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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Measurement of the Sixth-Order Cumulant of Net-Proton Multiplicity Distributions in Au + Au Collisions at s NN = 27 , 54.4, and 200 GeV at RHIC

According to first principle Lattice QCD calculations, the transition from quark-gluon plasma to hadronic matter is a smooth crossover in the region µB ≤ Tc. As a result, higher-order cumulants and their ratios are predicted to be negative, C 6 /C 2 < 0, for example. In this paper, we report the first measurement of the midrapidity net-proton C 6 /C 2 from 27, 54.4 and 200 GeV Au+Au collisions at RHIC. The dependence on collision centrality and kinematic acceptance in (p T, y ) are analyzed. While for 27 and 54.4 GeV collisions the C 6 /C 2 values are close to zero within uncertainties, it is observed that for 200 GeV collisions, the C 6 /C 2 ratio becomes progressively negative from peripheral to central collisions. Transport model calculations without critical dynamics predict values around zero. These observations seem to favor a smooth crossover in the high energy nuclear collisions at RHIC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Incommensurate magnetic orders and topological Hall effect in the square-net centrosymmetric EuGa 2 Al 2 system

Neutron diffraction on the centrosymmetric square-net magnet EuGa 2 Al 2 reveals multiple incommensurate magnetic states (AFM1, 2, 3) in zero field. In applied field, a new magnetic phase (A) is identified from magnetization and transport measurements, bounded by two of the μ 0 H=0 incommensurate magnetic phases (AFM1, helical, and AFM3, cycloidal) with different moment orientations. Moreover, magnetotransport measurements indicate the presence of a topological Hall effect, with maximum values centered in the A phase. Together, these results render EuGa 2 Al 2 a material with noncoplanar or topological spin texture in applied field. X-ray diffraction reveals an out-of-plane (OOP) charge density wave (CDW) below T CDW ~50 K while the magnetic propagation vector lies in plane below T N =19.5 K. Together these data point to a new route to realizing in-plane noncollinear spin textures through an OOP CDW. In turn, these noncollinear spin textures may be unstable against the formation of topological spin textures in an applied field.

36 MATERIALS SCIENCE↗
DOE OSTI2018

IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks

Deep neural networks (DNN) excel at extracting patterns. Through representation learning and automated feature engineering on large datasets, such models have been highly successful in computer vision and natural language applications. Designing optimal network architectures from a principled or rational approach however has been less than successful, with the best successful approaches utilizing an additional machine learning algorithm to tune the network hyperparameters. However, in many technical fields, there exist established domain knowledge and understanding about the subject matter. In this work, we develop a novel furcated neural network architecture that utilizes domain knowledge as high-level design principles of the network. We demonstrate proof-of-concept by developing IL-Net, a furcated network for predicting the properties of ionic liquids, which is a class of complex multi-chemicals entities. Compared to existing state-of-the-art approaches, we show that furcated networks can improve model accuracy by approximately 20-35%, without using additional labeled data. Lastly, we distill two key design principles for furcated networks that can be adapted to other domains.

Sakloth, Khushmeen↗
DOE OSTI2022

Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning

Terrestrial ecosystems play a central role in the global carbon cycle and affect climate change. However, our predictive understanding of these systems is still limited due to their complexity and uncertainty about how key drivers and their legacy effects influence carbon fluxes. Here, we propose an interpretable Long Short-Term Memory (iLSTM) network for predicting net ecosystem CO 2 exchange (NEE) and interpreting the influence on the NEE prediction from environmental drivers and their memory effects. We consider five drivers and apply the method to three forest sites in the United States. Besides performing the prediction in each site, we also conduct transfer learning by using the iLSTM model trained in one site to predict at other sites. Results show that the iLSTM model produces good NEE predictions for all three sites and, more importantly, it provides reasonable interpretations on the input driver's importance as well as their temporal importance on the NEE prediction. Additionally, the iLSTM model demonstrates good across-site transferability in terms of both prediction accuracy and interpretability. The transferability can improve the NEE prediction in unobserved forest sites, and the interpretability advances our predictive understanding and guides process-based model development.

Liu, Siyan↗
DOE OSTI2020

Net Load Redistribution Attacks on Nodal Voltage Magnitude Estimation in AC Distribution Networks

A high penetration level of smart devices and communication networks increases the threat of cyber-attacks in the distribution system. In this paper, we model a hidden, coordinated, net load redistribution attack (NLRA) in an AC distribution system. Based on local information of an attack region, the attacker’s goal is to create violations in nodal voltage magnitude estimation. Acting as a system operator equipped with global AC state estimation and bad data detection, we validate the stealthiness of the hidden NLRA in multiple attack cases. Simulation results on a modified PG&E 69-node distribution system show the validity of the proposed NLRA. The influence of NLRA on the distribution system is assessed and the impact of attack regions, attack timing, and system observability is also revealed.

Zhang, Hang↗
DOE OSTI2019

A 4×4 electrooptic silicon photonic switch fabric with net neutral insertion loss

We present a strictly nonblocking 4×4 electrooptic silicon photonic switch fabric with on-chip gain. The switch integrates 12 Mach-Zehnder cells in a 3-stage topology equipped with fast electrooptic phase shifters, and thermooptic phase trimmers. To compensate for the losses of the fabric, a 4-channel GaInAsP/InP semiconductor optical amplifier array is flip-chip attached into an etched cavity in the silicon photonic chip with butt-coupled waveguide interfaces. The chip is wirebonded to a CMOS driver that provides push-pull drive to each elementary Mach-Zehnder cell. We demonstrate an optical switch assembly with net neutral insertion loss in the C-band together with nanosecond-scale reconfiguration time.

42 ENGINEERING↗
DOE OSTI2012

Net Interchange Schedule Forecasting of Electric Power Exchange for RTO/ISOs

Neighboring independent system operators (ISOs) exchange electric power to enable efficient and reliable operation of the grid. Net interchange (NI) schedule is the sum of the transactions (in MW) between an ISO and its neighbors. Effective forecasting of the amount of actual NI can improve grid operation efficiency. This paper presents results of a preliminary investigation into various methods of prediction that may result in improved prediction accuracy. The methods studied are linear regression, forward regression, stepwise regression, and support vector machine (SVM) regression. The work to date is not yet conclusive. The hope is to explore the effectiveness of other prediction methods and apply all methods to at least one new data set. This should enable more confidence in the conclusions.

Electrical Power Exchange↗
DOE OSTI2020

A Data-Driven Method for Adaptive Reserve Requirement Estimation via Probabilistic Net Load Forecasting

The University of Colorado Boulder Boulder, CO, 80309, USA With the increasing penetration of renewable energy, power systems are subject to more uncertainty. This makes power system reserve scheduling more challenging. Most of the current reserve requirement determination methods calculate reserve requirements based on historical data, which does not consider the real-time or future system uncertainty. In this paper, a data-driven method is developed to determine the non-spinning reserve requirement (NSRR) in the Electric Reliability Council of Texas (ERCOT) system. The method follows the procedure of the current ERCOT method while adaptively determining the NSRR based on probabilistic net load forecasts. Case studies with two years of ERCOT data show that the developed method significantly reduces the NSRR by introducing an adaptive temporal resolution and update rate. Sensitivity analysis with different forecasting and percentile thresholds indicates the flexibility of the developed method.

non-spinning reserve↗
DOE OSTI2013

An Ensemble Approach for Forecasting Net Interchange Schedule

The net interchange schedule (NIS) is the sum of the transactions (MW) between an ISO/RTO and its neighbors. Effective forecasting of the submitted NIS can improve grid operation efficiency. This paper applies a Bayesian model averaging (BMA) technique to forecast submitted NIS. As an ensemble approach, the BMA method aggregates different forecasting models in order to improve forecasting accuracy and consistency. In this study, the BMA method is compared to two alternative approaches: a stepwise regression method and an artificial neural network (ANN) trained for NIS forecasting. In our comparative analysis, we use field measurement data from the Pennsylvania, New Jersey, and Maryland (PJM) Regional Transmission Organization (RTO) to train and test each method. Our preliminary results indicate that ensemble-based methods can provide more accurate and consistent NIS forecasts in comparison to non-ensemble alternate methods.

Vlachopoulou, Maria↗
DOE OSTI2015

The impacts of net metering on utility profits and rates: Case studies of two prototypical utilities

Heated debates about the impact of net metering on utility shareholders and ratepayers have surfaced in some of the larger state solar markets and will only become more pronounced and widespread as solar costs decline and deployment accelerates. In order to inform these discussions, we performed a scoping analysis to quantify the magnitude of the financial impacts of distributed PV on utility shareholders and ratepayers, and that assesses the potential efficacy of various options for mitigating those impacts. We quantify the impacts of customer-sited PV for two prototypical investor-owned utilities: a vertically integrated utility located in the southwest and a wires-only utility and default service supplier located in the northeast. For each utility, we model the impacts of customer-sited PV over a 20-year period, estimating changes to utility costs, revenues, average rates, and utility shareholder earnings and return-on-equity.

Barbose, G↗
DOE OSTI2023

Implications of Battery Storage for Solar Net-Metering Reforms

Compensation structures for residential solar PV are evolving toward a model that incentivizes the use of battery storage to maximize solar self-consumption. Using metered data from 1,800 residential customers across six U.S. utilities, we show that batteries operated solely in this manner often provide no grid value, due to misalignment with market prices. Incentivizing customers to discharge storage in response to market prices, particularly on infrequent peak load days would greatly enhance storage dispatch value. However, doing so requires consideration of local distribution network impacts. We illustrate a net billing design that yields a storage dispatch value equal to 50-70% of its maximum potential market value, without materially degrading solar self-consumption levels or increasing local grid stress.

Barbose, Galen↗
DOE OSTI2017

An Analytical Time–Domain Expression for the Net Ripple Produced by Parallel Interleaved Converters

We apply modular arithmetic and Fourier series to analyze the superposition of N interleaved triangular waveforms with identical amplitudes and duty-ratios. Here, interleaving refers to the condition when a collection of periodic waveforms with identical periods are each uniformly phase-shifted across one period. The main result is a time-domain expression which provides an exact representation of the summed and interleaved triangular waveforms, where the peak amplitude and parameters of the time-periodic component are all specified in closed-form. Analysis is general and can be used to study various applications in multi-converter systems. This model is unique not only in that it reveals a simple and intuitive expression for the net ripple, but its derivation via modular arithmetic and Fourier series is distinct from prior approaches. The analytical framework is experimentally validated with a system of three parallel converters under time-varying operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Distribution Feeder-Scale Fast Frequency Response via Optimal Coordination of Net-load Resources Part I: Solution Design

This work is the first of a two-part series that develops and experimentally demonstrates a first-of-its-kind hierarchical control solution for optimally dispatching thousands of deferrable loads and distributed energy resources (DERs) across a distribution feeder to provide fast frequency response (FFR) within 500 ms to the bulk power system. This approach rapidly coordinates resources online after a frequency event occurs, allowing fast-changing, behind-the-meter (BTM) resources to be incorporated and aggregate FFR power set points to be achieved more quickly and accurately than existing approaches. We also present a solution for determining the optimal amount of headroom to operate solar inverters with to minimize opportunity cost while ensuring the FFR response viability of a building with the inverter and deferrable loads. In Part I, we develop practical algorithms for fast, cost-based optimal dispatch at multiple aggregation scales (single building, multiple buildings, and full distribution feeder), establish their optimality, and demonstrate via simulation that they are faster than state-of-the-art, coordinated frequency response approaches. In Part II, the entire platform is implemented and experimentally verified using a unique power hardware-in-the-loop demonstration, including more than 100 powered loads and DERs connected to a real-world distribution network model and over 10,000 net-load resources dispatched.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Distribution Feeder-Scale Fast Frequency Response via Optimal Coordination of Net-load Resources Part II: Large-Scale Demonstration

This work is the second of a two-part series in which we develop and experimentally demonstrate a hierarchical control solution for optimally coordinating thousands of deferrable loads and distributed energy resources (DERs) to provide fast frequency response (FFR) from an entire distribution feeder. In Part I, we developed and proved practical algorithms for fast, cost-based optimal dispatch and for determining the optimal amount of headroom to operate solar inverters with to support FFR dispatch while minimizing opportunity cost. Simulation results in Part I demonstrated the advantages of the hierarchical dispatch approach in being able to maintain fast solution times needed for FFR even when the problem size increases. In Part II, we implement the algorithms developed in Part I in a novel, large-scale power hardware-in-the-loop experiment including embedded controllers and more than 100 powered appliance loads and DER connected to a simulated real-world distribution system with more than 10,000 controlled devices. Experimental results from multiple scenarios confirm that the optimal FFR dispatch approach scales well and can optimally coordinate more than 10,000 net-load resources across a distribution network while achieving hardware response times within 500 ms, which is not possible using state-of-the-art optimal coordination approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Voltage Stability Constrained Moving Target Defense Against Net Load Redistribution Attacks

Moving target defense (MTD) using distributed flexible AC transmission system (D-FACTS) devices is a promising defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation. However, all existing studies myopically perturb the reactance of D-FACTS lines without considering the system voltage stability. In this paper, we first illustrate voltage instability induced by MTDs in a three-bus system. To address this issue, we further propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow and voltage stability indices. We mathematically derive the sensitivity matrix of voltage stability index to line impedance, on which an optimization problem for maximizing voltage stability index is formulated. This framework is tested on the IEEE 14-bus and the IEEE 118-bus transmission systems, in which net load redistribution attacks are launched by sophisticated attackers. Here, the simulation results show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. We conduct case studies with and without the proposed framework under different MTD planning and operational methods. The impacts of the proposed two methods on attack detection effectiveness and system economic metrics are also revealed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Microgrid Service Restoration Incorporating Unmonitored Automatic Voltage Controllers and Net Metered Loads

Islanded microgrids may experience voltage and frequency instability due to uncontrolled state changes of voltage regulation devices and inaccurate demand forecasts. Uncontrolled state changes can occur if optimal microgrid restoration and dispatch algorithms, used for generating control commands for distributed energy resources, do not incorporate the behavior of automatic controllers of voltage regulation devices. Inaccurate demand forecasts may be encountered since post-outage demand of behind-the-meter net metered (NM) loads can vary significantly from their historical NM profiles. Here, this paper proposes an optimization formulation which allows optimal control of voltage regulators and capacitor banks without remote control and communication capabilities. A generalized demand model for NM loads is proposed which incorporates the cold load pickup phenomenon and their time varying post-outage demand in accordance with the IEEE 1547 standard. The time dependent optimal control formulation and the NM demand model are integrated in a sequential microgrid restoration algorithm by linearization of the involved logic propositions. A detailed case study on the unbalanced IEEE 123-node test system in OpenDSS validates the effectiveness of the proposed approach.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Soil net nitrogen mineralization and leaching under Miscanthus × giganteus and Zea mays

Abstract The winter fallow period common in annual cropping systems leaves soils vulnerable to erosion and nutrient loss, especially to nitrogen (N) leaching. This vulnerability can be mitigated with perennial crops that have living roots in the ground year‐round. The mechanisms, magnitude, and consistency with which perennial crops retain N are not clear. We used an experiment to test whether a perennial crop, miscanthus ( Miscanthus × giganteus Greef et Deu.), would leach less N than continuous maize ( Zea mays L.) and how soil net N mineralization (N min ) may explain observed leaching under varied environment and management conditions. The experiment included three crossed factors: (1) cropping system (maize, juvenile miscanthus = 1–2 years old, mature miscanthus = 3–4 years old); (2) N fertilization (0 and 224 kg N ha −1 ); and (3) environment (four site‐years at two locations in Iowa, USA, that differed in climate and soil fertility). We measured N cycling dynamics, including: inorganic soil N (ammonium + nitrate), in situ N min , N leaching, crop N uptake, and calculated system N use efficiency. There were many complex interactions among factors. On average, cumulative N min under juvenile miscanthus was 111% greater than maize, but as miscanthus matured, there was no difference in N min between the perennial crop and maize. There was no difference in N leaching between juvenile miscanthus and maize, but mature miscanthus decreased N leaching by 42% and 88% compared to maize (with and without N fertilization, respectively). Across all treatments, there was no relationship between N min and N leaching, suggesting other mechanisms are regulating N leaching. Overall, mature miscanthus shows promise as a tool to reduce N losses in areas dominated by annual row‐crops.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Aboveground Rather Than Belowground Productivity Drives Variability in Miscanthus × giganteus Net Primary Productivity

Quantifying the carbon (C) uptake of Miscanthus × giganteus ( M × g ) in both aboveground and belowground structures (e.g., net primary productivity (NPP)) and differences among methodological approaches is crucial. Our objectives were to directly measure Mxg NPP and evaluate the effects of nitrogen application, location, and belowground biomass sampling methods. We hypothesize that increased nitrogen application increases the overall NPP of M × g and that quantifying rhizome biomass using excavations will produce the lowest variability between replicates. We collected biomass from mature M × g stands from three locations in Iowa with three nitrogen application rates and one site in Illinois. We destructively sampled at two time points, when rhizome mass is anticipated to be at a minimum (initial) and anticipated to be at its maximum (peak). Biomass was collected from 1 × 1 m quadrats in which one in-clump and one beside-clump cores were collected and then excavated to 30 cm depth to extract all rhizomes. We found that aboveground M × g NPP ranged from 15.4 Mg DM ha –1 year –1 to 36.4 Mg DM ha –1 year–1 and belowground M × g NPP ranged from 4.4 Mg DM ha –1 year –1 to 19.6 Mg DM ha –1 year –1 . M × g NPP varied across sites, fertilization, and calculation assumptions. Aboveground NPP (yield) was on average 68.7% of the total NPP. Root-to-shoot ratios at peak biomass decreased with nitrogen application rate, from an average of 1.9 for 0 N plots to 0.89 for 224 N fertilized plots. There was more variation in core data than from excavations; however, when in-clump and beside-clump cores were averaged together, core and excavation averages were not different. Overall, these results show that the range of mature M × g NPP is driven by aboveground productivity, influenced by nitrogen application and site. Our results provide useful data to constrain agro-ecosystem models and provide crucial insights for future perennial belowground sampling.

Hartman, Theodore [Univ. of Illinois at Urbana-Cha↗