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DOE OSTI2024

Enabling DER visibility using a distributed dissemination network

The electrical grid is currently undergoing a series of rapid transformational changes that have resulted in the introduction of new actors and operational schemes that have fragmented the data and control planes. To help address the issue, this paper describes the implementation of a sensor-oriented, distributed data dissemination network that seeks to eliminate data silos. The implementation is based on the DGSS architecture previously described in [1]. The developed product seeks to facilitate the seamless integration of multi-operator, multi-origin, multi-domain sensor data by using a distributed systems approach. The proposed solution decouples the sensor’s data streams from the application-specific infrastructure and migrates them into a software-defined databus that can be configured to suit the end application’s demands. To further validate DGSS capabilities, a DER oriented use case has been developed.

Sensor Dissemination Networks, Enhanced DER visibi↗

DOE OSTI2022

A novel approach for produced water treatment: Supercritical water oxidation and desalination

Produced water generated from oil and gas operations contains significant quantities of environmentally hazardous hydrocarbons, organic chemicals, and inorganic salts. Environmental regulations with impaired water disposal mandates produced water treatment and desalination. Industry standard desalination technologies are energy-intensive and mandate extensive produced water pre-treatment including removal of hydrocarbons constituents for efficient operations. Herein this study investigates a novel process intensification approach integrating supercritical water oxidation (SCWO) unit operation with a supercritical water desalination (SCWD) process for energy efficient produced water treatment and desalination. The coupled SCWD-SCWO process is found to be very energy-efficient and cost effective than existing industry standard desalination technologies. For energy efficient operation, the heat generated from the SCWO of hydrocarbons present in the produced water is used for power generation using a high efficiency and low-cost re-heat Rankine cycle process. The cost of treating produced water with proposed SCWO-SCWD process is independent of the salt concentration. The proposed process has the potential to offer step-change improvements over conventional processes in both the efficiency and cost of produced water treatment: for example, a cost and energy saving of 70% and 100% is calculated for the treatment of produced water containing 250 g/l salt and 10.6 g/l hydrocarbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Linearised Fokker–Planck collision model for gyrokinetic simulations

We introduce a gyrokinetic, linearised Fokker–Planck collision model that satisfies conservation laws and is accurate at arbitrary collisionalities. The differential test-particle component of the operator is exact; the integral field-particle component is approximated using a spherical harmonic and a modified Laguerre polynomial expansion developed by Hirshman and Sigmar (1976 Phys. Fluids 19 1532). The numerical methods of the implementation in the δf-gyrokinetic code stella (Barnes et al 2019 J. Comput. Phys. 391 365–80) are discussed, and conservation properties of the operator are demonstrated. The collision model is then benchmarked against the collision model of the gyrokinetic solver GS2 in the limiting cases of a reduced test-particle collision operator and energy- and momentum-conserving operator. The accuracy of the full collision model is investigated by solving the parallel Spitzer-Härm problem for the transport coefficients. It is shown that retaining collisional energy flux and higher-order terms in the field-particle operator reduces errors in the transport coefficients from 10%–25% for a simple momentum- and energy-conserving model to under 1%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Modified Andronov-Hopf Oscillator-Based Grid-Forming Converter with Emulated Virtual Cable for Enhanced Power Sharing Performance

Nonlinear oscillator-based grid-forming converters offer superior dynamic and steady-state performance, making them an attractive solution for interconnecting renewable resources. This paper proposes a novel modified Andronov-Hopf oscillator to enhance the operating spectrum and facilitate the integration of renewable energy sources. An inner loop controller based on the Lyapunov energy function is implemented to achieve robust stability and performance, while a virtual cable emulation strategy enables seamless parallel operation. Comprehensive modeling and simulation studies validate the effectiveness of the proposed system, demonstrating its capabilities in addressing diverse operating scenarios, including grid faults, renewable energy fluctuations, and parallel operation. The proposed solution exhibits fast transient response, robust stability, and flexible operation, making it a valuable contribution to the field of renewable energy integration. The results of this study can be used to inform the design and implementation of next-generation grid-forming converters, enabling a more sustainable and reliable energy future. Additionally, the proposed system's ability to operate in both grid-connected and islanded modes makes it an ideal candidate for remote and off-grid renewable energy applications. The proposed solution's scalability and modularity also make it suitable for large-scale renewable energy integration. The proposed system is verified through MATLAB/Simulink and PLECS simulations, demonstrating its effectiveness in ensuring robust and efficient operation.

Andronov-Hopf Oscillator (AHO)↗

DOE OSTI2023

Situational Awareness of Grid Anomalies (SAGA) for Visual Analytics—Near-Real-Time Cyber-Physical Resiliency Through Machine Learning

The Situational Awareness of Grid Anomalies (SAGA) project built upon foundational power system tools developed at the National Renewable Energy Laboratory (NREL) integrated with an ever-increasing set of Gridmetrics data extracted from the cable television (CATV) broadband network infrastructure while assimilating other time-series geospatial data and information, such as weather and cyber-physical phenomena, to demonstrate a disruptive technology for power system data analytics relying on existing infrastructure. Three research thrusts supported (1) visual analytics, (2) cyber-physical power system simulation, and (3) anomaly detection. SAGA created technology that leverages, couples, and fortifies two vastly different realms - power and broadband - to increase the resiliency of the power grid in the face of increasing cyberattacks and operational challenges related to integrating DERs. The exploration of potential synergies of broadband-enabled grids resulted in identifying a mutually beneficial symbiosis that can increase the resiliency of both power and broadband services. Broadband networks perform better with reliable power and are good at providing real-time measurements that identify where the grid is under attack, is failing, or is weak. Likewise, sensor-starved distribution grids perform better and can be more reliable when their operation is buttressed with observations of broadband-detected anomalies. Future research can explore broadband's contribution to continuing to improve grid resiliency, reliability, and cost-effective operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Joint ptycho-tomography with deep generative priors

Abstract Joint ptycho-tomography is a powerful computational imaging framework to recover the refractive properties of a 3D object while relaxing the requirements for probe overlap that is common in conventional phase retrieval. We use an augmented Lagrangian scheme for formulating the constrained optimization problem and employ an alternating direction method of multipliers (ADMM) for the joint solution. ADMM allows the problem to be split into smaller and computationally more efficient subproblems: ptychographic phase retrieval, tomographic reconstruction, and regularization of the solution. We extend our ADMM framework with plug-and-play (PnP) denoisers by replacing the regularization subproblem with a general denoising operator based on machine learning. While the PnP framework enables integrating such learned priors as denoising operators, tuning of the denoiser prior remains challenging. To overcome this challenge, we propose a denoiser parameter to control the effect of the denoiser and to accelerate the solution. In our simulations, we demonstrate that our proposed framework with parameter tuning and learned priors generates high-quality reconstructions under limited and noisy measurement data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Overview of the New Beam Physics Research at the IOTA/FAST Facility

The Fermilab Accelerator Science and Technology (FAST) facility is dedicated to the exploration of novel concepts in accelerator and beam physics, and the development of a robust workforce, in order to enable and enhance next-generation particle accelerators. FAST comprises a high-brightness superconducting electron linac, and a storage ring, the Integrable Optics Test Accelerator (IOTA). Experiments in the most recent operational run include studies of nonlinear integrable lattices; tracking of single electrons; precise characterization of undulator radiation; studies with low-momentum-compaction lattices; and ultra-wide range beam diagnostics based on Photomultiplier tubes. In the linac, experiments on noise in intense electron bunches were conducted. The IOTA proton injector, currently being commissioned, will enable a diverse program on space-charge-dominated beams. Research areas include non-invasive beam profile monitoring for proton beams; beam dynamics with electron lenses; halo suppression, feedback systems, and electron cooling. In this presentation, we provide an overview of the recent results and highlight future plans together with opportunities for collaboration.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Null states and time evolution in a toy model of black hole dynamics

Abstract Spacetime wormholes can provide non-perturbative contributions to the gravitational path integral that make the actual number of statese S in a gravitational system much smaller than the number of states$$ {e}^{S_{\textrm{p}}} $$ e S p predicted by perturbative semiclassical effective field theory. The effects on the physics of the system are naturally profound in contexts in which the perturbative description actively involvesN=O(e S ) of the possible$$ {e}^{S_{\textrm{p}}} $$ e S p perturbative states; e.g., in late stages of black hole evaporation. Such contexts are typically associated with the existence of non-trivial quantum extremal surfaces. However, by forcing a simple topological gravity model to evolve in time, we find that such effects can also have large impact forN≪e S (in which case no quantum extremal surfaces can arise). In particular, even for smallN, the insertion of generic operators into the path integral can cause the non-perturbative time evolution to differ dramatically from perturbative expectations. On the other hand, this discrepancy is small for the special case where the inserted operators are non-trivial only in a subspace of dimensionD≪e S . We thus study this latter case in detail. We also discuss potential implications for more realistic gravitational systems.

Physics↗

DOE OSTI2026

Smart Charging of Fleet and Personal Electric Vehicles through Joint Vehicle-to-Grid Optimization

As electric vehicle (EV) adoption accelerates, vehicle-to-grid (V2G) strategies offer advantages over unmanaged charging (V0G) by enhancing grid stability, reducing fleet operation costs, and supporting integration of variable generation resources. This research develops a day-ahead optimization framework linked with agent-based simulations to evaluate coordinated V2G participation by fleet and personal EVs under 5 energy-pricing settings in Austin, Texas. Three scenarios (V0G, fleet-only V2G, and joint-V2G) are examined, considering real-time price and grid profiles, health-damage costs, and operational constraints for both fleet and personal EVs. Results show how V2G scenarios shift fleet EV charging to mid-day while enabling strategic battery-discharge during evening peaks, mitigating grid stress and lowering EV energy costs. V2G delivers close to 80% energy-cost savings for a 2000-EV fleet in Austin on grid-stressed days, with 55% lower charging pollutant outputs. Joint-V2G amplifies system-level benefits by complementing fleet discharge, but smart-charging equipment costs can offset those benefits.

Electric vehicle↗

DOE OSTI2024

Quasilinear modelling of collisional trapped electron modes

The simplification of collision operators is necessary for quasilinear turbulence modelling used with integrated modelling frameworks, such as the gyrokinetic code QuaLiKiz. The treatment of collisions greatly impacts the accuracy of trapped electron mode (TEM) modelling, which is necessary to predict the electron heat flux and the balance between inward and outward particle fluxes. In particular, accurate particle flux predictions are necessary to successfully model density peaking in the tokamak core. We explored two ways of improving collisional TEM model reduction for tokamak core plasmas. First, we carried out linear GENE simulations to study the complex interplay between collisions and trapped electrons. We then used these simulations to define an effective trapped fraction to characterize the collisional TEM based on two key parameters, the local inverse-aspect ratio $\epsilon$ and the collisionality $\nu ^\ast$. One aspect missing from analytical TEM research is that the collisional frequency and the bounce-transit frequency are both velocity dependent; this effective trapped fraction takes both into account. In doing so, we determined that two parameters are not enough to model the collisional TEM, as an additional third free parameter was necessary. We determined that this model, as currently formulated, is not suitable for integrated modelling purposes. Second, we directly improved QuaLiKiz's Krook operator, which relies on two free parameters. We determined that these parameters required adjustments against higher-fidelity collisional models. In order to improve density profile predictions when paired with integrated models, we refined the Krook operator by using GENE simulations as a higher-fidelity point of comparison. We then demonstrate strong improvement of density peaking predictions of QuaLiKiz within the integrated modelling framework JETTO.

fusion plasma↗

DOE OSTI2026

Spherical tokamak physics research in preparation for the operation of NSTX-U

The National Spherical Torus Experiment Upgrade (NSTX-U) is preparing to resume operation, representing a crucial step toward realizing compact, cost-effective fusion pilot plants. In advance of this, extensive modeling and data analysis have been conducted to advance the physics basis for low-aspect-ratio, high-performance plasma regimes, focusing on three core objectives: confinement and stability, power and particle handling, and steady-state operation. Significant progress has been made in understanding the electron temperature flattening in high-β plasmas, which is shown to be driven by a complex interplay of magnetohydrodynamic instabilities (e.g. non-resonant infernal modes), fast-ion-driven Alfvén eigenmodes, and electron and ion-scale micro-instabilities, particularly Kinetic Ballooning Modes (KBMs), whose destabilization is strongly dependent on parallel magnetic field fluctuations (δB ∥ ). Furthermore, a new gyrokinetic critical pedestal model was developed, accurately predicting pedestal structure by identifying KBMs as the primary stability limit, offering a critical constraint for future high-confinement scenarios. To address the challenge of high heat flux, novel liquid lithium plasma-facing components were modeled. The analysis confirmed that lithium vapor shielding is a self-regulating mechanism for heat mitigation, while also emphasizing that strong main ion parallel flow is essential to minimize core lithium contamination. Finally, progress toward steady-state operation was anchored by developing the required physics basis and control tools. This includes predictive modeling for reversed magnetic shear sustainment, demonstrating that magnetic island-induced bootstrap current reduction is negligible in STs, and advancing real-time control and disruption avoidance capabilities. The development of high-speed surrogate models (e.g. MMMNet) provides computationally efficient tools vital for non-inductive scenario optimization and integrated, low-disruptivity operations planned for NSTX-U.

NSTX-U↗

DOE OSTI2023

Blockchain Empowered Provenance Framework for Sensor Identity Management and Data Flow Security in Fossil-based Power Plants

The overall goals of this project are divided into 3 important phases. First, a peer-to-peer SCADA network is to be established where identity profile of sensors from fossil-power plants will be stored in an immutable manner in order to verify data flow integrity in real time. Second, it is aimed to develop a Blockchain-based provenance platform to audit equipment operations along with data and process integrity violations. In this phase, various operational rules will be incorporated in the ledger on behalf of the operating sensor so its abnormal use can be easily detected. In addition, it is aimed to achieve provenance when the rate of transactions is exceedingly high, thus enabling to design a scalable provenance scheme that can work in real time when number of data collecting points or sensor units increase in fossil-based power plants. Finally, a working testbed will be developed to integrate the Blockchain platform with sensor-based fossil power plant comprising of Remote Terminal Units (RTU) and SCADA devices. Using multiple Raspberry-PIs mimicking the role of RTUs that are interfaced with multiple sensors devices will be deployed to serve as a critical component of fossil power plant and the performance metrics such as throughput, latency, bootstrapping time, etc., will be evaluated on the testbed.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Thermal Ratcheting Analysis of TEDS Packed-bed Thermocline Energy Storage Tank - Modeling Methodology and Data Validation

This report investigates numerical modeling methods for thermal ratcheting analysis of packed-bed thermal energy storage (TES) tank and discusses the validation results via comparison with experimental data. The experimental data obtained from various design characteristics of packed-bed thermocline tanks, including the Thermal Energy Distribution System (TEDS) TES tank at Idaho National Laboratory (INL), were used to validate thermal and mechanical models developed in this study to evaluate the thermal ratcheting potential. The thermal model was shown to predict the transient thermal propagation through the packed-bed thermocline tanks generally well. However, a larger discrepancy was observed during the comparison with the data from TEDS, presumably due to the uncertainty of boundary conditions given from the experiment. Based on the comparative study between the thermal model predictions and experimental data of various packed-bed thermocline tanks, potential improvements were suggested for the future TEDS experiments for more precise validation study. For mechanical (thermally induced stress) analysis, two different modeling approaches were tested to evaluate hoop stress applied to the packed-bed TES tank wall, which is a major cause of thermal ratcheting process: (i) infinite rigidity model and (ii) Drucker-Prager (DP) model. The ‘model (i)’ is a conservative method with infinite rigidity assumption of granular filler inside a TES tank, whereas the ‘model (ii)’ is a method that takes into account more realistic processes such as thermal expansion of filler and tank wall as well as inter-particle interactions during the cyclic operation of a packed-bed TES tank. The validity of each modeling method was examined by comparing the numerical simulation with the experimental data obtained from the packed-bed TES tank for Solar One pilot plant. Then, the effects of various model parameters were discussed to evaluate the thermal ratcheting potential of the TEDS TES tank. The preliminary thermal ratcheting analysis implies that the TEDS TES tank will hold its structural integrity during the normal operation cycles.

25 ENERGY STORAGE↗

DOE OSTI2022

Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network.

Neural operators have recently become popular tools for designing solution maps between function spaces in the form of neural networks. Differently from classical scientific machine learning approaches that learn parameters of a known partial differential equation (PDE) for a single instance of the input parameters at a fixed resolution, neural operators approximate the solution map of a family of PDEs [6, 7]. Despite their success, the uses of neural operators are so far restricted to relatively shallow neural networks and confined to learning hidden governing laws. In this work, we propose a novel nonlocal neural operator, which we refer to as nonlocal kernel network (NKN), that is resolution independent, characterized by deep neural networks, and capable of handling a variety of tasks such as learning governing equations and classifying images. Our NKN stems from the interpretation of the neural network as a discrete nonlocal diffusion reaction equation that, in the limit of infinite layers, is equivalent to a parabolic nonlocal equation, whose stability is analyzed via nonlocal vector calculus. The resemblance with integral forms of neural operators allows NKNs to capture long-range dependencies in the feature space, while the continuous treatment of node-to-node interactions makes NKNs resolution independent. The resemblance with neural ODEs, reinterpreted in a nonlocal sense, and the stable network dynamics between layers allow for generalization of NKN’s optimal parameters from shallow to deep networks. This fact enables the use of shallow-to-deep initialization techniques [8]. Our tests show that NKNs outperform baseline methods in both learning governing equations and image classification tasks and generalize well to different resolutions and depths.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Power and particle exhaust for the ARC fusion power plant

To successfully show that fusion is an attractive energy source, the ARCTM fusion power plant will need to operate with a robust, integrated power and particle exhaust solution. To maximise ARC’s fusion power output while avoiding excessive erosion of the plasma-facing components, we will need to radiatively dissipate most of the power crossing the last-closed flux surface, injecting radiating impurities such as argon or neon to access divertor detachment. Divertor detachment will need to be integrated with a high-performance core plasma, and with efficient impurity pumping to prevent the accumulation of helium ash in the core. To access and control detachment in high-performance plasmas, we have designed ARC with up–down-symmetric divertors, with secondary X-points in long, tightly baffled outer legs. Using a core-edge modelling workflow, we predict that with this divertor design, ARC will access detachment with modest argon seeding in the divertor (c Ar,div ∼0.9%), which should have minimal impact on the core ( Z eff,core <0.5) for reasonable argon enrichment (c Ar,div /c Ar,core =6). Due to the high predicted divertor neutral pressure (p div ∼20 Pa), we predict that ARC will sufficiently pump helium to limit ash accumulation in the core (c He,core <2%) for a helium enrichment of c He,div /c He,core =0.4. ARC’s divertor design is expected to increase the stability of a detachment front in the outer divertor leg, helping to prevent divertor reattachment during smaller heat-flux transients such as scrape-off-layer filaments associated with the quasi-continuous exhaust regime. However, this buffering will not be sufficient to prevent divertor reattachment during large type-I edge-localised modes (ELMs), and as such these will need to be avoided on ARC. Experiments on SPARC will be used to select an integrated scenario which avoids or mitigates type-I-ELMs while maintaining access to detachment, good core fusion performance and sufficient impurity exhaust. SPARC experiments will also be used to finalise ARC’s divertor design, by studying the impact of magnetic and first-wall geometry on detachment stability, impurity enrichment and neutral baffling under conditions similar to those expected for ARC. In conclusion, our analysis finds that ARC will have a viable power and particle exhaust solution which is compatible with high-power operations, and this solution will be validated in experiments on SPARC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter

Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the distinct characteristics of instruments and operations still hamper further integration and interoperability across mid-infrared (MIR) soil spectral libraries. In this study, we conducted a large-scale ring trial experiment to understand the lab-to-lab variability of multiple MIR instruments. By developing a systematic evaluation of different mathematical treatments with modeling algorithms, including regular preprocessing and spectral standardization, we quantified and evaluated instruments' dissimilarity and how this impacts internal and shared model performance. We found that all instruments delivered good predictions when calibrated internally using the same instruments' characteristics and standard operating procedures by solely relying on regular spectral preprocessing that accounts for light scattering and multiplicative/additive effects, e.g., using standard normal variate (SNV). When performing model transfer from a large public library (the USDA NSSCKSSL MIR library) to secondary instruments, good performance was also achieved by regular preprocessing (e. g., SNV) if both instruments shared the same manufacturer. However, significant differences between the KSSL MIR library and contrasting ring trial instruments responses were evident and confirmed by a semi-unsupervised spectral clustering. For heavily contrasting setups, spectral standardization was necessary before transferring prediction models. Non-linear model types like Cubist and memory-based learning delivered more precise estimates because they seemed to be less sensitive to spectral variations than global partial least square regression. In summary, the results from this study can assist new laboratories in building spectroscopy capacity utilizing existing MIR spectral libraries and support the recent global efforts to make soil spectroscopy universally accessible with centralized or shared operating procedures.

58 GEOSCIENCES↗

DOE OSTI2023

On the Feasibility of Market Manipulation and Energy Storage Arbitrage via Load-Altering Attacks

Around the globe, electric power networks are transforming into complex cyber–physical energy systems (CPES) due to the accelerating integration of both information and communication technologies (ICT) and distributed energy resources. While this integration improves power grid operations, the growing number of Internet-of-Things (IoT) controllers and high-wattage appliances being connected to the electric grid is creating new attack vectors, largely inherited from the IoT ecosystem, that could lead to disruptions and potentially energy market manipulation via coordinated load-altering attacks (LAAs). In this article, we explore the feasibility and effects of a realistic LAA targeted at IoT high-wattage loads connected at the distribution system level, designed to manipulate local energy markets and perform energy storage (ES) arbitrage. Realistic integrated transmission and distribution (T&D) systems are used to demonstrate the effects that LAAs have on locational marginal prices at the transmission level and in distribution systems adjacent to the targeted network.

25 ENERGY STORAGE↗

DOE OSTI2022

Radiative pulsed L-mode operation in ARC-class reactors

Abstract A new ARC-class, highly-radiative, pulsed, L-mode, burning plasma scenario is developed and evaluated as a candidate for future tokamak reactors. Pulsed inductive operation alleviates the stringent current drive requirements of steady-state reactors, and operation in L-mode affords ELM-free access to ∼ 90 % core radiation fractions, significantly reducing the divertor power handling requirements. In this configuration the fusion power density can be maximized despite L-mode confinement by utilizing high-field to increase plasma densities and current. This allows us to obtain high gain in robust scenarios in compact devices with P fus > 1000 MW despite low confinement. We demonstrate the feasibility of such scenarios here; first by showing that they avoid violating 0D tokamak limits, and then by performing self-consistent integrated simulations of flattop operation including neoclassical and turbulent transport, magnetic equilibrium, and radiofrequency current drive models. Finally we examine the potential effect of introducing negative triangularity with a 0D model. Our results show high-field radiative pulsed L-mode scenarios are a promising alternative to the typical steady state advanced tokamak scenarios which have dominated tokamak reactor development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗