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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Policy and Cost Allocation Considerations for Large Electric Load Interconnections: Emerging Policy Trends in Rate Structures, Interconnection, and Cost Impacts on Other System Users

Load growth in the United States is rapidly increasing: load from data centers alone has tripled over the past decade, and this growth is forecasted to continue accelerating. These and other large electric loads (LELs) promise economic benefits at the state and local level, but their deployment has also led to increasing concerns about grid impacts and potential cost shifts onto other ratepayers. Legislators, regulators, and other stakeholders are increasingly proposing and enacting policies in effort to balance these and other considerations. This white paper reviews state-level legislation, selected utility rate cases, and relevant federal orders in an effort to describe and categorize relevant trends in policies related to LEL cost allocation, interconnection, and deployment. Policy categories identified through this review include tax incentives, rate actions, and requirements related to interconnection, permitting, and reporting. By offering a taxonomy of policies, this white paper aims to offer a resource to policymakers and other stakeholders navigating this transformative moment for the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Adaptive stratified importance sampling: hybridization of extrapolation and importance sampling Monte Carlo methods for estimation of wind turbine extreme loads

Wind turbine extreme load estimation is especially difficult because turbulent inflow drives nonlinear turbine physics and control strategies; thus there can be huge differences in turbine response to essentially equivalent environmental conditions. The two main current approaches, extrapolation and Monte Carlo sampling, are both unsatisfying: extrapolation-based methods are dangerous because by definition they make predictions outside the range of available data, but Monte Carlo methods converge too slowly to routinely reach the desired 50-year return period estimates. Thus a search for a better method is warranted. We introduce an adaptive stratified importance sampling approach that allows for treating the choice of environmental conditions at which to run simulations as a stochastic optimization problem that minimizes the variance of unbiased estimates of extreme loads. Furthermore, the framework, built on the traditional bin-based approach used in extrapolation methods, provides a close connection between sampling and extrapolation, and thus allows the solution of the stochastic optimization (i.e., the optimal distribution of simulations in different wind speed bins) to guide and recalibrate the extrapolation. Results show that indeed this is a promising approach, as the variance of both the Monte Carlo and extrapolation estimates are reduced quickly by the adaptive procedure. We conclude, however, that due to the extreme response variability in turbine loads to the same environmental conditions, our method and any similar method quickly reaches its fundamental limits, and that therefore our efforts going forward are best spent elucidating the underlying causes of the response variability.

17 WIND ENERGY↗
DOE OSTI2020

Assessing and Reducing Plug and Process Loads in Office Buildings

Plug and process loads (PPLs) account for 33% of U.S. commercial building electricity consumption (McKenney et al. 2010). (See Figure 1.) Minimizing these loads is a significant challenge in the design and operation of an energy-efficient building. Lobato et al. (2011) and Lobato et al. (2012) define PPLs as energy loads that are not related to general lighting, heating, ventilation, cooling, and water heating, and that typically do not provide comfort to the occupants. The percentage of total building energy use from PPLs is increasing. According to the U.S. Department of Energy (DOE), by 2030, commercial building energy consumption is expected to increase by 24%; PPL energy consumption is anticipated to increase by 49% in the same time frame (DOE 2010). These trends illustrate the importance of PPL energy reduction to achieve an overall goal of reducing whole-building energy consumption.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Assessing and Reducing Plug and Process Loads in Retail Buildings

Plug and process loads (PPLs) account for 33% of U.S. commercial building electricity consumption (McKenney et al. 2010). (See Figure 1.) Minimizing these loads is a significant challenge in the design and operation of an energy-efficient building. Lobato et al. (2011) and Lobato et al. (2012) define PPLs as energy loads that are not related to general lighting, heating, ventilation, cooling, and water heating, and that typically do not provide comfort to the occupants. The percentage of total building energy use from PPLs is increasing. According to the U.S. Department of Energy (DOE), by 2030, commercial building energy consumption is expected to increase by 24%; PPL energy consumption is anticipated to increase by 49% in the same time frame (DOE 2010). These trends illustrate the importance of PPL energy reduction to achieve an overall goal of reducing whole-building energy consumption.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

A Two-Step Time-Series Data Clustering Method for Building-Level Load Profile

Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. The load profiles in the same group will have similar characteristics at the same time step, so grid operators can send the grid service signal to the customer group with a higher chance to respond at that time step. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation and the results have proved the effectiveness of this method.

AMI↗
DOE OSTI2025

Operando Neutron Imaging of Lithium Flux and Gradient Cathode Design for Enhanced Kinetics in High‐Loading All‐Solid‐State Li─S Batteries

All-solid-state Li–sulfur batteries (ASSLSBs) are considered promising candidates for next-generation energy storage owing to their inherent safety, high energy density, and abundant sulfur resources. However, slow redox kinetics greatly limit sulfur utilization during solid-solid sulfur reactions, leading to significant challenges to achieve efficient performance in high-mass-loading ASSLSBs. Here, operando neutron image is employed to directly visualize, for the first time, that sluggish Li + transport kinetics and the uneven distribution of Li + during cathodic reactions are critical factors limiting sulfur conversion. To address this issue, gradient cathode architectures comprising three and five layers are designed, in which catholyte concentrations are strategically varied to optimize Li-ion flux and enhance ionic conductivity of the whole composite cathode electrode. Operando neutron imaging distinctly visualizes and confirms that three-layer gradient approach significantly enhances Li-ion mobility, resulting in more uniform redox reactions and greatly improved sulfur utilization compared to traditional non-gradient structures. Consequently, the three-layer gradient cathode achieves superior rate performance and reduced electrode polarization at high sulfur mass loadings of 4.5 and 6.0 mg cm −2 . Furthermore, the applicability and scalability of this design are demonstrated in a five-layer gradient cathode architecture, achieving an impressive discharge specific capacity increase from 656 mAh g −1 (three-layer gradient) to 1232 mAh g −1 at 1/20 C for ultra-high sulfur loading of 7.5 mg cm −2 . In conclusion, this innovative gradient cathode design offers substantial advancements in understanding and overcoming Li-ion transport limitations, paving the way toward practical, high-energy-density ASSLSBs.

25 ENERGY STORAGE↗
DOE OSTI2024

Ultrathin Microporous Transport Layers: Implications for Low Catalyst Loadings, Thin Membranes, and High Current Density Operation for Proton Exchange Membrane Electrolysis

Porous transport layers (PTL) and their surface properties have the potential to improve the performance of proton exchange membrane water electrolyzers (PEMWE), which is imperative to reduce feedstock costs and lead to their widespread implementation. This work introduces a novel generation of titanium microporous layers (MPLs) with ultra-low thicknesses of approx. 20 um which reduces raw material costs. They also feature advanced interfacial properties tailored to maximize catalyst utilization at low Ir-loadings. The bulk morphology and surface properties of the hierarchically structured PTLs are assessed by X-ray tomographic microscopy. The low surface roughness of the MPL allows the use of thinner membranes since it minimizes possible deformations in the membrane. Cells containing the MPLs outperformed those containing state-of-the-art commercially available PTL materials by up to 100 mV at 7 A cm-2 in combination with low-loaded catalyst-coated membranes of 0.4 mgIr cm-2. Hydrogen crossover is also reduced, especially at low current densities, leading to a larger turndown ratio which can enable more cost-effective operating strategies. Finally, these rationally designed MPLs also lead to high catalyst utilization by overcoming the naturally occurring high in-plane resistance of low-loaded catalyst layers.

hydrogen crossover↗
DOE OSTI2022

Extended Barton–Bandis model for rock joints under cyclic loading: Formulation and implicit algorithm

In this paper, the Barton–Bandis model for rock joints is extended to cyclic loading conditions, without any new material parameter. Also developed herein is an implicit solution algorithm for the extended Barton–Bandis model, which can also be used for the original Barton–Bandis model for which an implicit algorithm has been unavailable. To this end, we first cast the Barton–Bandis model into an incremental elasto-plastic framework, deriving an expression for the elastic shear stiffness being consistent with the original model formulation. We then extend the model formulation to cyclic loading conditions, incorporating the dependence of shear stress and dilation on the joint position and the shearing direction. The extension is achieved by introducing a few state-dependent variables which can be calculated with the existing material parameters. For robust and accurate utilization of the model, we also develop an implicit algorithm based on return mapping, which is unconditionally stable and guarantees the satisfaction of the strength criterion. We verify that the proposed model formulation and algorithm produce virtually the same results as the original Barton–Bandis model under monotonic shearing conditions. Here, we then validate the extended Barton–Bandis model against experimental data on natural rock joints under cycling loading conditions. The present work thus enables the Barton–Bandis model, which has been exceptionally popular in research and practice, to be applicable to a wider range of problems in rock mechanics and rock engineering.

58 GEOSCIENCES↗
DOE OSTI2015

A Framework to Analyze the Performance of Load Balancing Schemes for Ensembles of Stochastic Simulations

Ensembles of simulations are employed to estimate the statistics of possible future states of a system, and are widely used in important applications such as climate change and biological modeling. Ensembles of runs can naturally be executed in parallel. However, when the CPU times of individual simulations vary considerably, a simple strategy of assigning an equal number of tasks per processor can lead to serious work imbalances and low parallel efficiency. This paper presents a new probabilistic framework to analyze the performance of dynamic load balancing algorithms for ensembles of simulations where many tasks are mapped onto each processor, and where the individual compute times vary considerably among tasks. Four load balancing strategies are discussed: most-dividing, all-redistribution, random-polling, and neighbor-redistribution. Simulation results with a stochastic budding yeast cell cycle model are consistent with the theoretical analysis. It is especially significant that there is a provable global decrease in load imbalance for the local rebalancing algorithms due to scalability concerns for the global rebalancing algorithms. The overall simulation time is reduced by up to 25 %, and the total processor idle time by 85 %.

ALGORITHMS↗
DOE OSTI2015

Small scale mechanical characterization of thin foil materials via pin load microtesting

In situ scanning electron microscope (SEM) experiments, where small-scale mechanical tests are conducted on micro- and nanosized specimens, allow direct visualization of elastic and plastic responses over the entirety of the volume being deformed. This enables precise spatial and temporal correlation of slip events contributing to the plastic flow evidenced in a stress–strain curve. A new pin-loading methodology has been employed, in situ within the SEM, to conduct microtensile tests on thin polycrystalline metal foils. This approach can be tailored to a specific foil whose particular grain size may range from microns to tens of microns. Manufacture of the specialized pin grip was accomplished via silicon photolithography-based processing followed by subsequent focused ion beam finishing. Microtensile specimen preparation was achieved by combining a stencil mask methodology employing broad ion beam sputtering along with focused ion beam milling in the study of several metallic foil materials. Finite-element analyses were performed to characterize the stress and strain distributions in the pin grip and micro-specimen under load. Furthermore, under appropriately conceived test conditions, uniaxial stress–strain responses measured within these foils by pin-load microtensile testing exhibit properties consistent with larger scale tests.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Effects of copper loading on NH3-SCR and NO oxidation over Cu impregnated CHA zeolite

Cu/CHA catalysts with various Cu loadings (0.5 wt%–6.0 wt%) were synthesized via incipient wetness impregnation. The catalysts were then applied to the selective catalytic reduction (SCR) of NO with NH 3 and NO oxidation reaction. XRD and N 2 adsorption-desorption data showed that CHA structure was maintained with the incorporation of Cu, while specific surface areas decreased with increasing Cu loading. At intermediate Cu loading, 4 wt%, the highest NH 3 -SCR activity was observed with ~98% N2 selectivity from 150°C to 300°C. Small amounts of water, 2%, slightly increased NO conversion in addition to the remarkable N 2 O and NO 2 reduction at high temperature. Water effects are attributed to the improved Cu ion reducibility and mobility. NO oxidation results provided no relation between NO 2 formation and SCR activity. Physicochemical properties, NO conversion, N 2 selectivity, and activation energy data showed that impregnated samples’ molecular structure and catalytic activity are comparable to the conventional ion-exchanged (IE) samples’ ones.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A deterministic method for PWR loading pattern optimization

A new deterministic approach to core loading optimization is presented. Selection of fuel enrichment and burnable poison (BP) arrangement in a pressurized water reactor (PWR) core are optimally determined subject to power peaking factor (PF) constraints. The deterministic approach is based on the method of Lagrange multipliers and the direct adjoining approach for the inequality power PF constraint. The optimality conditions are derived using calculus of variations resulting in the presence of jump conditions and a linear control Hamiltonian. The optimal control problems are addressed by simultaneously minimizing the Hamiltonian using the gradient method and performing Newton's method in different regions of the core to produce viable solutions for the controls. Without active control of the power profile in PWRs during depletion, our methodology is able to satisfy the power PF constraint at all times by proper loading selection at the beginning of cycle (BOC). This is achieved by promoting the proper burnup path forward in time during the calculation of the forward optimality conditions. Here this information is utilized in the adjoint burnup calculation, which acts to propagate the optimal control path back to the BOC during the calculation of the adjoint optimality conditions. The methodology has been developed into a new code DMCO (Deterministic Multi-Control Optimization) which can produce two-dimensional two-group depletion results in approximately seven minutes per optimization iteration on a personal computer. No application of heuristics is required and the code is capable of finding solutions from initial control distributions. A preliminary case study is presented for the Westinghouse AP600 first cycle fuel loading design which achieved an extended fuel cycle while satisfying power PF constraints.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Effect of sodium loading on Pt/ZrO 2 during ethanol steam reforming

Ethanol steam reforming (ESR) was investigated on unpromoted and several sodium promoted Pt/ZrO 2 catalysts. From DRIFTS experiments, the following steps during ESR were inferred: dissociation of ethanol to produce ethoxy species; oxidative dehydrogenation of ethoxy species to acetate; and acetate decomposition. Acetate decomposition depends on the catalyst formulation. Decarboxylation is the most favored route at high sodium loading (2.5 and 5 wt.%); acetate decomposes in the forward direction to CH 4 and a carbonate, which further decomposes to CO 2 . In contrast, decarbonylation is prevalent for the unpromoted catalyst or catalysts having low sodium loading. Furthermore, acetate likely decomposes to CH 3 OH and CO. Adsorbed methanol may undergo further steam reforming by oxidative dehydrogenation to formate species, which decarbonylates via reverse decomposition to CO and H 2 O. Temperature programmed desorption/reaction and activity data confirmed that alkali promotion, especially at 1.8 %Na and higher loading, facilitates the forward acetate decomposition step, favoring decarboxylation over decarbonylation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Transactive control of fast-acting demand response based on thermostatic loads in real-time retail electricity markets

Coordinated operation of distributed thermostatic loads such as heat pumps and air conditioners can reduce energy costs and prevents grid congestion, while maintaining room temperatures in the comfort range set by consumers. This paper furthers efforts towards enabling thermostatically controlled loads (TCLs) to participate in real-time retail electricity markets under a transactive control paradigm. An agent-based approach is used to develop an effective and low complexity demand response control scheme for TCLs. The proposed scheme adjusts aggregated thermostatic loads according to real-time grid conditions under both heating and cooling modes. Here, a case study is presented showing the method reduces consumer electricity costs by over 10% compared to uncoordinated operation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network

Non-intrusive load monitoring (NILM) of electrical demand for the purpose of identifying load components has thus far mostly been studied using univariate data, e.g., using only whole building electricity consumption time series to identify a certain type of end-use such as lighting load. However, using additional variables in the form of multivariate time series data may provide more information in terms of extracting distinguishable features in the context of energy disaggregation. In this work, a novel probabilistic graphical modeling approach, namely the spatiotemporal pattern network (STPN) is proposed for energy disaggregation using multivariate time-series data. The STPN framework is shown to be capable of handling diverse types of multivariate time-series to improve the energy disaggregation performance. The technique outperforms the state of the art factorial hidden Markov models (FHMM) and combinatorial optimization (CO) techniques in multiple real-life test cases. Furthermore, based on two homes' aggregate electric consumption data, a similarity metric is defined for the energy disaggregation of one home using a trained model based on the other home (i.e., out-of-sample case). The proposed similarity metric allows us to enhance scalability via learning supervised models for a few homes and deploying such models to many other similar but unmodeled homes with significantly high disaggregation accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings

As utility electricity rates evolve, pairing solar photovoltaic (PV) systems with battery storage has potential to ensure the value proposition of residential solar by mitigating economic uncertainty. In addition to batteries, load control technologies can reshape customer load profiles to optimize PV system use. The combination of PV, energy storage, and load control provides an integrated approach to PV deployment, which we call 'solar plus'. The U.S. National Renewable Energy Laboratory's Renewable Energy Optimization (REopt) model is utilized to evaluate cost-optimal technology selection, sizing, and dispatch in residential buildings under a variety of rate structures and locations. The REopt model is extended to include a controllable or 'smart' domestic hot water heater model and smart air conditioner model. We find that the solar plus approach improves end user economics across a variety of rate structures - especially those that are challenging for PV - including lower grid export rates, non-coincident time-of-use structures, and demand charges.

14 SOLAR ENERGY↗
DOE OSTI2018

Impact of post-rainfall evaporation from porous roof tiles on building cooling load in subtropical China

Rainfall occurs frequently in subtropical regions of China, with the subsequent water evaporation from building roofs impacting the thermal performance and the energy consumption of buildings. In this paper, we proposed a novel simulation method using actual meteorological data to evaluate this impact. New features were developed in EnergyPlus to enable the simulation: (1) an evaporation latent heat flux source term was added to the heat balance equation of the external surface and (2) algorithms for the evaporative cooling module (ECM) were developed and implemented into EnergyPlus. The ECM experimental results showed good agreement with the simulated results. The ECM was used to assess the impact of evaporation from porous roof tiles on the cooling load of a one-floor building in subtropical China. The results show that the evaporation process decreased the maximal values of the external and internal roof surface temperatures by up to 6.4 °C and 3.2 °C, respectively, while the lower internal surface temperature decreased the room accumulated cooling load by up to 14.8% during the hot summer period. Lastly, the enhanced EnergyPlus capability can be used to evaluate the evaporative cooling performance of roofs with water-storage mediums, as well as to quantify their impact on building cooling loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Characterization of white poplar and eucalyptus after ionic liquid pretreatment as a function of biomass loading using X-ray diffraction and small angle neutron scattering

A systematic study was done to understand interactions among biomass loading during ionic liquid (IL) pretreatment, biomass type and biomass structures. White poplar and eucalyptus samples were pretreated using 1-ethyl-3-methylimidazolium acetate (EmimOAc) at 110 °C for 3 h at biomass loadings of 5, 10, 15, 20 and 25 wt%. All of the samples were chemically characterized and tested for enzymatic hydrolysis. Physical structures including biomass crystallinity and porosity were measured by X-ray diffraction (XRD) and small angle neutron scattering (SANS), respectively. SANS detected pores of radii ranging from ~25 to 625 Å, enabling assessment of contributions of pores with different sizes to increased porosity after pretreatment. Contrasting dependences of sugar conversion on white poplar and eucalyptus as a function of biomass loading were observed and cellulose crystalline structure was found to play an important role.

59 BASIC BIOLOGICAL SCIENCES↗