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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Impacts of Voltage-Based Grid Support Functions on Energy Production of PV Customers

This paper presents the impact of inverter grid- support functions (GSFs) on photovoltaic (PV) customer energy production on a real distribution feeder in Oahu, HI. These autonomous GSFs based on local voltage measurements are good alternatives to increase PV hosting capacity. However, these functions can result in PV energy curtailment to the customer, and this study addresses the concerns about the impact of inverter GSFs through detailed quasi-static time series (QSTS) simulations. It proposes four metrics: maximum and average GSF curtailment, average increased generation and average net generation change, to assess the impact of a given control on PV systems located on customer sites. It was found that curtailment of PV production is negligible for customers where peak voltage is within ANSI C84.1 range. A reliable relationship between curtailment and peak customer voltage is demonstrated, suggesting that peak voltage could be used as an indicator of customer curtailment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Reserve Model of Energy Storage in Day-ahead Joint Energy and Reserve Markets: A Stochastic UC Solution

With many favorable advantages including fast response ability in particular, utility-level energy storage systems (ESS) are being integrated into energy and reserve markets to help mitigate uncertain renewable resources and fluctuant demands. This paper discusses a stochastic unit commitment (UC) model to explore capabilities of ESSs in providing valuable grid services by simultaneously joining energy and reserve markets. The proposed reserve model of ESSs presents the following features: (i) two constraints are proposed to formulate ESS’s reserve provision ability in each hour via six operation modes, namely increasing/reducing the level of charge, switching to discharge, increasing/reducing the level of discharge, switching to charge; (ii) as an energy-limited asset, constraints on ESS’s reserve deliverability across multiple hours is introduced to hold enough state of charge (SOC) headroom and floor room, guaranteeing that reserves cleared in individual hours are continuously deliverable over multiple successive hours without violating operation limits. Furthermore, a scenario-based UC model, which addresses uncertainties of renewables and demands, is adopted to evaluate reserves provided by ESSs and generators. To effectively solve the stochastic UC problem, the progressive hedging algorithm with heuristic approaches is discussed. A 6-bus system and a modified IEEE 118-bus system are used to illustrate effectiveness of the proposed approaches.

25 ENERGY STORAGE↗
DOE OSTI2021

Energy demand reduction in the built environment using shallow geothermal integrated energy systems: Part II – Hybrid ground source heat pump for building heating

The research collection aims at finding the various possible opportunities for the effective integration of shallow geothermal energy (SGE) to decrease the energy demand in the built environment and to reduce emission associated with it. The direct utilization of SGE using a ground source heat pump (GSHP) has been reviewed in comprehensive review part I and part II. From the extensive review, we have found that the hybrid GSHP is needed to avoid ground thermal imbalance and peak demand. Hybrid GSHP can adopt various supplemental heat sources and sinks according to the local climatic conditions and the balance of energy demands. The primary focus on the integration of subsystems such as biomass, solar energy (PV, PVT, and collector), phase change material, micro gas turbine, and absorption heat pump with GSHP is presented for heating application. This comprehensive review part III highlights the recent research findings and a potential gap in hybrid GSHP for further research and developments

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

The Importance of Weather and Climate to Energy Systems: A Workshop on Next Generation Challenges in Energy–Climate Modeling

More than 80 international participants, representing weather, climate, and energy systems research, joined two 4-hour remote sessions to highlight and prioritize ongoing and future challenges in energy-climate modelling. The workshop had two primary goals: to build a deeper engagement across the “energy” and “climate” research communities, and to identify and begin to address the scientific challenges associated with modelling climate risk in energy systems.

17 WIND ENERGY↗
DOE OSTI2020

Planning Considerations for Energy Storage in Resilience Applications. Outcomes from the NELHA Energy Storage Conference's Policy and Regulatory Workshop

This report presents the proceedings and lessons learned at a conference workshop that discussed the role of energy storage in supporting electric system resilience, which took place at the Natural Energy Laboratory of Hawaii Authority’s (NELHA) Conference on Energy Storage Trends and Opportunities in December 2018. Staff from the Pacific Northwest National Laboratory (PNNL) made two presentations on the topic of resilience: the first covering a conceptual framework for incorporating resilience into resource planning processes, and the second covering a tool developed for microgrid planning that can assist in identifying resource mixes that will meet site-specific resilience needs. Throughout the presentations, presenters and workshop participants discussed the obstacles to improving electric system resilience and potential solutions for overcoming them. Following the workshop, the authors conducted additional research to further contextualize the topics discussed at the workshop and to frame the resulting recommendations for future engagement on this subject by the Department of Energy and the national laboratories.

25 ENERGY STORAGE↗
DOE OSTI2025

Leading Energy Analysis: Data-Driven Insights That Power Our Energy Future

Energy analysts at the National Renewable Energy Laboratory (NREL) use a broad set of expertise and cutting-edge tools to capture the complexities of our interconnected energy system. Decision-makers rely on these insights to drive cost savings, enhance grid reliability, support long-term innovation, and bolster America's energy workforce and global competitiveness. This fact sheet highlights some of NREL's high-impact analyses, data, and tools, largely focusing on power grid analysis.

data↗
DOE OSTI2024

Lifespan Impacts to Infrastructure, Renewable Energy Components and Energy Storage Components Related to Fluoropolymer Use

This report focuses on the use of fluoropolymers in infrastructure materials (building construction materials, transportation, and electrical transmission and distribution); renewable energy generation components (specifically wind and solar); and energy storage components (lithium-ion batteries and fuel cells) and product lifespan impacts if fluoropolymers were no longer available or allowed in commerce. Additionally, environmental considerations for fluoropolymer manufacture, use, and end-of-life disposal are discussed. This document is the second of two companion reports. The first report, Assessment of Fluoropolymer Production and Use With Analysis of Alternative Replacement Materials, contained an analysis of use of fluoropolymers and their potential replacement technologies in aerospace, automotive, battery, building construction, chemical processing, electronics, infrastructure, semiconductor, solar panel, and wind energy industries sectors, along with qualitative life cycle assessment (LCA) and cost-benefit analysis of replacing fluoropolymers. This report does not focus on the lifecycle aspects of use of fluoropolymer or alternatives in the designated applications. For more information on those topics, see aforementioned report.

25 ENERGY STORAGE↗
DOE OSTI2026

Energy 101 Marine Energy [Slides]

The Energy 101: Marine presentation, developed for the Energy Technology Innovation Partnership Project (ETIPP), provides an overview of marine energy. It covers technology fundamental concepts, opportunities, and case studies.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Probing transport energies and defect states in organic semiconductors using energy resolved electrochemical impedance spectroscopy

Abstract Determining the relative energies of transport states in organic semiconductors is critical to understanding the properties of electronic devices and in designing device stacks. Futhermore, defect states are also highly important and can greatly impact material properties and device performance. Recently, energy‐resolved electrochemical impedance spectroscopy (ER‐EIS) is developed to probe both the ionization energy (IE) and electron affinity (EA) as well as sub‐bandgap defect states in organic semiconductors. Herein, ER‐EIS is compared to cyclic voltammetry (CV) and photoemission spectroscopies for extracting IE and EA values, and to photothermal deflection spectroscopy (PDS) for probing defect states in both polymer and molecular organic semiconductors. The results show that ER‐EIS determined IE and EA are in better agreement with photoemission spectroscopy measurements as compared to CV for both polymer and molecular materials. Furthermore, the defect states detected by ER‐EIS agree with sub‐bandgap features detected by PDS. Surprisingly, ER‐EIS measurements of regiorandom and regioregular poly(3‐hexylthiophene) (P3HT) show clear defect bands that occur at significantly different energies. In regioregular P3HT the defect band is near the edge of the occupied states while it is near the edge of the unoccupied states in regiorandom P3HT.

14 SOLAR ENERGY↗
DOE OSTI2023

The wave energy converter control competition (WECCCOMP): Wave energy control algorithms compared in both simulation and tank testing

The wave energy control competition established a benchmark problem which was offered as an open challenge to the wave energy system control community. The competition had two stages: In the first stage, competitors used a standard wave energy simulation platform (WEC-Sim) to evaluate their controllers while, in the second stage, competitors were invited to test their controllers in a real-time implementation on a prototype system in a wave tank. The performance function used was based on converted energy across a range of standard sea states, but also included aspects related to economic performance, such as peak/average power, peak force, etc. This paper compares simulated and experimental results and, in particular, examines if the results obtained in a linear system simulation are borne out in reality. Overall, within the scope of the device tested, the range of sea states employed, and the performance metric used, the conclusion is that high-performance WEC controllers work well in practice, with good carry-over from simulation to experimentation. However, the availability of a good WEC mathematical model is deemed to be crucial.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Comparative Study on the Machine Learning-Based Prediction of Adsorption Energies for Ring and Chain Species on Metal Catalyst Surfaces

Computation of adsorption and transition state energies for a large number of surface intermediates for numerous active site models pose significant computational overhead in computational screening of catalysts. Machine learning (ML) techniques can be used to predict part of these energies. To predict the energies, ML models need to be fed appropriate metal and species descriptors. For complex surface chemistries, the structures of the intermediate species can vary greatly. In this paper, working with the hydrodeoxygenation of succinic acid on six different metal surfaces, we have studied the effect of linear and non-linear ML models used along with pen-and-paper based species descriptors and two categories of metal descriptors on two different categories of intermediate species: chain and ring. More specifically, our computations include the prediction of chain species when trained on only chain species and also when trained on both chain and ring species. Similar computations were performed for predictions of ring species. In each case, results of linear ML models were compared with kernel based non-linear models. Our results indicate that ring species data does not improve the prediction of chain species. Similarly, chain species data does not improve the prediction of ring species. The use of non-linear ML models, however, did help to minimize the prediction errors compared to the linear models. Furthermore, the study also shows that electronic or adsorption energy based metal descriptors along with bond count based species fingerprints can achieve a mean absolute error (MAE) of less than 0.2 eV for complex chain molecules when used with an appropriate machine learning model.

Adsorption↗
DOE OSTI2020

Tunable exciton binding energy in 2D hybrid layered perovskites through donor–acceptor interactions within the organic layer

The strength of electrostatic interactions within semiconductors strongly affects their performance in optoelectronic devices. An important target is the tuning of a material’s exciton binding energy—the energy binding an electron–hole pair through the electrostatic Coulomb force—independent of its electronic band gap. Here, we report on the doping of a family of two-dimensional hybrid perovskites, in which inorganic lead halide sheets alternate with naphthalene-based organic layers, with tetrachloro-1,2-benzoquinone (TCBQ). For four out of seven n = 1 perovskites, the incorporation of the electron-accepting TCBQ dopant into the organic sublattice containing the electron-donating naphthalene species enabled the tuning of the materials’ 1s exciton binding energy. The naphthalene–TCBQ electron donor–acceptor interactions increased the electrostatic screening of the exciton, in turn lowering its binding energy relative to the undoped perovskite—by almost 50% in one system. Structural and optical characterization showed that the inorganic lattice is not significantly perturbed even though the layer-to-layer spacing increases upon molecular dopant incorporation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cross-correlation of Dark Energy Survey Year 3 lensing data with ACT and Planck thermal Sunyaev-Zel’dovich effect observations. I. Measurements, systematics tests, and feedback model constraints

Here we present a tomographic measurement of the cross-correlation between thermal Sunyaev-Zel’dovich (TSZ) maps from Planck and the Atacama Cosmology Telescope and weak galaxy lensing shears measured during the first three years of observations of the Dark Energy Survey. This correlation is sensitive to the thermal energy in baryons over a wide redshift range and is therefore a powerful probe of astrophysical feedback. We detect the correlation at a statistical significance of 21σ, the highest significance to date. We examine the TSZ maps for potential contaminants, including cosmic infrared background and radio sources, finding that cosmic infrared background has a substantial impact on our measurements and must be taken into account in our analysis. We use the cross-correlation measurements to test different feedback models. In particular, we model the TSZ using several different pressure profile models calibrated against hydrodynamical simulations. Our analysis marginalizes over redshift uncertainties, shear calibration biases, and intrinsic alignment effects. We also marginalize over Ω m and σ 8 using Planck or DES priors. We find that the data prefer the model with a low amplitude of the pressure profile at small scales, compatible with a scenario with strong active galactic nuclei feedback and ejection of gas from the inner part of the halos. When using a more flexible model for the shear profile, constraints are weaker, and the data cannot discriminate between different baryonic prescriptions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. II. cosmological results

Here, we present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven 𝑤 Cold Dark Matter (𝑤⁢ CDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (𝑆 8 , Ω m ) is improved by 70% (Λ ⁢CDM) and 90% (𝑤 ⁢CDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter 𝑆 8 ≡ 𝜎 8 ⁢(Ω m /0.3) 0.5 , obtaining 𝑆 8 = 0.794 ±0.017 (Λ⁢ CDM) and 𝑆 8 = 0.817 ±0.021 (𝑤 ⁢CDM), and a ∼10% constraint on Ω m , obtaining Ω m =0.259 ±0.025 (Λ ⁢CDM) and Ω m = 0.273 ±0.029 (𝑤⁢ CDM). In the context of the 𝑤⁢ CDM scenario, these statistics also strengthen the constraints on the parameter 𝑤, obtaining 𝑤 <−0.72. The constraints from different statistics are shown to be internally consistent (with a 𝑝-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2⁢𝜎.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Installation of the Dark Energy Spectroscopic Instrument at the Mayall 4-meter telescope

The Dark Energy Spectroscopic Instrument (DESI) is a Stage IV ground-based dark energy experiment that will measure the expansion history of the Universe using the Baryon Acoustic Oscillation technique. The spectra of 35 million galaxies and quasars over 14000 square degrees will be measured during the life of the experiment. We describe the installation of the major elements of the instrument at the Mayall 4m telescope, completed in late 2019. The previous prime focus corrector, spider vanes, and upper rings were removed from the Mayall’s Serrurier truss and replaced with the newlyconstructed DESI ring, vanes, cage, hexapod, and optical corrector. The new corrector was optically aligned with the primary mirror using a laser tracker system. The DESI focal plane system was integrated to the corrector, with each of its ten 500-fiber-positioner petal segments installed using custom installation hardware and the laser tracker. Ten DESI spectrographs with 30 cryostats were installed in a newly assembled clean room in the Large Coude Room. The ten cables carrying 5000 optical fibers from the positioners in the focal plane were routed down the telescope through cable wraps at the declination and hour angle axes, and their integral slitheads were integrated with the ten spectrographs. The fiber view camera assembly was installed to the Mayall’s primary mirror cell. Servers for the instrument control system replaced existing computer equipment. The fully integrated instrument has been commissioned and is ready to start its operations phase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Emissions and Energy Impacts of the Inflation Reduction Act

If goals set under the Paris Agreement are met, the world may hold warming well below 2 degrees C (1); however, parties are not on track to deliver these commitments (2), increasing focus on policy implementation to close the gap between ambition and action. Recently, the US government passed its most prominent piece of climate legislation to date - the Inflation Reduction Act of 2022 (IRA) - designed to invest in a wide range of programs that, among other provisions, incentivize clean energy and carbon management, encourage electrification and efficiency measures, reduce methane emissions, promote domestic supply chains, and address environmental justice concerns (3). IRA's scope and complexity make modeling important to understand impacts on emissions and energy systems. We leverage results from nine independent, state-of-the-art models to examine potential implications of key IRA provisions, showing economy-wide emissions reductions between 43 and 48% below 2005 levels by 2035.

electricity↗