electric resistance and fuel-driven dehydration technologies exhibit a maximum coefficient of performance of well below 1 mainly due to enthalpy losses associated with the air leaving the dehydration system. To improve energy efficiency, condensing dryer systems condense the moisture captured from a product in a closed-loop air circulation cycle. Existing condensing dehydration systems including heat pump dryers, however, need to significantly cool the air to achieve dehumidification. The added cooling and subsequent heating to return the air to a desired drying temperature consume substantial energy and thus reduce drying performance. Here, an innovative sorption-based gas dehydration system is proposed to overcome barriers deteriorating energy efficiency in existing gas, electric, or heat pump dryer systems. Decoupling latent and sensible loads, the system employs a liquid-desiccant solution to directly capture air humidity, thereby allowing circulation of the air in a closed loop to achieve high drying energy efficiency. In other words, the system captures waste latent heat from the moisture produced during the dehydration process and reuses it to improve energy efficiency. This study focuses on a comprehensive quasi-steady-state thermodynamic modeling of the proposed sorption-based dehydration concept employed for a gas clothes dryer application to predict transient response and overall drying performance (i.e., time and energy metrics). The analysis indicates the proposed sorption-based gas clothes dryer system can deliver a specific moisture extraction rate of 1.71 kg of water per kWh (i.e., a combined energy factor of 3.167 kg (6.98 lbm) of dry cloth per kWh) with a drying time of 44 min. This is a 112% energy improvement compared with state-of-the-art gas clothes dryers exhibiting a combined energy factor of 1.50 kg (3.3 lbm) of dry cloth per kWh. The technology pursued here can potentially be employed as a platform for many fuel-driven equipment to take advantage of available waste thermal energy in the environment instead of simply burning a fuel.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Mini-CAPTAIN liquid argon time projection chamber

This manuscript describes the commissioning of the Mini-CAPTAIN liquid argon detector in a neutron beam at the Los Alamos Neutron Science Center (LANSCE), which led to a first measurement of high-energy neutron interactions in argon. The Mini-CAPTAIN detector consists of a Time Projection Chamber (TPC) with an accompanying photomultiplier tube (PMT) array sealed inside a liquid-argon-filled cryostat. The liquid argon is constantly purified and recirculated in a closed-loop cycle during operation. The specifications and assembly of the detector subsystems and an overview of their performance in a neutron beam are reported.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Heliostats with Adjustable Shape for High Concentration throughout the Day

Our motivation is to develop more efficient heliostats that can provide commercially viable solar thermal power at temperatures > 800°C. Such high temperatures will enable high-temperature industrial processes, as well as electrical generation after sunset with high efficiency. The importance of this research is that such heliostats have the potential to substantially expand the global use of solar energy, by adding solar thermal power as a major component. Thermal solar currently accounts for only 1% of all solar power (with PV being the rest), with heliostat fields providing just 0.25%. Our goals have been 1) to demonstrate a technical improvement for heliostats that can enable fields of them to more efficiently power receivers and reactors, and 2) to show a path to low-cost mass production. Our solution uses new opto-mechanical technology to correct a fundamental deficiency of present heliostats that limits their concentration, namely that they have fixed shape. Most of today’s heliostat research does not address this, but is directed simply toward cost reduction in an effort to make heliostats commercially viable. We are motivated to explore also improving heliostat efficiency, which can be done by continually changing their shape to maximize the concentration of sunlight throughout the day. This is not a new concept, but it has never been implemented in a practical, cost-effective way that approaches the theoretical limit to concentration while also improving mechanical performance; this is our goal. Our major accomplishments have been: 1) We have realized the planned design, construction, and test of a prototype heliostat that achieves the required shape changes in an 8 m2 single-piece glass mirror. The mirror is attached to a steel support frame that is automatically mechanically twisted by the heliostat drives that orient the mirror to direct sunlight to the tower-mounted receiver. Closed-loop tracking is done using a new beamsplitter camera that exploits the target-oriented mount configuration. Field tests of the heliostat show that the light is reflected through the day to always form a disc image of the sun, as needed to obtain the highest concentration. 2) We have developed the design for a field of 431 heliostats to deliver annual average of 1 MW of thermal power at 3,000 sun concentration, matched to a high-temperature ≥ 1000°C chemical reactor. 3) We have also developed, beyond the original stated goals of the project, a new concept for closed-loop tracking and shape-sensing for all the heliostats in the above field, using just 6 cameras around the concentrated reactor focus. Our research adds to the understanding of solar thermal energy by its demonstration of the technical effectiveness of a higher performing heliostat, and by its concept for a new powerful method for real-time tracking and shape sensing in the field, as described above. We have studied the economic feasibility of fields of our twisting heliostats to provide high- temperature heat at a price competitive with that of burning gas, to satisfy the DOE’s studied zero-emissions scenario, where the gas price has to include the cost of carbon capture. The project has the potential to greatly benefit the public if it helps limit global warming by 1) reducing carbon emission from industrial heating, which is currently a major contributor to the 40-billion-ton annual increase in atmospheric CO 2 . 2) Ultimately, the technology could prove to be the least expensive method to power direct air capture of CO 2 on the very large scale needed to remove the 1 trillion-ton excess of CO 2 already in the atmosphere.

14 SOLAR ENERGY↗

Active control of resistive wall mode via modification of external tearing index

Modification of the external tearing index, Δ ext ′ , by magnetic feedback is analytically investigated for the purpose of controlling the resistive plasma resistive wall mode (RP-RWM). The matching method is pursued by deriving expressions for the close-loop Δ ext ′ and by linking it to the counterpart from the inner layer. Various feedback coil configurations are found to generally reduce Δ ext ′ and stabilize the RWM, with either proportional or derivative control. Feedback modification of Δ ext ′ is found to be generally independent of the inner layer resistive interchange index D R , confirming that feedback action primarily modifies the solution in the outer ideal region for the RP-RWM. Exception occurs when either the inner layer favorable curvature effect becomes sufficiently large or the feedback action is sufficiently strong to introduce a rotating RP-RWM in the static plasma, leading to complex-valued close-loop Δ ext ′ . The perturbed magnetic energy dissipation in the outer region, associated with the eddy current in the resistive wall, is identified as the key physics reason for feedback induced complex Δ ext ′ . Similar results are also obtained for active control of the external kink instability, whose open-loop growth rate is significantly reduced by inclusion of the plasma resistivity. Within the single poloidal harmonic approximation, which is most suitable for the matching approach, external active coils combined with poloidal sensors are often found to be more efficient for feedback stabilization of the mode at large proportional gain values. This counter-intuitive result is explained as the lack of (non-resonant) poloidal harmonics for proper description of the feedback coil geometry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Biobased Poly(dodecylene Furanoate) with Inherent Advantages in Performance and Circularity

Biobased polymers are gaining traction toward more sustainable flexible-film packaging, yet overcoming trade-offs between their performance properties and end-of-life (EoL) options still remains a challenge. Here, it is shown that biobased poly(dodecylene 2,5-furanoate) (PDDF), synthesized via both step-growth polycondensation and chain-growth ring-opening polymerization methods, exhibits advantages not only in gas barrier properties but also in EoL options due to its biodegradability and closed-loop chemical circularity. Specifically, PDDF displays significantly lower oxygen and carbon dioxide permeability than commercial poly(butylene adipate-co-terephthalate) (PBAT) and linear low-density polyethylene , alongside a markedly higher modulus (by ≈3 ×) and reduced water vapor transmission rate compared to PBAT. This superior performance is attributed to the inherently rigid, polar, H-bonding furan rings that enhance chain interaction, packing and crystallinity and thus reduce free volume impeding gas diffusion, while the long hydrophobic dodecylene segments inhibit water permeation. Furthermore, PDDF can be recycled back to its cyclic monomer by base-catalyzed depolymerization or diester and diol monomers by simple methanolysis. These superior barrier properties, coupled with biodegradation and closed-loop circularity, highlight the potential of the biobased PDDF as a more sustainable alternative for packaging.

Poly(dodecylene 2,5-furanoate) (PDDF)↗

Toward the implementation of self-powered, wireless, real-time reactor power sensing

The successful development of real-time, self-powered, wireless reactor power sensing technology would enable key operating parameters of every fuel assembly in a commercial reactor core to be continuously monitored, and potentially be utilized for applications such as closed-loop reactor control. This paper discusses the expansion of successful work on the application of Self Powered Neutron Detectors (SPND) for reactor power monitoring and the wireless transmission of these detector signals using advanced vacuum micro-electronic (VME) transmitter technology developed by Westinghouse in collaboration with the Penn State University Radiation Science and Engineering Center. Results demonstrate that this technology may be successfully applied via long-term testing in the Penn State TRIGA reactor. SPND are inherently slower than, for example, ion chambers due to their dependence on radioactive decay to generate a signal. Additional research developed delay compensation algorithms to accelerate the response of these detectors for use in near-real-time closed-loop reactor control. Initial results indicate that practical signal acceleration can be obtained digitally or with an equivalent analog circuit. Future research will apply an inverse model of the sensor’s balance differential equations to more-effectively accelerate the SPND signal. Use of inverse models will also prove to be adaptive in the sense that time-dependent burn-up of these detectors, due to neutron activation of the detector material, can be modeled and applied in the acceleration algorithm.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Representing the Future Role of Hydropower and Pumped Storage Hydropower (PSH) in Electricity Planning Tools

Existing tools for long-term electric sector planning struggle to represent hydropower's nuanced site-specific technical and operating characteristics, which depend on technical specifications as well as water management practices and regulations. As a result, long-term planning models and tools insufficiently characterize hydropower value and incentives, and they cannot fully represent the role hydropower can play in a future electricity system that could include a high penetration of variable wind and solar generation, battery storage, and other low-carbon technologies. This presentation demonstrates the culmination of a multi-year effort to enhance hydropower representations in electricity planning models at the National Renewable Energy Laboratory (NREL), as part of the U.S. Department of Energy (USDOE) HydroWIRES Initiative. New modeling techniques are demonstrated using the NREL Regional Energy Deployment System (ReEDS), an open-access electric sector capacity expansion model used extensively in a wide range of technology deployment and integration analysis, including the 2016 USDOE Hydropower Vision. ReEDS uses a least-cost optimization approach to understand investment and operation of electricity generation, storage, and transmission technologies under future scenarios of electricity technology innovation, demand, policy, and other sectoral drivers. ReEDS was modified to better represent value and opportunities for both pumped storage hydropower (PSH) and hydropower systems without pumping. We incorporated a new national closed-loop PSH resource and cost assessment to explore new PSH deployment opportunities and added plant-level data to better represent the existing PSH fleet. New upgrade pathways enable opportunities for enhanced hydropower flexibility by adding pumps, upgrading dispatchability, increasing capacity, or increasing energy availability. The model was also modified to better represent the value of long-duration energy storage beyond diurnal time scales, allowing both hydropower and PSH to better balance energy supply and demand variations in high-renewable systems. These new features are demonstrated under reference and high-renewable futures and a range of sensitivity scenarios to understand which hydropower and PSH deployment and upgrade opportunities are the most attractive. These scenarios indicate potential for new closed-loop PSH deployment and for hydropower flexibility improvements to have important impacts on long-term electricity system emissions and economic outcomes. Increasing flexibility of the existing hydropower fleet can reduce the need to invest in new flexible grid technologies and help achieve decarbonization goals. Systems with sufficient energy storage could also be valuable for balancing seasonal differences in renewable energy availability, particularly from solar energy. The methods developed for ReEDS and subsequent scenario results reveal important considerations for future hydropower and grid system planning, and all data and code is freely available in a public code repository for use throughout the hydropower industry.

capacity expansion↗

Upcycling Mixed Spent Ni-Lean Cathodes into Ni-Rich Polycrystalline Cathodes

Sustainable battery recycling is vital for conserving resources and reducing environmental impacts. Current open- and closed-loop recycling strategies often focus on recovering individual components, making the reuse of mixed cathode materials a complex challenge. Meanwhile, the research on upcycling has been limited to using pristine cathode feedstocks and virgin materials for synthesis. Here, to address this issue, we present an upcycling approach for spent Ni-lean mixed cathode materials that integrate an upcycling hydrometallurgical recycling process with traditional hydrometallurgical methods. This strategy achieves a utilization of 92.31 mol % of recycled materials, enabling the regeneration of Ni-rich cathode materials while significantly reducing the reliance on virgin resources. The regenerated 83Ni cathode materials demonstrate physical properties comparable to those produced from virgin materials. Electrochemical evaluations using single-layer pouch cells show that both recycled and virgin cathodes exhibit initial specific capacity close to 201.1 mAh/g and maintain approximately 88 % capacity retention after 500 cycles. Additionally, 2Ah cells confirmed these findings, delivering 85 % capacity retention after about 900 cycles. Techno-economic analysis demonstrates notable environmental benefits, including reductions in greenhouse gas emissions and energy consumption, achieving 232.75 MJ/kg of product, which is 8.6 % lower than traditional methods and comparable to direct upcycling. Furthermore, the upcycling hydrometallurgical recycling process generates the highest profit, proving its economic viability. This scalable and versatile process is adaptable to varying transition metal compositions, facilitating a closed-loop recycling system that bridges mixed spent cathodes with next-generation cathode materials, and offers a sustainable solution for managing waste battery materials.

Hydrometallurgical recycling↗

Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D is Driving Speed, Scale, and Efficiency

This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

Gibson, Brian↗

In‐mold rheology and automated process control for injection molding of recycled polypropylene

Abstract Manufacturing plastic parts with secondary feedstocks has risen to the forefront of importance in recent years. However, the variation in molecular weight and rheology of secondary feedstock can lead to inconsistent part quality. This work evaluates the effectiveness of a novel closed‐loop adaptive process control system that adjusts nozzle pressure in response to in‐mold pressure data. Five different recycled polypropylene blends, with a broad distribution of flow properties, were evaluated to determine the effectiveness of the control system at reducing processing variation. The experimental results show that the process control strategy reduced the variation within the mold, as seen by in‐mold pressure curves and calculated in‐mold viscosity values. Additionally, the parameters that control the automated process adjustments were investigated, showing the importance of optimization. The analysis of the correlation between in‐mold rheology and mechanical properties showed a slight variation in the mechanical properties and parts weight with a coefficient of variation of under 5%. Overall, the results demonstrate the ability of pressure‐controlled molding and automated viscosity adjustment to reduce the variability when molding a secondary feedstock. Highlights Pressure‐controlled injection molding of recycled polypropylene. Automated closed‐loop adaptive process control methodology. Methodology resulted in a reduction in pressure variation during molding. Changes in mechanical properties and in‐mold viscosity were investigated. Results show the potential of pressure‐controlled molding at reducing variation.

Krantz, Joshua↗

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBS

The increasing demand for lithium-ion batteries (LIBs ) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCam).During this project ,samples of high-purity recycled NMC hydroxide (~2kg each) were received from Nth Cycle. In the first received batch some impurities like cadmium, calcium, and sodium are present in quantities that would negatively impact battery performance. Nth Cycle indicated that the impurities such as cadmium are present due to poor battery separation and co-shredding of NiCd batteries with with LIB. Cadmium was not present in the two subsequent batches as Nth Cycle processed cadmium free black mass. Thus, effective recycled battery sorting is critical to closed-loop LIB recycling into active electrode materials.

99 GENERAL AND MISCELLANEOUS↗

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBS

The increasing demand for lithium-ion batteries (LIBs) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCam). During this project , samples of high-purity recycled NMC hydroxide (~2 kg each) were received from Nth Cycle. In the first received batch some impurities like cadmium, calcium, and sodium are present in quantities that would negatively impact battery performance. Nth Cycle indicated that the impurities such as cadmium are present due to poor battery separation and co-shredding of NiCd batteries with with LIB. Cadmium was not present in the two subsequent batches as Nth Cycle processed cadmium free black mass. Thus, effective recycled battery sorting is critical to closed-loop LIB recycling into active electrode materials.

25 ENERGY STORAGE↗

Advanced Hydropower and PSH Capacity Expansion Modeling (Final Report on HydroWIRES D1 Improvements to Capacity Expansion Modeling)

Hydropower and pumped-storage hydropower (PSH) have played a key role in providing flexible, low-carbon electricity to the U.S. electricity system for over a century. As variable generation (VG) deployment increases the demand for flexible, dispatchable generation, it is important to use all available methods for understanding how hydropower and PSH interfaces with VG in a future low-carbon grid. Capacity expansion models (CEMs) of electricity systems are often used to study future electricity scenarios, but these tools often have difficulty representing site- and technology-details of hydropower and PSH due to limited spatial, temporal, or process resolution. This report demonstrates a set of model advancements to improve hydropower and PSH representations in CEMs and other models that consider hydropower and PSH's role in electricity systems. Model advancements include new data integration to define closed-loop PSH resource availability and cost, along with site-level parameterizations of existing PSH capacity and energy storage specifications. Shifting energy across seasons for both hydropower and PSH is explored to demonstrate the potential value of long-duration storage. New representations of hydropower upgrades offer opportunities to increase dispatchability, add pumps, or independently add capacity or energy depending on what is most valuable. New model structures and data are demonstrated individually and in combination to observe their impact on model results and provide initial insights into what is most important for analysts, electricity system planners, and hydropower decision-makers to consider when assessing future roles of hydropower. Improving flexibility of existing hydropower assets has the potential to reduce CO 2 emissions through complementing VG technologies and/or improve electricity system economics by reducing the need to deploy higher-cost systems. Large-scale energy storage is also shown to provide opportunities for balancing seasonal differences in VG, particularly solar photovoltaics (PV). Initial analysis with a new closed-loop PSH resource and cost dataset also demonstrate the potential for new PSH deployment to offer new grid flexibility opportunities. Future analysis and modeling of hydropower's role in the U.S. and other electricity systems could include methodological improvements based on those discussed here along with sensitivity analysis to better represent current and future potential hydropower and PSH flexibility. Improvements to geospatial and site-level data can further improve the understanding of how hydropower and PSH can be upgraded and operated in response to future electricity system needs. This work lays the groundwork to use advanced planning models to explore the range of roles hydropower and PSH can play in the grid of the future.

13 HYDRO ENERGY↗

Digital twin framework for PIP-II linac: AI-driven multi-scale modeling from ion source to 800 MeV

The PIP-II superconducting linac at Fermilab is designed to deliver multi-megawatt proton beams for neutrino physics and other high-intensity applications. To expedite commissioning and enhance operational reliability, we have developed an EPICS-based data flow framework that seamlessly integrates digital twins (DT) with physical twins (PT). These digital twins comprise high-fidelity beam dynamics models or data-driven surrogate models connected to their physical counterparts through real-time diagnostics and advanced machine-learning algorithms.Central to this framework is Linac_Gen, an accelerated simulation tool that incorporates convolutional neural networks, random forests, and genetic algorithms to provide up to a tenfold speedup in optimizing the accelerator geometry model. An EPICS translator layer ensures interoperability by efficiently mapping lattice parameters across diverse simulation platforms.Our EPICS-based framework supports multiple operational modes—monitoring, passive learning, closed-loop control, and online learning—covering the entire machine lifecycle. By leveraging HPC resources and multi-objective optimization techniques, the digital twin enables adaptive trajectory correction, real-time fault detection, and predictive modeling of beam stability. This comprehensive approach paves the way for robust, high-intensity operation and data-driven accelerator R&D at Fermilab.

Pathak, Abhishek [Fermilab]↗