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DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Peer-to-peer communication control for resilient operations of networked cyberphysical systems

This report includes two main accomplishments of the peer-to-peer communication control for resilient operation of networked microgrids project in FY24, which include a scheme for cyberattack-aware coordination of networked microgrids for supporting voltages of bulk power systems and a scheme for price signal-based operations of EV-rich networked microgrids with mixed ownership. First, the cyberattack-aware scheme enables networked microgrids to distributedly determine the amount of reactive power injection to support the voltage of bulk power system (BPS) in a fair manner. In this scheme, a risk-informed algorithm is presented to generate the peer-to- peer (P2P) communication graph with minimal risk of attack on communication links. To deal with cyberattacks on MG controllers, the resilient consensus algorithm (CA) is utilized for MG controllers to robustly estimate the total reactive power headroom, from which the MGs can accurately provide the needed amount of reactive power injection for supporting the voltage of BPS. The CA implementation and performance within the P2P communication framework are demonstrated on the IEEE 39-bus system with 6 microgrids contained in the distribution feeder under different cyberattack scenarios. Second, the price-based scheme enables the usage of the real-time price signal for the operations of electric vehicle (EV)-rich networked-microgrids with mixed ownership, in which not all the microgrids can communicate with the distribution system operator (DSO). In this scheme, a max consensus is introduced to enable the real-time price signal to be propagated from the DSO to all the microgrids, from which each microgrid controller will manage the DERs to balance the load demand and the power injection from the EV charging stations within its microgrid. Numerical results over one day with 288 slots of 5-minute intervals on the modified 123-node test feeder including 3 microgrids with high penetration of EV are presented to evaluate how the price signal affects the operations of networked microgrids under different charging strategies of the EV charging stations. The result indicates that our proposed EVCS (dis)charging strategy, which leverages the flexibility of EVs to support the grid through discharging during peak demand, proves to be a cost-effective solution that reduces operational costs while improving the social welfare of EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Secure Control Regions for Distributed Stochastic Systems with Application to Distributed Energy Resource Dispatch: Preprint

With the increasing connectedness and interdependence of systems that are stochastic in nature, the issue of how to manage and coordinate them for safe operation has evidently become more important. In many networked system architectures, the system-wide output has to be delicately managed; often within a prescribed set of bounds. In this paper, a novel control framework is proposed where the bounds on the outputs are translated into independent bounds on the controllable inputs of each subsystem. The main benefit of this framework is that respecting the individual control bounds suffices to guarantee that the system-wide outputs will remain within safe boundaries. Since the systems are assumed to be stochastic, the bounds on the output are introduced as probabilistic chance constraints. The benefits of this framework are demonstrated by applying it to the control of distributed energy resources in a distribution networks where main goal is to keep the voltage magnitudes with their prescribed bounds. The control bounds are evaluated using real data on an IEEE test system.

chance constrained optimization↗

DOE OSTI2022

Secure Control Regions for Distributed Stochastic Systems with Application to Distributed Energy Resource Dispatch

With the increasing connectedness and interdependence of systems that are stochastic in nature, the issue of how to manage and coordinate them for safe operation has evidently become more important. In many networked system architectures, the system-wide output must be delicately managed, often within a prescribed set of bounds. In this paper, a novel control framework is proposed where the bounds on the outputs are translated into independent bounds on the controllable inputs of each subsystem. The main benefit of this framework is that respecting the individual control bounds suffices to guarantee that the system-wide outputs will remain within safe boundaries. Because the systems are assumed to be stochastic, the bounds on the output are introduced as probabilistic chance constraints. The benefits of this framework are demonstrated by applying it to the control of distributed energy resources in a distribution network where the main goal is to keep the voltage magnitudes within their prescribed bounds. The control bounds are evaluated using real data on an IEEE test system.

chance constrained optimization↗

DOE OSTI2024

Ion-specific phenomena limit energy recovery in forward-biased bipolar membranes

The ability for bipolar membranes (BPMs) to interconvert voltage and pH makes them attractive materials for use in energy conversion and storage. Reverse-biased BPMs, which use electrical voltage to dissociate water into acid and base, have become increasingly well studied. However, forward-biased BPMs (FB-BPMs), in which voltage is extracted from pH gradients through recombination, require further study. Here physics-based modeling elucidates how the complex coupling of transport and kinetics dictates the performance of FB-BPMs in electrochemical devices. Simulations reveal that the open-circuit potential of FB-BPMs is dictated by the balance of ion recombination and crossover, where recombination of buffering counter-ions attenuates the open-circuit potential. Counter-ion mass-transport limitations and uptake of ionic impurities limit achievable current densities by reducing the applied pH gradient or the available fixed-charge sites that mediate recombination. Further, the model highlights the importance of selective ion management in mitigating energy losses and provides insight into the rational material design of FB-BPMs for energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Combined Effects of Electric Vehicle Charging and Rooftop Solar Integration on Voltage Imbalance in Residential Distribution Networks

Residential electric vehicle (EV) chargers, as single phase loads, contribute to unbalanced voltage drops across phases, while rooftop solar systems, as single phase generators, can exacerbate voltage imbalance by causing unbalanced voltage increases. This paper investigates combined effects of residential EV charging and rooftop solar generation on voltage imbalance in residential distribution grids. The study examines these simultaneous impacts using the IEEE 8500-node test system, enhanced with a secondary network to realistically model the EV chargers and rooftop solar integration. To account for the variability and uncertainty in the EV charging loads and solar generation, a Monte Carlo approach is employed to capture and quantify the simultaneous impact of the EV charging and rooftop solar integration. In this approach, multiple influencing factors are considered, including state-of-charge (SOC), maximum charging power levels, and geographic distribution of chargers. The results provide practical insights for utilities and stakeholders, offering expectations for planning and operating strategies that effectively manage the increasing adoption of EVs and solar power while maintaining grid reliability.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗

DOE OSTI2020

The TRANSCEND University Consortium: Theme 2 - Site Decommissioning, Deconstruction and Remediation - 20329

This paper will discuss the aims, objectives and progress to-date under Theme 2 of the TRANSCEND consortium project: Site decommissioning, deconstruction and remediation. Decommissioning nuclear sites involves waste retrieval, decontamination, deconstruction and, where necessary, containment and/or remediation of the remaining structure and surrounding land. Critical to management of these processes is limiting radiation exposure for the workforce, restricting the spread of radionuclides in groundwater, surface water and airborne particulates, and minimising the volume of contaminated waste for disposal. The aim of Theme 2 research is to develop new technologies for monitoring, remediation and containment that serve to minimise the volume of radioactively contaminated waste for disposal, for application prior to, during and after retrieval, deconstruction and decontamination operations. Prior research, conducted under the previous DISTINCTIVE project, demonstrated that colloidal silica grout can penetrate low permeability materials (including cement) for hydraulic barrier formation, and improved sorption capacity. The silica grout can be injected at surface using extremely small (potentially gravity-driven) fluid pressures, without the need for borehole drilling. Current work is investigating the erodibility of silica-grouted soils for inhibition of airborne and water-borne particulates as well as enhancing the grout's sorption capacity by addition of other materials to provide a chemical, as well as hydraulic, barrier to subsurface migration. EK remediation uses low voltage DC current to control migration of contaminants in porous media as well as to remove or degrade them. Researchers in the consortium have already demonstrated that low-energy ex-situ EK techniques can be used to provide remediation and volume minimisation for AWE legacy wastes in the UK. Under the current project researchers are building EK test cells containing simulated site materials at laboratory and intermediate(m)-scales to: remove, focus or degrade contaminants (remediation or waste minimisation); and direct subsurface water, chemical and colloid flow (fencing/containment or forced migration). This lab-based research is being informed by numerical models of EK processes that can subsequently be used to design full-scale on-site applications by nuclear site holders. Research under theme 2 of TRANSCEND will ultimately combine novel non-invasive detection technologies with EK techniques and colloidal silica grout barriers, to optimise the containment of radionuclide contamination in soils. Thus, allowing us to detect in-situ contamination, mobilise it to a selected location and grout it in-situ, prior to the initiation of decommissioning and deconstruction operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Black-box optimization of CT acquisition and reconstruction parameters: a reinforcement learning approach

Protocol optimization is critical in Computed Tomography (CT) for achieving desired diagnostic image quality while minimizing radiation dose. Due to the inter-effect of influencing CT parameters, traditional optimization methods rely on the testing of exhaustive combinations of these parameters. This poses a notable limitation due to the impracticality of exhaustive parameter testing. This study introduces a novel methodology leveraging Virtual Imaging Trials (VITs) and reinforcement learning to more efficiently optimize CT protocols. Computational phantoms with liver lesions were imaged using a validated CT simulator and reconstructed with a novel CT reconstruction Toolkit. The optimization parameter space included tube voltage, tube current, reconstruction kernel, slice thickness, and pixel size. The optimization process was done using a Proximal Policy Optimization (PPO) agent which was trained to maximize the Detectability Index (d’) of the liver lesion for each reconstructed image. Results showed that our reinforcement learning approach found the absolute maximum d’ across the test cases while requiring 79.7% fewer steps compared to an exhaustive search, demonstrating both accuracy and computational efficiency, offering a efficient and robust framework for CT protocol optimization. The flexibility of the proposed technique allows for use of varying image quality metrics as the objective metric to maximize for. Our findings highlight the advantages of combining VIT and reinforcement learning for CT protocol management.

Fenwick, David [Duke University Medical Center]↗

DOE OSTI2024

Performance and Durability of Hybrid Fuel Cell Systems for Class-8 Long Haul Trucks

Hybrid fuel cell-battery configurations are investigated that overcome thermal management issues in fuel cell powertrains for heavy-duty Class 8 trucks. The battery is sized so that it has sufficient capacity to provide supplemental power and energy on a hill climb transient at end-of-life. A dynamic load sharing strategy is developed to distribute the power demand between the fuel cell system (FCS) and the energy storage system in a manner that optimizes their lifetimes. The FCS end-of-life is identified as the terminal point beyond which the stack cannot generate the rated power with target power density at 0.7 V and 40 °C ambient temperature. Reaching the target lifetime with a-Pt/C cathode catalyst in one hybrid configuration requires voltage clipping to 813 mV, idle power limited to 50 kW, catalyst overloading to 0.45 mg cm -2 total Pt in anode and cathode, and 44% active membrane area oversizing. The stack and FCS drive cycle efficiencies decrease by 4.2% and 5.4%, respectively, during the electrode lifetime. Further, the FCS performance, durability and cost are compared with the targets of 68% peak efficiency, 0.30 mg cm -2 total Pt loading, 2.5 kW/g PGM Pt group metal (PGM) loading, 750 mW cm -2 power density, 25,000-h lifetime and $80/kW cost.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

A Dynamic Pricing Method to Manage the Impact of EV Charging on the Grid Using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

EV charging, dynamic pricing, grid-informed chargi↗

DOE OSTI2025

A dynamic pricing method to manage the impact of EV charging on the grid using RL

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Pathways to the Next-Generation Power System With Inverter-Based Resources: Challenges and recommendations

Managing the stability of today's electric power systems is based on decades of experience with the physical properties and control responses of large synchronous generators. Today's electric power systems are rapidly transitioning toward having an increasing proportion of generation from nontraditional sources, such as wind and solar (among others), as well as energy storage devices, such as batteries. In addition to the variable nature of many renewable generation sources (because of the weather-driven nature of their fuel supply), these newer sources vary in size - from residential-scale rooftop systems to utility-scale power plants - and they are interconnected throughout the electric grid, both from within the distribution system and directly to the high-voltage transmission system. Most important for our purposes, many of these new resources are connected to the power system through power electronic inverters. Collectively, we refer to these sources as inverter-based resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Peer-to-Peer Energy Trading under Network Constraints Based on Generalized Fast Dual Ascent

We report the wide deployment of renewable energy resources, combined with a more proactive demand-side management, is inducing a new paradigm in both power system operation and electricity market trading, which especially boosts the emergence of the peer-to-peer (P2P) market. A more flexible local market mechanism is highly desirable in response to fast changes in renewable power generation at the distribution network level. Moreover, large-scale implementation of P2P energy trading inevitably affects the secure and economic operation of the distribution network. This paper presents a new P2P electricity trading framework with distribution network security constraints considered using the generalized fast dual ascent method. First, an event-driven local P2P market framework is presented to facilitate short-term or immediate local energy transactions. Then, the sensitivity analysis of nodal voltage and network loss with respect to nodal power injections is used to evaluate the impacts of P2P transactions on the distribution network, which ensures the secure operation of the distribution system. Thereby, the external operational constraints are internalized, and the cost of P2P energy trading can be appropriately allocated in an endogenous way. Moreover, a generalized fast dual ascent method is employed to implement distributed market-clearing efficiently. Finally, numerical results indicate that the proposed model could guarantee secure operation of the distribution system with P2P energy trading, and the solution method enjoys good convergence performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Managing photon flux in a miniaturized photoionization detector

Miniaturized photoionization detectors (PIDs) are used in conjunction with gas chromatography systems to detect volatile compounds in gases by collecting the current from the photoionized gas analytes. PIDs should be inexpensive and compatible with a wide range of analyte species. One such PID is based on the formation of a He plasma in a dielectric barrier discharge (DBD), which generates vacuum UV (VUV) photons from excited states of He to photoionize gas analytes. There are several design parameters that can be leveraged to increase the ionizing photon flux to gas analytes to increase the sensitivity of the PID. To that end, the methods to maximize the photon flux from a pulsed He plasma in a DBD-PID were investigated using a two-dimensional plasma hydrodynamics model. The ionizing photon flux originated from the resonance states of helium, He(3P) and He(2 1 P), and from the dimer excimer He 2 *. While the photon flux from the resonant states was modulated over the voltage pulse, the photon flux from He 2 * persisted long after the voltage pulse passed. Several geometrical optimizations were investigated, such as using an array of pointed electrodes. However, increasing the capacitance of the dielectric enclosing the plasma chamber had the largest effect on increasing the VUV photon fluence to gas analytes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

The Quantum Nature of the Neutrino

Over the last 100 years we have learned much about the neutrino, but there remain interesting questions about this weakly interacting particle. In particular, at LLNL we are developing an experiment to measure the quantum nature of the neutrino. The 2015 long range plan recom mended tonne-scale neutrinoless double beta decay experiments as the top new project priority and this experiment will target the quantum nature of the neutrino. The LLNL team is motivated and focused on developing the best technology for this experiment which is a liquid xenon time projection chamber called nEXO. Work on nEXO at LLNL started in 2015 with an LDRD and program development funds to de velop the nEXO concept, publish sensitivity predictions, explore alternatives and risks, and to build a credible project team and this effort is on going. In addition, we received research funding from DOE-SC NP and LLNL manages pre-conceptual R&D for the nEXO collaboration a portion of which is executed at LLNL. LLNL has a long history of building large projects, science projects and time projection chambers, but nEXO is in fact the first project of this scale that LLNL is prepared to lead for DOE-SC NP. We have the tools, skills, people and motivation to make nEXO a reality. The current program devel opment dollars are used to prepare the nEXO concept for down select and CD1. These internal LLNL dollars pay for a number of things including project staff to organize the nEXO collaboration for the various reviews, to develop the draft plans and structure to manage the project as well as setting up external advisory committees. The DOE-SC NP base funding is targeted at simulation and analysis of the nEXO concept in preparation for the down select and refinement of the under standing of the detector as well as scientific effort on the large xenon test stand (LXTS) that will burn down one of the largest risks to the nEXO project. Lastly, LLNL is leading the pre-conceptual R&D effort and managing the funds for the nEXO collaboration. LLNL continues to build the best scientific team for nEXO and this year that includes adding Ethan Bernard to lead the efforts on the LXTS. We will also soon add a new postoc, Samuel Hedges, in the fall to the LLNL nEXO team. The effort this year was influenced by the portfolio review, and there were a number of scientific activities led by LLNL to prepare for this review. In addition, we again took a lead role on the new sensitivity paper as well as publishing a paper based analyzing the effects of skin xenon in nEXO. LLNL leads the software and analysis for the project and we continued work in this area as well. High voltage remains a significant risk for the project and we continue to make progress on the LXTS that will mitigate this risk. Lastly we remain active in looking at how to scale the technology to larger scales, and expect to produce a paper on this topic in the near future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Impact of Different Thermal Gradients on the Dynamics of Cylindrical Lithium-ion Cells Subject to Accelerated Aging and on Module Performance

This study investigates the impacts of applying different thermal gradient patterns to cylindrical lithium-ion cells in a module on cell dynamics (temperatures, current flows, state of charge), module performance (evolution of resistance, capacity, and energy versus cycle number), and module lifetime. The thermal gradients were generated using cooling plates (CPs) with three different flow-field designs, namely, straight, perpendicular, and U-turn. The study uses computational fluid dynamics (CFD), the pseudo-two-dimensional (P2D) battery model, capacity loss and increased impedance due to the growth of a solid-electrolyte-interphase, and the electric current distribution from module terminals to cells that depends on the series-parallel electrical connections among the cells. The impact of the thermal gradient (resulting from the CP designs) on the variability in resistance, current, state of charge, and voltage among the cells was analyzed and linked to differences in the module's performance. Applying a thermal gradient to parallel-connected strings of series-connected cells led to variation in the current through each parallel string and an imbalance in the voltage of series-connected cells. Module performance is poorer when the thermal gradient causes a voltage imbalance than when it causes a current imbalance. Module performance becomes the worst when both current variation and voltage imbalance happen together. For instance, the module's lifetime (estimated as reaching 80% of its initial capacity) varied by 5% to 17.5%, depending on the magnitude and pattern of the imposed thermal gradient. As the relative orientation between thermal gradients and cells' electrical connectivity influences the module's performance, appropriate consideration should be given to the choice of the CP, especially if large thermal gradients are allowed.

Battery thermal management↗

DOE OSTI2020

A High-Speed High-Power-Density Non-Heavy Rare-Earth Permanent Magnet Traction Motor

There has been a global push for higher torque density and lower cost traction motors. The use of non-heavy rare-earth (non-HRE) permanent magnet materials in traction motors are being investigated for the sustainability, profitability and affordability of electric vehicles and to broaden their adoption. A 20,000-rpm permanent magnet traction motor using non-HRE magnet materials is proposed. A dual three-phase winding configuration driven by a segmented dual three-phase drive is proposed to reduce the current ripple, and as a result, the DC Link capacitor, as well as to ease the voltage constraint at high speed and eliminate any risk of uncontrolled regeneration. Furthermore, the dual winding configuration enables a fault tolerant design which is useful for reliability. The paper presents comprehensive electromagnetic, thermal and mechanical designs and analyses using an integrated approach. The results have shown that the design is robust against demagnetization and confirmed its thermal and mechanical viability.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Electrochemical Model Assessment of Strategies for Fast Charge

The United States Department of Energy (DOE) has identified extreme fast charging (XFC) as a critical challenge that must be overcome in order to achieve widespread adoption of electric vehicles. DOE’s eXtreme Fast Charge and Cell Evaluation (XCEL) program seeks to reduce charge time to 10-15 minutes for a 200+ Wh/kg Li-ion battery. This presentation for DOE’s Vehicle Technologies Program Annual Merit Review summarizes the XCEL team’s work developing electrochemical models to interpret data and applying them to identify best strategies to achieve fast charge. Strategies include advanced electrode architectures, elevated temperature charging, novel charge protocols, advanced electrolytes, thermal management and suppression of heterogeneities that cause early onset of the damaging Li plating side reaction.

47 OTHER INSTRUMENTATION↗