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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Nonstationary and Non-Gaussian Moving Average Model for Solar Irradiance

Historically, power has flowed from large power plants to customers. Increasing penetration of distributed energy resources such as solar power from rooftop photovoltaic has made the distribution network a two-way-street with power being generated at the customer level. The incorporation of renewables introduces additional uncertainty and variability into the power grid. Distribution network operation studies are being adapted to include renewables; however, such studies require high quality solar irradiance data that adequately reflect realistic meteorological variability. Data from satellite-based products are spatially complete, but temporally coarse, whereas solar irradiances exhibit high frequency variation at very fine timescales. We propose a new stochastic method for temporally downscaling global horizontal irradiance (GHI) to 1 min resolution, but we do not consider the spatial aspect due to limited availability of the in situ irradiance measurements. Solar irradiance's first and second-order structures vary diurnally and seasonally, and our model adapts to such nonstationarity. Empirical irradiance data exhibits highly non-Gaussian behavior; we develop a nonstationary and non-Gaussian moving average model that is shown to capture realistic solar variability at multiple timescales. We also propose a new estimation scheme based on Cholesky factors of empirical autocovariance matrices, bypassing difficult and inaccessible likelihood-based approaches. The model is demonstrated for a case study of three locations that are located in diverse climates through the United States. The model is compared against competitors from the literature and is shown to provide better uncertainty and variability quantification on testing data.

Cholesky factor↗
DOE OSTI2020

Modular Electrochemical Synthesis Using a Redox Reservoir Paired with Independent Half-Reactions

Electrochemical synthesis of high-value chemicals using renewable electricity could lead to sustainability advantages over conventional chemical manufacturing. The tight coupling between paired anodic and cathodic reactions in conventional electrochemical processes, however, constrains the products and their efficiencies. Here, we demonstrate a strategy to achieve modular electrochemical synthesis (ModES) of different chemicals by decoupling and pairing the oxidative and reductive half-reactions with a heterogeneous redox reservoir (RR). Specifically, sodium nickel hexacyanoferrate (NaNiHCF) can serve as a robust and reversible RR that enables the modular production of several strong oxidants, hydrogen peroxide (H 2 O2) and sodium persulfate (Na 2 S 2 O 8 ) or active chlorine, in separate RR-coupled electrochemical processes. The system’s excellent performance and operational stability is demonstrated by continuous operation over 100 cycles (~36 h) to produce H 2 O 2 and Na 2 S 2 O 8 with a high voltage efficiency. The concept presented here highlights the prospects for using RRs to enable efficient, modular, and on-demand electrochemical synthesis of valuable chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Demonstration of Power System Black Start with Hydropower Generator and Battery Energy Storage: Preprint

Battery energy storage systems (BESS) are an important asset for power systems with high integration levels of renewable energy, and they can be controlled to provide various services to the grid. This paper presents the hardware demonstration and characterization of using a utility-scale BESS with grid-following (GFL) and grid-forming (GFM) controls and a run-of-river (ROR) hydropower plant to perform a bottom-up power system black start that enhances power systems' resiliency. ROR hydropower plants are generally not used for power system restoration due to their frequency instability during islanded operation; however, BESS with droop control can provide critical damping to convert a ROR hydropower generator into a blackstart- capable unit. To demonstrate this, we carry out hardware experiments at the megawatt-scale integrating a synchronous generator driven by a dynamometer, an actual GFL/GFM BESS, a medium-voltage impedance network, and a load bank. The demonstration shows the different roles of BESS with GFL and GFM control in power system restoration. GFL BESS can suffer from high-frequency oscillations, even instability, depending on the droop control gain and loading condition. The results provide further insights for system operators on how GFL- or GFMcontrolled BESS can enhance grid stability and how hydro-BESS hybrids can operate as a black-start-capable unit. The presented experimental results are also a valuable resource to understand the different stability characteristics of real-world BESS with different control modes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Small Hydro Power Plants with Integrated BESS for Enhance Resiliency

Battery energy storage systems (BESS) are an important asset for power systems with high integration levels of renewable energy, and they can be controlled to provide various services to the grid. This paper presents the hardware demonstration and characterization of using a utility-scale BESS with grid-following (GFL) and grid-forming (GFM) controls and a run-of-river (ROR) hydropower plant to perform a bottom-up power system black start that enhances power systems' resiliency. ROR hydropower plants are generally not used for power system restoration due to their frequency instability during islanded operation; however, BESS with droop control can provide critical damping to convert a ROR hydropower generator into a black start- capable unit. To demonstrate this, we carry out hardware experiments at the megawatt-scale integrating a synchronous generator driven by a dynamometer, an actual GFL/GFM BESS, a medium-voltage impedance network, and a load bank. The demonstration shows the different roles of BESS with GFL and GFM control in power system restoration. GFL BESS can suffer from high-frequency oscillations, even instability, depending on the droop control gain and loading condition. The results provide further insights for system operators on how GFL- or GFM controlled BESS can enhance grid stability and how hydro-BESS hybrids can operate as a black-start-capable unit. The presented experimental results are also a valuable resource to understand the different stability characteristics of real-world BESS with different control modes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Model-Free State Estimation Using Low-Rank Canonical Polyadic Decomposition

As electric grids experience high penetration levels of renewable generation, fundamental changes are required to address real-time situational awareness. Here, we utilize unique traits of tensors to devise a model-free situational awareness and energy forecasting framework for distribution networks. This work formulates the state of the network at multiple time instants as a three-way tensor; hence, recovering full state information of the network is tantamount to estimating all the values of the tensor. Given measurements received from µphasor measurement units and/or smart meters, the recovery of unobserved quantities is carried out using the low-rank canonical polyadic decomposition of the state tensor—that is, the state estimation task is posed as a tensor imputation problem utilizing observed patterns in measured (sampled) quantities. Two structured sampling schemes are considered, namely, asynchronous slab and fiber sampling. For both schemes, we present sufficient conditions on the number of sampled slabs and fibers that guarantee identifiability of the factors of the state tensor. Numerical results demonstrate the ability of the proposed framework to achieve high estimation accuracy in multiple sampling scenarios.

42 ENGINEERING↗
DOE OSTI2024

Industrial Energy Storage Review

As the United States moves to net-zero carbon emission by 2050, a transition to renewable energy generation is required. However, the variable nature of renewable energy generation at high penetrations can cause imbalances in generation and transmission of electricity. These imbalances can be circumvented by the deployment of energy storage. Global industrial energy storage is projected to grow 2.6 times in the coming decades, from just over 60 GWh to 167 GWh in 2030. The challenge is to balance energy storage capabilities with the power and energy needs for particular industrial applications. Energy storage technologies can be classified by the form of the stored energy. The most common forms include thermal, chemical, electrochemical, and mechanical storage technologies. The most appropriate storage technology will depend on the unique energy needs of the industrial application. The purpose of this report is to provide a review of energy storage technologies relevant to the U.S. industrial sector, highlighting the applications in industry that will benefit from increased integration of energy storage, as well as the respective challenges and opportunities unique to integrating different storage technologies.

25 ENERGY STORAGE↗
DOE OSTI2023

Modeling, testing, and mitigation of electromagnetic pulse on PV systems

Electromagnetic Pulse (EMP) poses a significant threat to the normal operation of power systems, especially with the increasing penetration of renewable energy. Without adequate protection, EMP can severely damage equipment or result in circuit breakdowns or short circuits. Solar photovoltaic (PV) facilities are particularly susceptible to EMP since PV systems are outdoors and exposed to EMP radiation. To assess and mitigate this threat, this paper summarizes various models and tests used to study the effects of EMP on PV systems, assesses the nature of the threat, and identifies measures to mitigate it. The paper provides a comprehensive review by categorizing analytical methods based on their pros and cons, introducing and describing EMP-related events, and providing a taxonomy of analytical methods for studying EMP. This paper compares the processes of modeling, testing, and mitigating EMP at both the component and system levels of PV systems. Furthermore, it also presents a case study that reveals the vulnerability of solar inverters to EMP using the pulse current injection method. Finally, the paper discusses some of the remaining challenges that should be considered in future solar PV system design and deployment.

14 SOLAR ENERGY↗
DOE OSTI2020

A novel matching formulation for startup costs in unit commitment

Here we present a novel formulation for startup cost computation in the unit commitment problem (UC). Both our proposed formulation and existing formulations in the literature are placed in a formal, theoretical dominance hierarchy based on their respective linear programming relaxations. Our proposed formulation is tested empirically against existing formulations on large-scale UC instances drawn from real-world data. While requiring more variables than the current state-of-the-art formulation, our proposed formulation requires fewer constraints, and is empirically demonstrated to be as tight as a perfect formulation for startup costs. This tightening can reduce the computational burden in comparison to existing formulations, especially for UC instances with large reserve margins and high penetration levels of renewables.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Facets of hydro power and future trends in a Nordic Context

Hydropower technologies bolster high penetration of variable renewable energies (VREs) in the net zero emissions scenarios. Nevertheless, there are various challenges to meeting the ambitious goal, such as stability, reliability, resiliency, security, lack of reactive power, voltage support and inertia, large-scale storage deployment and coordination, interconnectedness, demand-side response, higher thermal cycles with increased start/stops, and inadequate Levelized Cost of Energy (LCOE) for system-wise VRE integration and profitability. This survey conducts a bottom-up analysis to unveil the opportunities to utilize hydropower facilities and disentangle the nested problem for intertwining design features, control algorithms, operation, optimization approaches, incentives, services, and market mechanisms using a three-pillar framework perspective: grid owners, power producers, and machine designers. The survey identified emerging trends in real-time and capacity markets, flexible power systems, and enhanced grid capabilities, including advanced voltage support and updated grid codes. These developments present significant opportunities for hydropower, such as achieving super-flexibility through hybridization, expanded reactive power capabilities, and advanced operational modes like a synchronous condenser and power adequator functionalities. These opportunities require novel design philosophies — including new winding, stator, and rotor configurations, optimized ventilation, and active cooling systems — to enhance performance under stressed grid and climate conditions. Finally, integrating climate and energy models for multi-basin optimization with finer spatial and temporal granularity enhances the planning accuracy for water management of hydropower while addressing environmental challenges. The review delivers helpful prospective suggestions and tools that would serve researchers, power engineers, and stakeholders in making decisions about hydropower technologies and services in 2050 and beyond.

13 HYDRO ENERGY↗
DOE OSTI2026

Quantitative measurement of pebble fuel anisotropy using generalized ellipsometry

The renewed development of high-temperature gas-cooled reactors has created a need to modernize pebble fuel quality control methods. One important specification in these methods is the coefficient of thermal expansion (CTE) anisotropy, which reflects graphite grain alignment and affects fuel performance. This study investigates the feasibility of using two-modulator generalized ellipsometry microscopy (2-MGEM) as a potential surrogate metric for CTE anisotropy. Graphite matrix compacts with controlled levels of anisotropy were fabricated by varying pre-pressures during forming and were subsequently characterized using both optical dilatometry and 2-MGEM. Measured responses were compared to an isotropic reference pebble produced using an industrial manufacturing process to provide a practical baseline. The resulting measurements revealed a strong quantitative correlation between the CTE anisotropy ratio and the corresponding diattenuation ratio. However, propagated measurement uncertainties in the optical method were found to limit definitive pass/fail discrimination, highlighting the need for improved precision before qualification as a quality control tool. Still, the results establish a quantitative relationship between optical and CTE anisotropy and support further development of 2-MGEM as a potential surrogate method for evaluating graphite matrix anisotropy in pebble fuel manufacturing.

Raftery, Alicia [ORNL] (ORCID:0000000259076427)↗
DOE OSTI2022

Better together: Protein partnerships for lineage-specific oil accumulation

Plant-derived oils are a major agricultural product that exist in both ubiquitous forms such as common vegetable oils and in specialized forms such as castor oil and coconut oil. These specialized oils are the result of lineage-specific metabolic pathways that create oils rich in unusual fatty acids. Considerable progress has been made toward understanding the enzymes that mediate fatty acid biosynthesis, triacylglycerol assembly, and oil storage. However, efforts to translate this knowledge into renewable bioproducts via engineered oil-producing plants and algae have had limited success. Here, we review recent evidence that protein–protein interactions in each of the three major phases of oil formation appear to have profound effects on specialized oil accumulation. We suggest that furthering our knowledge of the noncatalytic attributes of enzymes and other proteins involved in oil formation will be a critical step toward creating renewable bioproducts derived from high performing, engineered oilseeds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Epitaxial growth of oriented CoO films by radio-frequency sputtering deposition

Rock-salt CoO is a p-type semiconductor and its Neel temperature is close to room temperature. CoO-based compounds are known as promising systems for renewable energy harvest with high efficiency. CoO with catalytic and exchange bias properties can be widely used for industrial applications. In this paper, we report high-quality stable CoO(111) and (100) films epitaxially grown on c-cut (0001) and r-cut ($10\bar1$2) alpha-Al 2 O 3 substrates, respectively, using radio-frequency sputtering deposition. X-ray diffraction (XRD) measurements revealed that the CoO films had a rock-salt structure (Fm3m) with lattice constants of 4.2477 Å and 4.2617 Å for film grown on (0001) and ($10\bar1$2) α-Al 2 O 3 substrates, respectively. CoO films with the best crystal quality were grown at a substrate temperature of similar to ~700°C. XRD measurements of CoO(111) films indicated a lack of structural residual strain, whereas CoO(100) films had substantial amounts of structural strain. X-ray reflectivity (XRR) and transmission electron microscopy measurements showed neither oxygen vacancy nor defects in both CoO(111) and (100) films. Further, XRR revealed that the mean electron density of the CoO films was nearly identical to a pure CoO and that the films were considerably stable under the atmosphere.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigating Cu-Site Doped Cu–Sb–S Nanoparticles Using Photoelectron and Electron Paramagnetic Resonance Spectroscopy

Tetrahedrite (Cu 12 Sb 4 S 13 ) and famatinite (Cu 3 SbS 4 ) are good candidates for green energy applications because they possess promising thermoelectric and photovoltaic properties as well as contain earth-abundant and nontoxic constituents. Herein, X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS), and electron paramagnetic resonance spectroscopy (EPR) methods examined inherent electronic properties and interatomic magnetic interactions of Cu-site doped tetrahedrite and famatinite nanomaterials. An energy-efficient modified polyol method was utilized for the synthesis of tetrahedrite and famatinite nanoparticles doped on the Cu-site with Zn, Fe, Ni, Mn, and Co. This is the first parallel study of tetrahedrite and famatinite nanomaterials with XPS, UPS, and EPR methods alongside a systematic analysis of dopant-dependent effects on the electronic structure and magnetic interactions for each material. XPS showed that the Cu and Sb species in tetrahedrite and famatinite possess different oxidation states, while UPS characterization reveals larger dopant-dependent shifts in the work function for tetrahedrite nanoparticles (4.21 to 4.79 eV) than for famatinite nanoparticles (4.57 to 4.77 eV). Finally, all famatinite nanoparticles display an EPR signal, indicating trace amounts of paramagnetic Cu(II) present below the detection limit of XPS. For tetrahedrite, EPR signatures were observed only for the Zn-doped and Mn-doped nanoparticles, suggesting signal broadening from Cu–Cu spin exchange or spin–lattice relaxation. This study demonstrates the complementary nature of XPS and EPR techniques for studying the oxidation states of metals in solid-state nanomaterials. Comparing the electronic and magnetic properties of tetrahedrite and famatinite while studying the impact of dopant incorporation will guide future endeavors in designing sustainable, high-performance materials for renewable energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Capturing carbon dioxide from air with charged-sorbents

Emissions reduction and greenhouse gas removal from the atmosphere are both necessary to achieve net-zero emissions and limit climate change. There is thus a need for improved sorbents for the capture of carbon dioxide from the atmosphere, a process known as direct air capture. In particular, low-cost materials that can be regenerated at low temperatures would overcome the limitations of current technologies. In this work, we introduce a new class of designer sorbent materials known as ‘charged-sorbents’. These materials are prepared through a battery-like charging process that accumulates ions in the pores of low-cost activated carbons, with the inserted ions then serving as sites for carbon dioxide adsorption. We use our charging process to accumulate reactive hydroxide ions in the pores of a carbon electrode, and find that the resulting sorbent material can rapidly capture carbon dioxide from ambient air by means of (bi)carbonate formation. Unlike traditional bulk carbonates, charged-sorbent regeneration can be achieved at low temperatures (90–100 °C) and the sorbent’s conductive nature permits direct Joule heating regeneration using renewable electricity. Given their highly tailorable pore environments and low cost, we anticipate that charged-sorbents will find numerous potential applications in chemical separations, catalysis and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Deconstruction of biomass enabled by local demixing of cosolvents at cellulose and lignin surfaces

A particularly promising approach to deconstructing and fractionating lignocellulosic biomass to produce green renewable fuels and high-value chemicals pretreats the biomass with organic solvents in aqueous solution. Here, neutron scattering and molecular-dynamics simulations reveal the temperature-dependent morphological changes in poplar wood biomass during tetrahydrofuran (THF):water pretreatment and provide a mechanism by which the solvent components drive efficient biomass breakdown. Whereas lignin dissociates over a wide temperature range (>25 °C) cellulose disruption occurs only above 150 °C. Neutron scattering with contrast variation provides direct evidence for the formation of THF-rich nanoclusters (R g ∼ 0.5 nm) on the nonpolar cellulose surfaces and on hydrophobic lignin, and equivalent water-rich nanoclusters on polar cellulose surfaces. The disassembly of the amphiphilic biomass is thus enabled through the local demixing of highly functional cosolvents, THF and water, which preferentially solvate specific biomass surfaces so as to match the local solute polarity. A multiscale description of the efficiency of THF:water pretreatment is provided: matching polarity at the atomic scale prevents lignin aggregation and disrupts cellulose, leading to improvements in deconstruction at the macroscopic scale.

09 BIOMASS FUELS↗
DOE OSTI2020

Modular cell-free expression plasmids to accelerate biological design in cells

Industrial biotechnology aims to produce high-value products from renewable resources. This can be challenging because model microorganisms—organisms that are easy to use like Escherichia coli—often lack the machinery required to utilize desired feedstocks like lignocellulosic biomass or syngas. Non-model organisms, such as Clostridium, are industrially proven and have desirable metabolic features but have several hurdles to mainstream use. Namely, these species grow more slowly than conventional laboratory microbes, and genetic tools for engineering them are far less prevalent. To address these hurdles for accelerating cellular design, cell-free synthetic biology has matured as an approach for characterizing non-model organisms and rapidly testing metabolic pathways in vitro. Unfortunately, cell-free systems can require specialized DNA architectures with minimal regulation that are not compatible with cellular expression. In this work, we develop a modular vector system that allows for T7 expression of desired enzymes for cell-free expression and direct Golden Gate assembly into Clostridium expression vectors. Utilizing the Joint Genome Institute’s DNA Synthesis Community Science Program, we designed and synthesized these plasmids and genes required for our projects allowing us to shuttle DNA easily between our in vitro and in vivo experiments. We next validated that these vectors were sufficient for cell-free expression of functional enzymes, performing on par with the previous state-of-the-art. Lastly, we demonstrated automated six-part DNA assemblies for Clostridium autoethanogenum expression with efficiencies ranging from 68% to 90%. We anticipate this system of plasmids will enable a framework for facile testing of biosynthetic pathways in vitro and in vivo by shortening development cycles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multiphysics Modeling of Hydrokinetic Turbine Energy Conversion System

Hydrokinetic turbines (HKTs) hold great promise as a renewable energy source, but high maintenance costs and limited energy output hinder their widespread adoption. The lack of comprehensive research on HKT drivetrain designs creates a knowledge gap in enhancing generation efficiency and cost reduction. A model of the HKT system with a focus on electric drivetrains and power converters is required to address this knowledge gap. This paper first introduces a MATLAB-averaged model integrating electrical-mechanical-thermal domains and aging behaviors within multi-time frames. Then a PLECS model, which incorporates maximum power point tracking and dq reference framed control for AC-DC-AC power converters, is enriched by a dynamic thermal model to predict fast transients accurately. These models optimize the design at the component level, resulting in improved integrated system performance. Furthermore, the validation of the models is carried out through hardware experiments for the averaged model and hardware-in-the-loop testing for the dynamic model.

ADVANCED PROPULSION SYSTEMS,HYDRO ENERGY↗
DOE OSTI2025

Machine Learning-Assisted Distribution System Network Reconfiguration Problem

High penetration from volatile renewable energy resources in the grid and the varying nature of loads raise the need for frequent line switching to ensure the efficient operation of electrical distribution networks. Operators must ensure maximum load delivery, reduced losses, and the operation between voltage limits. However, computations to decide the optimal feeder configuration are often computationally expensive and intractable, making it unfavorable for real-time operations. This is mainly due to the existence of binary variables in the network reconfiguration optimization problem. To tackle this issue, we have devised an approach that leverages machine learning techniques to reshape distribution networks featuring multiple substations. This involves predicting the substation responsible for serving each part of the network. Hence, it leaves simple and more tractable Optimal Power Flow problems to be solved. This method can produce accurate results in a significantly faster time, as demonstrated using the IEEE 37-bus distribution feeder. Compared to the traditional optimization-based approaches, a feasible solution is achieved approximately ten times faster for all the tested scenarios.

deep neural networks↗