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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Verification of neoclassical toroidal viscosity induced by energetic particles

The thermal particles contributed neoclassical toroidal viscosity (NTV) have been successfully developed and explored by many impressive works such as the study by Shaing et al. [Phys. Plasmas 10, 1443 (2003)] and Zhu et al. [Phys. Rev. Lett. 96, 225002 (2006)]. In this work, the scope of the NTV study is extended to explore the contribution of energetic particles (EPs) through both theory and experiments. In theory, the existence of the NTV torque due to the precessional drift resonance of trapped EPs is identified based on the equivalence between the NTV torque and the perturbed drift kinetic energy [J. Park, Phys. Plasmas 18, 110702 (2011)]. Toroidal modeling with the Magneto Resistive Spectrum - drift Kinetic code [Y. Liu, Phys. Plasmas 15, 112503 (2008)], based on this equivalence, indicates that trapped EPs can contribute a significant amount of the NTV torque. Meanwhile, this work also focuses on developing the dedicated DIII-D experiments in the presence of the n = 2 external magnetic perturbation to verify the EP induced NTV (EP-NTV) by measuring the change of the NTV torque while varying the angle and the voltage of the neutral beam injection. However, the developed experiments have been unable to create conditions necessary to clearly demonstrate the presence of EP-NTV. The main challenge is separating the resonant and non-resonant momentum transport responses in the plasma. Finally, the experience, gained from this study, can help the further exploration of EP-NTV in the future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Measured gain suppression in FBK LGADs with different active thicknesses

In recent years, the gain suppression mechanism has been studied for large localized charge deposits in Low-Gain Avalanche Detectors (LGADs). LGADs are a thin silicon detector with a highly doped gain layer that provides moderate internal signal amplification. Using the CENPA Tandem accelerator at the University of Washington, the response of LGADs with different thicknesses to MeV-range energy deposits from a proton beam were studied. Three LGAD prototypes of 50 μm, 100 μm, and 150 μm were characterized. The devices' gain was determined as a function of bias voltage, incidence beam angle, and proton energy. This study was conducted in the scope of the PIONEER experiment, an experiment proposed at the Paul Scherrer Institute to perform high-precision measurements of rare pion decays. LGADs are considered for the active target (ATAR), and energy linearity is an important property for particle ID capabilities.

Particle tracking detectors↗
DOE OSTI2021

PMU-data-driven Event Classification in Power Transmission Grids

This paper presents an event classification in transmission grids. The convolutional neural network (CNN)-based classifier is proposed to capture the temporal similarity of time-synchronized data stream from phasor measurement units (PMUs). The proposed CNN is trained using Bayesian optimization to search for the best hyperparameters. The effectiveness of the proposed event classification is validated through the real-world dataset from the U.S. transmission grids. This dataset includes line outage, transformer outage, frequency, and oscillation events. The validation process also includes different PMU outputs, such as voltage magnitude, phase angle, current magnitude, frequency, and rate of change of frequency (ROCOF). The results show that ROCOF gives the best classification performance compared to other PMU outputs. In addition, it is shown that the classifier trained with a larger dataset has higher accuracy. Moreover, the superiority of the proposed method is validated through comparison with other state-of-the-art classification methods.

Niazazari, Iman↗
DOE OSTI2024

Newton-Raphson AC Power Flow Convergence Based on Deep Learning Initialization and Homotopy Continuation

Power flow forms the basis of many power system studies. With the increased penetration of renewable energy, grid planners tend to perform multiple power flow simulations under various operating conditions and not just selected snapshots at peak or light load conditions. Getting a converged AC power flow (ACPF) case remains a significant challenge for grid planners especially in large power grid networks. This paper proposes a two-stage approach to improve Newton-Raphson ACPF convergence and was applied to a 6102 bus Electric Reliability Council of Texas (ERCOT) system. The first stage utilizes a deep learning-based initializer with data re-training. Here a deep neural network (DNN) initializer is developed to provide better initial voltage magnitude and angle guesses to aid in power flow convergence. This is because Newton-Raphson ACPF is quite sensitive to the initial conditions and bad initialization could lead to divergence. The DNN initializer includes a data re-training framework that improves the initializer's performance when faced with limited training data. The DNN initializer successfully solved 3,285 cases out of 3,899 non-converging dispatch and performed better than random forest and DC power flow initialization methods. ACPF cases not solved in this first stage are then passed through a hot-starting algorithm based on homotopy continuation with switched shunt control. The hot-starting algorithm successfully converged 416 cases out of the remaining 614 non-converging ACPF dispatch. In conclusion, the combined two-stage approach achieved a 94.9% success rate, by converging a total of 3,701 cases out of the initial 3,899 unsolved cases.

Deep learning↗
DOE OSTI2022

TCF-20-20213: Advanced Power Distribution Sensing and Communications through the Cable TV Broadband Network (Final Report. Period of Performance: June 2020 to June 2022)

To enable the rapid, widespread commercial availability of secondary distribution grid voltage and phase angle data, the DOE OE Technology Commercialization Fund (TCF) project: 1) created a new American National Standard for next-generation grid power quality sensing and communications, 2) created a new prototype broadband-based standard-compliant grid power sensing system for use by utilities and others, and 3) improved by several orders of magnitude the spatiotemporal scale of the in-progress DOE CESER project: Situational Awareness of Grid Anomalies (SAGA) for Visual Analytics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Study of the Protection Improvements for a Weak Grid Area With High Inverter-Based Resources (IBRs)

This project designs enhanced protection scheme for the real-world weak grid area with a high penetration of IBRs. As the existing protection schemes are originally designed for traditional synchronous machines, we first evaluate if the protection scheme will continue to operate reliably in systems with high levels of IBRs. Hardware relays are tested using a controller-hardware-in-the-loop setup. PSCAD electromagnetic transient simulation with IBR original equipment manufacturer black-box models is used to perform fault studies and generate COMTRADE data, which are replayed by a real-time digital simulator (RTDS) to feed input to the hardware relays. Three scenarios are analyzed: normal operation, an N-1 contingency, and an IBR-only scenario. The evaluation results reveal the following: 1) the protection scheme remains reliable under normal conditions and N-1 contingencies and 2) in IBR-only scenarios, differential protection (87L) continues to operate reliably, whereas local protection elements, such as distance and directional elements, fail because of the lack of regulated negative sequence current contributed by IBRs. Enhanced protection is designed to address the challenge of lack of negative sequence current from IBRs, including increased restraining factors a2 and k2 to block 32Q or using V instead QV ORDER for ground faults, enhanced mho distance element with voltage and phase angle supervision for L-L faults. The efficacy of enhanced protection logic is validated and proven to work reliably. Additionally, IEEE Std. 2800-2022 negative sequence current compliant GFL and GFM IBRs from another vendor are tested and proven to work reliably without need for enhanced logic. Therefore, this work provides valuable decision-making for utilities facing protection system challenges due to IBRs, either designing enhanced protection scheme or requesting their IBRs being IEEE Std. 2800-2022 compliant to produce regulated negative sequence current for protection relay to make correct decision.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Decoupled Droop Control Strategy for Cascaded Multicell Inverter with Low-Frequency Modulation

Cascaded multicell inverter (CMI), featured by its merits of modularity and fault-tolerance, is suitable for medium-voltage applications without using bulky step-up transformers. However, little research has reported grid-forming control of the CMI for the application in the power grid with high penetrations of inverter-interfaced generation. To bridge this research gap, this paper proposes a novel droop control strategy for the CMI with a low-frequency modulation to offer inertia and reactive power support to the power grid. A decoupled Q/V droop control strategy is proposed to eliminate the coupling effect from the P/ω control loop caused by the phase-angle difference between the voltages of the CMI and the grid. The output of the Q/V control loop is set as the reference voltage for each cell of the CMI, which makes the CMI naturally a voltage source to provide a grid-forming capability. Finally, the proposed control strategy shows great active and reactive power regulation and sharing capability, which is validated by simulation on two 100 kW, 2.4 kV CMIs connected in parallel to a power grid.

14 SOLAR ENERGY↗
DOE OSTI2022

A multi-scale time-series dataset with benchmark for machine learning in decarbonized energy grids

The electric grid is a key enabling infrastructure for the ambitious transition towards carbon neutrality as we grapple with climate change. With deepening penetration of renewable resources, the reliable operation of the electric grid becomes increasingly challenging. In this paper, we present PSML, a first-of-its-kind open-access multi-scale time-series dataset, to aid in the development of data-driven machine learning (ML)-based approaches towards reliable operation of future electric grids. The dataset is synthesized from a joint transmission and distribution electric grid to capture the increasingly important interactions and uncertainties of the grid dynamics, containing power, voltage and current measurements over multiple spatio-temporal scales. Using PSML, we provide state-of-the-art ML benchmarks on three challenging use cases of critical importance to achieve: (i) early detection, accurate classification and localization of dynamic disturbances; (ii) robust hierarchical forecasting of load and renewable energy; and (iii) realistic synthetic generation of physical-law-constrained measurements. We envision that this dataset will provide use-inspired ML research in safety-critical systems, while simultaneously enabling ML researchers to contribute towards decarbonization of energy sectors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Visual Tool for Assessing Stability of DER Configurations on Three-Phase Radial Networks

Here, we present a method and tool for evaluating the placement of Distributed Energy Resources (DER) on distribution circuits in order to control voltages and power flows. Our previous work described Phasor-Based Control (PBC), a novel control framework where DERs inject real and reactive power to track voltage magnitude and phase angle targets. Here, we employ linearized power flow equations and integral controllers to develop a linear state space model for PBC acting on a three-phase unbalanced network. We use this model to evaluate whether a given inverter-based DER configuration admits a stable set of controller gains, which cannot be done by analyzing controllability nor by using the Lyapunov equation. Instead, we sample over a parameter space to identify a stable set of controller gains. Our stability analysis requires only a line impedance model and does not entail simulating the system or solving an optimization problem. We incorporate this assessment into a publicly available visualization tool and demonstrate three processes for evaluating many control configurations on the IEEE 123-node test feeder (123NF).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Practical Event Location Estimation Algorithm for Power Transmission System Based on Triangulation and Oscillation Intensity

Event location in power systems is quite essential information for system operators to enhance control-room situational awareness capability. Therefore, it is of great importance to develop an event location estimation algorithm for transmission systems with high accuracy. With the development of wide-area measurement system (WAMS) such as FNET/GridEye, and the synchrophasor measurement devices (SMDs) such as frequency disturbance recorders (FDRs), the synchronous measurement data including frequency, voltage amplitude and phase angle can be collected and used for event location estimation. First, the phase angle and rate of change of frequency (RoCoF) trajectories are respectively used for determining two sets of wave arrival time associated with each FDR. Then, a convolutional neural network (CNN) is utilized to determine the wave arrival order to select the more suitable set of wave arrival times for a given case and to perform corresponding modifications. Next, the oscillation intensity associated with each FDR is determined based on phase angle trajectories in the center of inertia (COI) coordinate system. Finally, the multiple criteria for event location estimation are represented. In conclusion, case studies and comparisons between the proposed and previous algorithms using actual and confirmed cases in U.S. power systems are performed to demonstrate the effectiveness and improvement of the proposed algorithm in practical applications.

frequency disturbance recorder (FDR)↗
DOE OSTI2021

Open Source Fault-tolerant Grid Frequency Measurement for Solar Inverters

The Discrete Fourier transform (DFT) based measurement algorithms are one of the most common measurement algorithms for grid parameter estimation such as rms, phase angle, frequency. Over the past few years, many DFT based algorithms have been developed to enhance its measurement accuracy under steady-state and/or dynamic grid conditions. For example, an adaptive band-pass filter utilizing exponential modulation filter has been proposed to reduce measurement errors at the presence of large frequency deviations. Measurement accuracy of different algorithms including FIR filter, extended Kalman filtering (EKF), and enhanced DFT method have been compared in detail under different grid conditions. Two artificial signals that have 90-degree phase difference were constructed by the Clarke transformation to address the frequency spectrum leakage of DFT. A multi-module approach was developed to enhance both steady-state and dynamic measurement accuracies, in which each module was developed to eliminate some specific errors. Besides DFT-based measurement algorithms, some signal model-based algorithms have been developed to further improve the accuracy under dynamic conditions. However, a key drawback of the state-of-the-art algorithms is that they cannot perform measurements accurately during system transient faults. In the Blue Cut Fire event, there was a phase angle jump of about 26 degrees in the voltage waveform during the transient fault. The phase angle jump fault will cause waveform discontinuity, and these algorithms will fail to provide reliable measurements during this period because they typically assume the waveform to be measured is continuous, no matter what method (DFT, PLL, EKF, FIR, or Taylor WLS) is used for estimation. In fact, the measurement errors during the system transient faults like phase-jump is not required in the IEEE Standard. As a result, although a measurement instrument can pass the strict IEEE Standard, it could still be the source of the problem in the future if we have similar system transient faults, which could happen again. Therefore, developing the fault-tolerant measurement technology is the key to solve the problem.

14 SOLAR ENERGY↗
DOE OSTI2026

Transient Stability Study of IEEE 2800-2022 Standard Negative-Sequence-Current Compliant GFM IBRs

The primary function of grid-forming (GFM) inverter-based resources (IBRs) is to maintain voltage and fre- quency/phase angle stability; however, during unbalanced grid faults, IEEE Std. 2800-2022 requires IBRs to inject both positive- and negative-sequence reactive current. Enforcing compliance with this standard could compromise the stability of GFM IBRs under such fault conditions. This paper presents a preliminary transient stability study focused on the power angle stability of GFM IBRs operating in compliance with IEEE Std. 2800 during unbalanced faults. The goal is to assess potential stability issues associated with the standard's current injection requirements under fault ride-through conditions. The results show that injecting positive-sequence current with d-axis priority during unbalanced faults better preserves the power angle stability than the q-axis priority while still enabling negative-sequence current injection. These findings suggest that, to ensure stability, GFM IBRs might need to partially comply with IEEE Std. 2800 by prioritizing positive-sequence current injection along the d-axis.

14 SOLAR ENERGY↗
DOE OSTI2020

Matrix converter operation in current control mode with regulation of output voltage vector

A matrix converter system having a current control mode operation is provided. The matrix converter system includes a matrix converter that includes a plurality of switches. A unity current reference vector having an amplitude of one is determined that defines an angle and frequency of an output current vector as a function of a reference phase angle, which is a function of the output current vector and an output voltage vector representing feedback signals of a multiphase signal output to a load. The unity current reference vector is used to control the matrix converter, to cause the output current vector to be aligned with the unity current reference vector. A unity voltage reference vector having an amplitude of one is provided that defines a reference angle and frequency as a function of a zero phase angle. The output voltage vector and the unity voltage reference vector are aligned to determine the reference phase angle as an angle between the aligned output voltage vector and the output current vector.

42 ENGINEERING↗
DOE OSTI2020

Matrix converter operating in current control mode using feed forward signals

A matrix converter system having a current control mode operation is provided. The system includes a matrix converter having a switching matrix. The matrix converter is coupled at its low-voltage side to a generator and at its output load side to a load. A controller having a pulse width modulation (PWM) control circuit is configured to control the matrix converter via its switching matrix to increase energy within the internal inductances of the generator when the switching matrix causes a short circuit. A feed forward calculator is configured to calculate a feed forward output phase angle. The feed forward output phase angle is an estimation of an angle between an output current vector and an output voltage vector that represent feedback signals of current and voltage output by the matrix converter. The angular position of the voltage output vector is adjusted as a function of the feed forward output phase angle to align angular position or phase angle of the voltage output vector that represents the voltage output with a selected angular position or phase angle.

42 ENGINEERING↗
DOE OSTI2025

Reconfigurable Magnetotransport in MnBi 2 Te 4 via Gate and Magnetic Field Tuning

The intrinsic magnetic topological insulator MnBi 2 Te 4 is a promising platform for exploring quantum phases with nontrivial band topology and for enabling electrical control over coupled magnetic and electronic phase transitions. In-plane magnetic fields, in particular, offer a distinct means of tuning these properties by strengthening quantized Hall effects, enhancing surface energy gaps, and driving spin reorientation transitions. However, a systematic understanding of how such fields affect magnetotransport is limited. Here, the magnetotransport behavior of few-layer MnBi 2 Te 4 as a function of gate voltage, temperature, and magnetic field angle, with a primary focus on in-plane field effects, are investigated. A gate-tunable crossover in magnetoresistance is observed from positive to negative values under in-plane magnetic fields as the gate voltage is swept below the charge neutrality point at temperatures below the Néel temperature. The in-plane field drives a transition from the antiferromagnetic ground state to a ferromagnetic configuration with spins aligned in-plane, while simultaneously altering the electronic structure, as revealed by gate-dependent transport features. The angle-dependent measurements reveal strongly gate-tunable magnetotransport anisotropy. These results establish in-plane magnetic fields as an effective tuning parameter for modulating spin and charge transport in MnBi 2 Te 4 , advancing prospects for reconfigurable spintronic and topological devices.

MnBi 2 Te 4↗
DOE OSTI2025

Small-Signal Stability of Grid-Forming Inverters Using Current-Limiting and Frequency Stabilization

This paper presents a small-signal stability analysis of grid-forming (GFM) inverters under current-limiting conditions. It examines how adjustments in virtual impedance angles, implemented through advanced current-limiting and frequency stabilization techniques, influence small-signal stability. This paper studies a GFM inverter control integrating a fictitious power technique stabilizing primary control by adding a virtual power term and a hybrid current limiter integrating virtual impedance in the anti-wind-up feedback with current reference saturation limiting. A small-signal model is developed to assess the impact of virtual impedance angles on GFM inverter dynamics during grid disturbances, such as voltage drops. The findings indicate that although increasing the virtual impedance angle (to make it more inductive) enhances large-signal stability and voltage support during faults, it can induce oscillations and lead to instability if the angle exceeds certain thresholds. Based on the small-signal models, this paper provides design considerations for the current-limiter impedances to ensure reliable GFM inverter behavior under grid disturbances while maintaining small-signal stability.

current limiting↗
DOE OSTI2021

Moiréless correlations in ABCA graphene

Atomically thin van der Waals materials stacked with an interlayer twist have proven to be an excellent platform toward achieving gate-tunable correlated phenomena linked to the formation of flat electronic bands. In this work we demonstrate the formation of emergent correlated phases in multilayer rhombohedral graphene––a simple material that also exhibits a flat electronic band edge but without the need of having a moiré superlattice induced by twisted van der Waals layers. We show that two layers of bilayer graphene that are twisted by an arbitrary tiny angle host large (micrometer-scale) regions of uniform rhombohedral four-layer (ABCA) graphene that can be independently studied. Scanning tunneling spectroscopy reveals that ABCA graphene hosts an unprecedentedly sharp van Hove singularity of 3–5-meV half-width. We demonstrate that when this van Hove singularity straddles the Fermi level, a correlated many-body gap emerges with peak-to-peak value of 9.5 meV at charge neutrality. Mean-field theoretical calculations for model with short-ranged interactions indicate that two primary candidates for the appearance of this broken symmetry state are a charge-transfer excitonic insulator and a ferrimagnet. Finally, we show that ABCA graphene hosts surface topological helical edge states at natural interfaces with ABAB graphene which can be turned on and off with gate voltage, implying that small-angle twisted double-bilayer graphene is an ideal programmable topological quantum material.

42 ENGINEERING↗
DOE OSTI2021

Design, modeling and experimental validation of a micro cantilever beam with an electro-controllable twisting ability

The structure design of micro cantilever beams (MCBs), which has a significant effect on MCBs' controllable actuation range, is usually restricted by the establishment of the inner electric circuit. This paper proposes the design of a micro electro-controllable twisting cantilever beam (METCB). The architecture and the fabrication diagram of the proposed METCB are presented before its features are theoretically and experimentally validated. In detail, the analytical validation includes a sequence of two models: electro-thermal and thermo-mechanical. Through these two models, the thermal distribution along the METCB and the deformation brought by the thermal distribution are investigated, respectively. On the basis of the design and equations, the METCB samples have been manufactured using a planar deposition technique with an e-beam evaporator. Two in-site experiments are then conducted to sequentially figure out the upper voltage limit of the inner electric circuit and the maximum temperature limit of the METCB. Finally, another experiment is carried out to explore the relation between the applied voltage and the relative twisting angle of the METCB sample. Here, the theoretical prediction and the observed experiment result both prove the feasibility of the proposed METCB and its electro-controllable twisting ability.

36 MATERIALS SCIENCE↗