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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Impact of Wildfires on Solar Generation, Reserves and Energy Prices

Wildfire seasons in the Western U.S. become more prolonged and intense in recent years bringing significant variability and uncertainty of solar generation. It greatly challenges the bulk power system and electricity market operation managed by California Independent System Operator (CAISO) as California leads both the wildfire records and the solar power integration. This study presents a screening-level analysis of the impact of wildfires on solar generation, operating reserve and energy prices applying historical real-world wildfire and market operation data. To the best of the authors knowledge, it is a first-of-its-kind study and will lay the foundation for market impact quantification and wildfire mitigation strategies design based on projected wildfire activities in future years.

electricity price↗
DOE OSTI2014

Functional approach to exploring climatic and landscape controls of runoff generation: 1. Behavioral constraints on runoff volume

Abstract Inspired by the Dunne diagram, the climatic and landscape controls on the partitioning of annual runoff into its various components (Hortonian and Dunne overland flow and subsurface stormflow) are assessed quantitatively, from a purely theoretical perspective. A simple distributed hydrologic model has been built sufficient to simulate the effects of different combinations of climate, soil, and topography on the runoff generation processes. The model is driven by a sequence of simple hypothetical precipitation events, for a large combination of climate and landscape properties, and hydrologic responses at the catchment scale are obtained through aggregation of grid‐scale responses. It is found, first, that the water balance responses, including relative contributions of different runoff generation mechanisms, could be related to a small set of dimensionless similarity parameters. These capture the competition between the wetting, drying, storage, and drainage functions underlying the catchment responses, and in this way, provide a quantitative approximation of the conceptual Dunne diagram. Second, only a subset of all hypothetical catchment/climate combinations is found to be “behavioral,” in terms of falling sufficiently close to the Budyko curve, describing mean annual runoff as a function of climate aridity. Furthermore, these behavioral combinations are mostly consistent with the qualitative picture presented in the Dunne diagram, indicating clearly the commonality between the Budyko curve and the Dunne diagram. These analyses also suggest clear interrelationships amongst the “behavioral” climate, soil, and topography parameter combinations, implying these catchment properties may be constrained to be codependent in order to satisfy the Budyko curve.

Li, Hong‐Yi↗
DOE OSTI2019

Effect of wavefunction delocalization on shift current generation

We derive upper bounds on the magnitude of shift photocurrent generation of materials in two limiting cases: the flat-band limit of almost-isolated systems such as molecular crystals, and the wide-band limit of one-dimensional or quasi-one-dimensional materials such as ferroelectric polymers or other materials with chain-like motifs. These bounds relate the magnitudes of the shift current bulk photovoltaic effect to materials parameters. In both cases, we find that ratio of electron hopping amplitudes to the band gap plays a vital role in maximizing the amount of nonlinear response. Furthermore, by using the Wannier function formalism, we quantify the effect of long-range hopping amplitudes, showing how delocalization of electronic states gives rise to larger photocurrents. Lastly, these results inform the design and selection of new materials for large shift current generation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Evaluating Demand Response Impacts on Capacity Credit of Renewable Distributed Generation in Smart Distribution Systems

Environmental concerns and depletion of traditional energy lead to the booming development of renewable distributed generation (RDG) in the past decade. However, due to intermittent nature of renewable energy sources, to what extent RDG could provide capacity to power systems becomes a critical issue to the utility company when implementing long-term system strategic (generation expansion) planning. On the other hand, in a smart-grid frame, the popularization of different varieties of demand-side resources enables the system to operate at more flexible modes ever before. The potential variability in load demand not only introduces additional dynamics and uncertainties to the system, but could also affect the reliability benefits of RDG. Therefore, in practice, to effectively estimate the reliability value of RDG in power systems, the potential interaction between generation- and demand-side must be properly captured. In this paper, a study to assess the capacity credit (CC) of RDG in a context of distributed generation system is performed with consideration of the impacts of demand response (DR). A compound reliability model for DR is presented, which considers the uncertainties involved in both instant response and follow-on load recovery processes. On this basis, an assessment framework for the CC of RDG based on sequential Monte Carlo simulation is developed by which the inter-temporal characteristics of DR resources can be fully captured. The numerical study is implemented based on the IEEE-38 bus test case. The calculation results demonstrate that the CC of RDG would depend on a variety of factors, including penetration level, responsiveness of load demand and the correlations between RDG and DR availability. Also, it is shown that accounting for the underlying effect of DR is of absolute importance, otherwise the CC of RDG might be estimated erroneously in real practices.

capacity credit↗
DOE OSTI2021

Optimal Power System Black start using Inverter-Based Generation

Power system black start readiness is part of the system planning. Utility planners perform periodic studies to assess if their power system is capable of total restoration following a black out. Hydro and diesel generators are the most commonly used black start capable resources by power utilities. However, with increasing penetration of solar generation, inverter-based resources can be considered to provide black start capability. Since the solar inverters can be located at multiple locations throughout the power system, and in view of their unique characteristics, an optimal real-time capable plan is helpful for system operators for faster black start. Black start optimization is a multi stage mixed-integer non-linear optimization which is extremely hard to solve. In this paper, we propose an optimal black start methodology that is easier to solve and scalable in real-time. We demonstrate the proposed methodology on two test systems and illustrate how inverter-based resources can contribute and improve power system restoration.

power system restoration, blackstart, Inverter-bas↗
DOE OSTI2023

High-Resolution Synthetic Solar Irradiance Sequence Generation: An LSTM-Based Generative Adversarial Network

The rapid growth of renewable energy resources penetration is bringing more challenges to power system planning and operation. Relevant renewable energy integration studies, such as the capability and dynamic performance of inverter-based resources' primary frequency response and fast frequency response, require high-resolution renewable generation output data that are representative of renewable energy resources. This paper focuses on creating synthetic but realistic solar irradiance data and proposes a long short-term memory-based generative adversarial network to generate high-resolution (second-level) solar irradiance sequences from low-resolution (minute-level) measurements. Combined with a classifier to recognize the solar irradiance patterns, the proposed model is trained using multi-loss functions to accurately capture the temporal correlations among both high-resolution and low-resolution sequences. Verification of the proposed approach is performed on the data set of the Oahu Solar Measurement Grid collected through the National Renewable Energy Laboratory. The results of the case studies demonstrate the proposed approach's capability to capture the statistical characteristics of different solar irradiance patterns and to generate high-quality synthetic solar irradiance sequences in high resolution.

dynamic scheduling↗
DOE OSTI2022

Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models

Here, we propose a new method for inferring the governing stochastic ordinary differential equations (SODEs) by observing particle ensembles at discrete and sparse time instants, i.e., multiple “snapshots.” Particle coordinates at a single time instant, possibly noisy or truncated, are recorded in each snapshot but are unpaired across the snapshots. By training a physics-informed generative model that generates “fake” sample paths, we aim to fit the observed particle ensemble distributions with a curve in the probability measure space, which is induced from the inferred particle dynamics. We employ different metrics to quantify the differences between distributions, e.g., the sliced Wasserstein distances and the adversarial losses in generative adversarial networks. We refer to this method as generative “ensemble-regression” (GER), in analogy to the classic “point-regression,” where we infer the dynamics by performing regression in the Euclidean space. We illustrate the GER by learning the drift and diffusion terms of particle ensembles governed by SODEs with Brownian motions and Lévy processes up to 100 dimensions. We also discuss how to treat cases with noisy or truncated observations. Apart from systems consisting of independent particles, we also tackle nonlocal interacting particle systems with unknown interaction potential parameters by constructing a physics-informed loss function. Finally, we investigate scenarios of paired observations and discuss how to reduce the dimensionality in such cases by proving a convergence theorem that provides theoretical support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Functional approach to exploring climatic and landscape controls on runoff generation: 2 Timing of runoff storm response

Abstract Hortonian overland flow, Dunne overland flow, and subsurface stormflow are the three most dominant mechanisms contributing to both the volume and timing of streamflow in headwater catchments. In this paper, guided by the Dunne diagram, we explore the impacts of climate, soil, and topography on estimated probability distributions of the travel times of each of these three runoff components. In each case, these are expressed in terms of the Connected Instantaneous Response Functions (CIRF) and account for the dynamics of their individual partial effective contributing areas that retain the connectivity to the outlet (instead of the whole catchment area). A spatially distributed hydrological model is used to derive the CIRFs numerically under multiple combinations of climate, soil, and topographic properties. The mean travel times and dimensionless forms of the CIRFs (i.e., scaled by their respective mean travel times) are used to examine both advective and dispersive aspects of catchment's runoff routing response. It is found that the CIRFs, upon nondimensionalization, collapsed to common characteristic shapes, which could be explained in terms of the relative contributions of hillslope and channel network flows, and the size of runoff contributing areas. The contributing areas, particularly for the Dunne overland flow, are themselves found to be governed by the competition between drainage of and recharge to the water table, and could be explained by a dimensionless drainage index which quantifies this competition. The study also reveals simple indicators based on landscape properties that can explain the magnitude of travel times in different catchments.

Li, Hong‐Yi↗
DOE OSTI2023

Search for pair-produced scalar and vector leptoquarks decaying into third-generation quarks and first- or second-generation leptons in $pp$ collisions with the ATLAS detector

A search for pair-produced scalar and vector leptoquarks decaying into quarks and leptons of different generations is presented. It uses the full LHC Run 2 (2015–2018) data set of 139 fb -1 collected with the ATLAS detector in proton–proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV. Scalar leptoquarks with charge -(1/3)$e$ as well as scalar and vector leptoquarks with charge +(2/3)$e$ are considered. All possible decays of the pair-produced leptoquarks into quarks of the third generation ($t, b$) and charged or neutral leptons of the first or second generation ($e, μ, ν$) with exactly one electron or muon in the final state are investigated. No significant deviations from the Standard Model expectation are observed. Upper limits on the production cross-section are provided for eight models as a function of the leptoquark mass and the branching ratio of the leptoquark into the charged or neutral lepton. In addition, lower limits on the leptoquark masses are derived for all models across a range of branching ratios. Two of these models have the goal of providing an explanation for the recent $B$-anomalies. In both models, a vector leptoquark decays into charged and neutral leptons of the second generation with a similar branching fraction. Lower limits of 1980 GeV and 1710 GeV are set on the leptoquark mass for these two models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the World- wide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. This paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application and the performance that was achieved.

HEP↗
DOE OSTI2015

Electricity market design for generator revenue sufficiency with increased variable generation

Here, we present a computationally efficient mixed-integer program (MIP) that determines optimal generator expansion decisions, and hourly unit commitment and dispatch in a power system. The impact of increasing wind power capacity on the optimal generation mix and generator profitability is analyzed for a test case that approximates the electricity market in Texas (ERCOT). We analyze three market policies that may support resource adequacy: Operating Reserve Demand Curves (ORDC), Fixed Reserve Scarcity Prices (FRSP) and fixed capacity payments (CP). Optimal expansion plans are comparable between the ORDC and FRSP implementations, while capacity payments may result in additional new capacity. The FRSP policy leads to frequent reserves scarcity events and corresponding price spikes, while the ORDC implementation results in more continuous energy prices. Average energy prices decrease with increasing wind penetration under all policies, as do revenues for baseload and wind generators. Intermediate and peak load plants benefit from higher reserve prices and are less exposed to reduced energy prices. All else equal, an ORDC approach may be preferred to FRSP as it results in similar expansion and revenues with less extreme energy prices. A fixed CP leads to additional new flexible NGCT units, but lower profits for other technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Molecular Structure Controlled Transitions between Free-Charge Generation and Trap Formation in a Conjugated Copolymer Series

Charge transfer copolymers, where each repeating unit has at least one “donor” and one “acceptor” block, have played important roles in recent advances in organic photovoltaic (OPV) devices, however design criteria for these materials are still not completely clear. Here we show that the well-recognized LUMO-LUMO energy off-set design criterion for OPV materials using a fullerene acceptor is challenged in a series of copolymers, PTRn (n = 3, 5, 7 and 9), where n is the number of fused aromatic rings in the “donor” block and thienothiophene is the “acceptor” block in each repeating unit. Photoexcitation dynamics of PTRn copolymers in solution and BHJ (bulk heterojunction) films demonstrated that local push-pull interactions between the “donor” block and the “acceptor” block weakens with increasing n, whereas the LUMO-LUMO off-set between the polymer and PC71BM (Phenyl-C71-butyric acid methyl ester) increases. Such a counter intuitive trend can be explained by local energetics of each repeating unit as a function of n. The energetic changes transform the copolymer with strong local charge transfer character for efficient hole-electron separation to localized hole-electron pairs with low mobility, despite the apparent increase of the polymer/PC71BM LUMO-LUMO off-set. This suggests the importance of local charge transfer character in these copolymers in the initial exciton splitting dynamics, which could ultimately be reflected in the device performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Selective butene formation in direct ethanol-to-C3+-olefin valorization over Zn-Y/Beta and single-atom alloy composite catalysts using in situ generated hydrogen

The selective production of C3+ olefins from renewable feedstocks, especially via C1 and C2 platform chemicals, is a critical challenge for obtaining economically viable low-carbon middle distillate transportation fuels (i.e., jet and diesel). Here, we report a multifunctional catalyst system composed of Zn-Y/Beta and “single-atom” alloy (SAA) Pt-Cu/Al2O3 which selectively catalyzes ethanol-to-olefins (C3+, ETO) valorization in the absence of cofed hydrogen, forming butenes as the primary olefin products. Beta zeolites containing predominately isolated Zn and Y metal sites catalyze ethanol upgrading steps (588 K, 3.1 kPa ethanol, ambient pressure) regardless of cofed hydrogen partial pressure (0-98.3 kPa H2), forming butadiene as the primary product (60% selectivity at 87% conversion). The Zn-Y/Beta catalyst possesses site-isolated Zn and Y Lewis acid sites (at ~7 wt% Y) and Brønsted acidic Y sites, the latter of which has been previously uncharacterized. A secondary bed of SAA Pt-Cu/Al2O3 selectively hydrogenates butadiene to butene isomers at a consistent reaction temperature using hydrogen generated in situ from ethanol-to-butadiene (ETB) conversion. This unique hydrogenation reactivity at near-stoichiometric hydrogen and butadiene partial pressures is not observed over monometallic Pt or Cu catalysts, highlighting these operating conditions as a critical SAA catalyst application area for conjugated diene selective hydrogenation at high reaction temperatures (>573 K) and low H2/diene ratios (e.g., 1:1). Single-bed steady state selective hydrogenation rates, associated apparent hydrogen and butadiene reaction orders, and DFT calculations of the Horiuti-Polanyi reaction mechanisms indicate that the unique butadiene selective hydrogenation reactivity over SAA Pt-Cu/Al2O3 reflects lower hydrogen scission barriers relative to monometallic Cu surfaces and limited butene binding energies relative to monometallic Pt surfaces. DFT calculations further indicate the preferential desorption of butene isomers over SAA Pt-Cu(111) and Cu(111) surfaces while Pt(111) surface favors subsequent butene hydrogenation reactions to form butane over butene desorption events. Under operating conditions without of hydrogen cofeeding, this combination of Zn-Y/Beta and SAA Pt-Cu catalysts can selectively form butenes (65% butenes, 78% C3+ selectivity at 94% conversion) and avoid butane formation using only in situ generated hydrogen, avoiding costly hydrogen cofeeding requirements that hinder many renewable energy processes.

Cordon, Michael↗
DOE OSTI2021

Connectivity-informed drainage network generation using deep convolution generative adversarial networks

Abstract Stochastic network modeling is often limited by high computational costs to generate a large number of networks enough for meaningful statistical evaluation. In this study, Deep Convolutional Generative Adversarial Networks (DCGANs) were applied to quickly reproduce drainage networks from the already generated network samples without repetitive long modeling of the stochastic network model, Gibb’s model. In particular, we developed a novel connectivity-informed method that converts the drainage network images to the directional information of flow on each node of the drainage network, and then transforms it into multiple binary layers where the connectivity constraints between nodes in the drainage network are stored. DCGANs trained with three different types of training samples were compared; (1) original drainage network images, (2) their corresponding directional information only, and (3) the connectivity-informed directional information. A comparison of generated images demonstrated that the novel connectivity-informed method outperformed the other two methods by training DCGANs more effectively and better reproducing accurate drainage networks due to its compact representation of the network complexity and connectivity. This work highlights that DCGANs can be applicable for high contrast images common in earth and material sciences where the network, fractures, and other high contrast features are important.

42 ENGINEERING↗
DOE OSTI2013

Dynamics of coupled simplest chaotic two-component electronic circuits and its potential application to random bit generation

We numerically investigate the possibility of using a coupling to increase the complexity in simplest chaotic two-component electronic circuits operating at high frequency. We subsequently show that complex behaviors generated in such coupled systems, together with the post-processing are suitable for generating bit-streams which pass all the NIST tests for randomness. The electronic circuit is built up by unidirectionally coupling three two-component (one active and one passive) oscillators in a ring configuration through resistances. It turns out that, with such a coupling, high chaotic signals can be obtained. By extracting points at fixed interval of 10 ns (corresponding to a bit rate of 100 Mb/s) on such chaotic signals, each point being simultaneously converted in 16-bits (or 8-bits), we find that the binary sequence constructed by including the 10(or 2) least significant bits pass statistical tests of randomness, meaning that bit-streams with random properties can be achieved with an overall bit rate up to 10×100 Mb/s =1Gbit/s (or 2×100 Mb/s =200 Megabit/s). Moreover, by varying the bias voltages, we also investigate the parameter range for which more complex signals can be obtained. Besides being simple to implement, the two-component electronic circuit setup is very cheap as compared to optical and electro-optical systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗