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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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DOE OSTI2022

Generation of Data-Driven Expected Energy Models for Photovoltaic Systems

Although unique expected energy models can be generated for a given photovoltaic (PV) site, a standardized model is also needed to facilitate performance comparisons across fleets. Current standardized expected energy models for PV work well with sparse data, but they have demonstrated significant over-estimations, which impacts accurate diagnoses of field operations and maintenance issues. This research addresses this issue by using machine learning to develop a data-driven expected energy model that can more accurately generate inferences for energy production of PV systems. Irradiance and system capacity information was used from 172 sites across the United States to train a series of models using Lasso linear regression. The trained models generally perform better than the commonly used expected energy model from international standard (IEC 61724-1), with the two highest performing models ranging in model complexity from a third-order polynomial with 10 parameters (Radj2 = 0.994) to a simpler, second-order polynomial with 4 parameters (Radj2=0.993), the latter of which is subject to further evaluation. Subsequently, the trained models provide a more robust basis for identifying potential energy anomalies for operations and maintenance activities as well as informing planning-related financial assessments. We conclude with directions for future research, such as using splines to improve model continuity and better capture systems with low (≤1000 kW DC) capacity.

14 SOLAR ENERGY↗

DOE OSTI2027

Nodal capacity expansion planning with flexible large-scale load siting

We propose explicitly incorporating large-scale load siting into a stochastic nodal power system capacity expansion planning model that concurrently co-optimizes generation, transmission, and storage expansion. The potential operational flexibility of some of these large loads is also taken into account by considering them as consisting of a set of tranches with different reliability requirements, which are modeled as a constraint on expected served energy across operational scenarios. We implement our model as a two-stage stochastic mixed-integer optimization problem with cross-scenario expectation constraints. To overcome the challenge of scalability, we build upon existing work to implement this model on a high performance computing platform and exploit scenario parallelization using an augmented Progressive Hedging Algorithm. The algorithm is implemented using the bounding features of mpisppy, which have shown to provide satisfactory provable optimality gaps despite the absence of theoretical guarantees of convergence. We test our approach and assess the value of this proactive planning framework on total system cost and reliability metrics using realistic testcases geographically assigned to San Diego and South Carolina, with datacenter and direct air capture facilities as large loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Deciphering Degradation: Machine Learning on Real-World Performance Data

The solar investment community is in need of up-to-date and data-derived system degradation rates to use in financial models that calculate the risk and expectation of energy revenue. To date, financial models choose degradation rates from past studies that are limited and may not be representative of solar projects in development today. As the solar industry expands in all sectors (residential, commercial, and utility), there is a growing amount of energy generation data available to analyze. With the help of the open source degradation analysis code (RdTools) it is now possible to derive degradation on an ongoing basis and continuously provide up-to-date durability statistics to the investment community. Ongoing and accurate statistics of fielded photovoltaic systems allows financial stakeholders to constrain energy revenue projections, lower financial risk, and increase the bankability of solar. This presentation will provide a mid-term progress update on a 2 year SETO-funded degradation project that involves applying RdTools analysis on kWh Analytics’ industry database. With results from the RdTools analysis in hand, machine learning methods are employed to quantify how much variance of system performance degradation can be explained by predictor variables such as environmental factors, equipment bill of materials characteristics, and system design information. The goal of this presentation is to promote the usage of RdTools on an ongoing to data owners and to solicit feedback from researchers and stakeholders on how to maximize impact of the SETO-funded kWh Analytics degradation project.

14 SOLAR ENERGY↗

DOE OSTI2024

Surrogate modelling for urban building energy simulation based on the bidirectional long short-term memory model

Here, the urban microclimate is essential for accurate simulation-based urban building energy modelling (UBEM). However, a high spatial-resolution microclimate can increase the computational resources demands of UBEM. Surrogate modelling is one of the promising approaches for fast UBEM. This study proposes a bidirectional Long Short-Term Memory (LSTM)-based approach for simulation-based UBEM surrogate modelling. The estimations are aggregated into census tracts using total building floor area. A case study using UBEM to estimate annual hourly building energy use and anthropogenic heat from all existing buildings in Los Angeles County found that most of the surrogate models can complete the annual hourly simulation within 90 minutes with a normalized mean absolute error lower than 10%, and that the bidirectional LSTM outperforms the standard LSTM in accuracy. This study demonstrates the advantages of bidirectional RNN architecture in building energy surrogate modelling and is expected to promote long-term and high-resolution UBEM with detailed microclimates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Automated vehicle microscopic energy consumption study (AV-Micro): Data collection and model development

While the Adaptive Cruise Control (ACC) system in automated vehicles (AVs) is expected to impact transportation energy significantly, existing AV energy consumption models only directly adopt those developed with Human-driven Vehicle (HV) data without even slight adaptation or calibration to accommodate unique AV energy consumption features. This study will investigate how accurately HV data-based models can predict the energy consumption of AVs. Empirical trajectory data and corresponding instantaneous energy consumption rates from both AVs and HVs were collected. We adopted two classical HV data-based models to fit these data. The calibration results indicated that these models yield around 20 30% prediction errors for AVs. To further improve the prediction accuracy, this study designed an AV-Micro model by incorporating components of multiple classic energy consumption models that better capture ACC energy consumption features, including piecewise driving behavior. With this, the AV-Micro model achieves lower than 10% prediction errors. The AV-Micro model’s high consistency across different test runs was verified with statistical significance tests, demonstrating its adaptability in different driving profiles. To confirm the discrepancies between the energy consumption features of AVs and HVs, more statistical significance tests were conducted to show that the AV-Micro model cannot be directly applied to HV data. The findings by calibrated AV-Micro models revealed that AVs consume approximately 80.5–146.4 J more energy than HVs for each meter traveled. Furthermore, the frequency analysis of energy consumption indicates that there is still some room for AVs to improve energy efficiency, particularly given their larger amplitude high-frequency fluctuations.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Structure of 43 P and 42 Si in a two-level shape-coexistence model

Exclusive cross sections for the 43 P(-1p) 42 Si reaction to the lowest 0 + and 2 + states, measured at NSCL with GRETINA and the S800, are interpreted in terms of a two-level mixing (collective) model of oblate and prolate co-existing shapes. Here, using the formalism developed for deformed nuclei we calculate the spectroscopic amplitudes and exclusive cross-sections in the strong coupling limit, where for 43 P the schematic wavefunction includes the coupling of the Nilsson [211] 1/2 proton orbit. Good agreement with the experimental data is obtained when the amplitude of the oblate configuration is larger or equal than 80%, suggesting that both nuclei are predominantly oblate, in line with theoretical expectations. Model predictions for excitation energies and electromagnetic observables, that could motivate further studies of both nuclei, are also presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1995

Granularity of the Diffuse Background Observed

First results are reported from a program for measuring the field-to-field fluctuation level of the cosmic diffuse background by using differences between the two background positions of each deep exposure with the High Energy X-ray Timing Experiment (HEXTE) instrument on the Remote X Ray Timing Explorer (RXTE). With 8 million live seconds accumulated to date a fluctuation level on the 15-25 keV band is observed which is consistent with extrapolations from the High Energy Astrophysical Observatory-1 (HEAO-1) measurements. Positive results are expected eventually at higher energies. Models of (active galactic nuclei) AGN origin will eventually be constrained by this program.

Gruber, D. E.↗

NASA NTRS2020

Quantifying the Effect of Cosmic Ray Showers on the X-IFU Energy Resolution

The X-ray Integral Field Unit (X-IFU) will operate an array of more than 3000 Transition Edge Sensor pixels at 90 mK with an unprecedented energy resolution of 2.5 eV at 7 keV. In space, primary cosmic rays and secondary particles produced in the instrument structure will continuously deposit energy on the detector wafer and induce fluctuations on the pixels’ thermal bath. We have investigated through simulations of the X-IFU readout chain how these fluctuations eventually influence the energy measurement of X-ray photons. Realistic timelines of thermal bath fluctuations at different positions in the array are generated as a function of a thermal model and the expected distribution of the deposited energy of the charged particles. These are then used to model the TES response to these thermal perturbations and their influence on the onboard energy reconstruction process. Overall, we show that with adequate heatsinking, the main energy resolution degradation effect remains minimal and within the associated resolution allocation of 0.2 eV. We further study how a dedicated triggering algorithm could be put in place to flag the rarer large thermal events.

P. Peille↗

NASA NTRS1995

Diffuse Gamma-Ray Emission from the Starburst Galaxy NGC 253

The starburst galaxy NGC 253 was observed with the Energetic Gamma Ray Experiment Telescope (EGRET) aboard the Compton Gamma Ray Observatory (CGRO) satellite. We obtain a 2 sigma upper limit to the gamma-ray emission above 100 MeV of 8 x 10(exp -8) photons/sq cm/s. Because of their large gas column densities and supernova rates, nearby starburst galaxies were predicted to have gamma-ray fluxes detectable by EGRET. Our nondetection of gamma-rays from NGC 253 motivates us to reexamine in detail the premise of supernova acceleration of cosmic rays and the effect of enhanced cloud densities, photon densities, and magnetic fields on the high-energy spectra of galaxies. By modeling the expected gamma-ray and synchrotron spectra from NGC 253, we find that up to 20% of the energy from supernovae is transferred to cosmic rays in the starburst, which is consistent with supernova acceleration models. Our calculations match the EGRET and radio data well with a supernova rate of 0.08/yr, a magnetic field B greater than or approximately equal to 5 x 10(exp -5) G, a density n approximately 300/cu cm, a photon density U(sub ph) approximately 200 eV/cu cm, and an escape timescale tau(sub o) less than or approximately equal to 10 Myr.

Bertsch, David L.↗

DOE OSTI2023

Renewable electricity capacity planning with uncertainty at multiple scales

Abstract We formulate and compare optimization models of investment in renewable generation using a suite of social planning models that compute optimal generation capacity investments for a hydro-dominated electricity system where inflow uncertainty results in a risk of energy shortage. The models optimize the expected cost of capacity expansion and operation allowing for investments in hydro, geothermal, solar, wind, and thermal plant, as well as battery storage for smoothing load profiles. A novel feature is the integration of uncertain seasonal hydroelectric energy supply and short-term variability in renewable supply in a two-stage stochastic programming framework. The models are applied to data from the New Zealand electricity system and used to estimate the costs of moving to a 100% renewable electricity system by 2035. We also explore the outcomes obtained when applying different forms of CO 2 constraint that limit respectively non-renewable capacity, non-renewable generation, and CO 2 emissions on average, almost surely, or in a chance-constrained setting, and show how our models can be used to investigate the merits of a proposed pumped-hydro scheme in New Zealand’s South Island.

Ferris, Michael C.↗

DOE OSTI2023

Model Energy Codes End-Use Opportunity Analysis

Model energy codes (ASHRAE Standard 90.1 and IECC) has significantly impacted programs and policies aimed at improving energy efficiency both in United States and across the globe. Standard 90.1, first published in 1975 (originally referred to as Standard 90) provides minimum energy efficiency guidelines for designing, constructing, operating, and maintaining new construction and renovated buildings. It is updated continuously, with new editions published every 3 years. Pacific Northwest National Laboratory (PNNL) conducts simulated energy and cost savings analysis of model energy codes to determine their expected impact and to track progress toward net-zero goals and efficiency targets. Additionally, the simulation outputs are examined to assess how energy is used across primary systems within prominent U.S. commercial building types to understand how energy is used in each building type at the end-use level and to identify areas for improvements in future code cycles. This end-use opportunity analysis of model energy codes provides ASHRAE technical committees and other interested parties a better understanding of how the Standard affects various building systems and end uses, specifically, those in the Standard that most prominently influence energy efficiency. Additionally, findings provide industry stakeholders guidance in identifying building types and end-uses with the most potential for energy efficiency improvements through energy codes and those that may require beyond code measures to meet energy use reduction targets. This paper summarizes features and functionalities of a webtool created by PNNL to explore and visualize the End-Use opportunity analysis.

ASHRAE 90.1, Energy Codes, Tableau↗

DOE OSTI2023

Power flow in magnetically insulated transmission lines with ion backscatter effects

Ion backscattering off of surfaces in magnetically insulated transmission lines (MITLs) is often ignored in kinetic simulations of MITL power flow. Backscattering reduces ion current losses and the surface impact heating, which dictates the rate at which surface-adsorbed contaminants are liberated into the anode–cathode gap. Backscatter probabilities are difficult to implement in a kinetic code because there are limited data for incident ion energies less than a few keV. This paper presents an analytic model based on the Rutherford scattering formula that reproduces the measured backscatter probabilities at high incident energies and transitions to the highly reflective behavior expected at low incident energies. The backscatter model is implemented in power flow simulations, which are validated with current loss experiments conducted on the 0.4 TW Mykonos accelerator at Sandia National Laboratories. This simulation setup is then used in a high-current Z-machine shot. In conclusion, backscatter effects are found to be unimportant in the low-current Mykonos regime but significantly reduce current losses at the Z-machine scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1980

A thermalized ion explosion model for high energy sputtering and track registration

A velocity spectrum of neutral sputtered particles as well as a low resolution mass spectrum of sputtered molecular ions was measured for 4.74 MeV F-19(+2) incident of UF4. The velocity spectrum is dramatically different from spectra taken with low energy (keV) bombarding ions, and is shown to be consistent with a hot plasma of atoms in thermal equilibrium inside the target. A thermalized ion explosion model is proposed for high energy sputtering which is expected to describe track formation in dielectric materials. The model is shown to be consistent with the observed total sputtering yield and the dependence of the yield on the primary ionization rate of the incident ion.

Seiberling, L. E.↗

DOE OSTI2022

Validation of wind resource and energy production simulations for small wind turbines in the United States

Abstract. Due to financial and temporal limitations, the small wind community relies upon simplified wind speed models and energy production simulation tools to assess site suitability and produce energy generation expectations. While efficient and user-friendly, these models and tools are subject to errors that have been insufficiently quantified at small wind turbine heights. This study leverages observations from meteorological towers and sodars across the United States to validate wind speed estimates from the Wind Integration National Dataset (WIND) Toolkit, the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), revealing average biases within ±0.5 m s−1 at small wind hub heights. Observations from small wind turbines across the United States provide references for validating energy production estimates from the System Advisor Model (SAM), Wind Report, MyWindTurbine.com, and Global Wind Atlas 3 (GWA3), which are seen to overestimate actual annual capacity factors by 2.5, 4.2, 11.5, and 7.3 percentage points, respectively. In addition to quantifying the error metrics, this paper identifies sources of model and tool discrepancies, noting that interannual fluctuation in the wind resource, wind speed class, and loss assumptions produces more variability in estimates than different horizontal and vertical interpolation techniques. The results of this study provide small wind installers and owners with information about these challenges to consider when making performance estimates and thus possible adjustments accordingly. Looking to the future, recognizing these error metrics and sources of discrepancies provides model and tool researchers and developers with opportunities for product improvement that could positively impact small wind customer confidence and the ability to finance small wind projects.

17 WIND ENERGY↗

DOE OSTI2024

A supersymmetric SYK model with a curious low energy behavior

We consider N = 2,4 supersymmetric SYK models that have a peculiar low energy behavior, with the entropy going like S = S 0 + (constant)T a , where a ≠ 1. The large N equations for these models are a generalization of equations that have been previously studied as an unjustified truncation of the planar diagrams describing the BFSS matrix quantum mechanics or other related matrix models. Here we reanalyze these equations in order to better understand the low energy physics of these models. We find that the scalar fields develop large expectation values which explore the low energy valleys in the potential. The low energy physics is dominated by quadratic fluctuations around these values. These models were previously conjectured to have a spin glass phase. We did not find any evidence for this phase by using the usual diagnostics, such as searching for replica symmetry breaking solutions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1981

Heat pipe solar receiver with thermal energy storage

An HPSR Stirling engine generator system featuring latent heat thermal energy storge, excellent thermal stability and self regulating, effective thermal transport at low system delta T is described. The system was supported by component technology testing of heat pipes and of thermal storage and energy transport models which define the expected performance of the system. Preliminary and detailed design efforts were completed and manufacturing of HPSR components has begun.

Zimmerman, W. F.↗

NASA NTRS2016

Stair-Step Particle Flux Spectra on the Lunar Surface: Evidence for Nonmonotonic Potentials?

We present examples of unusual "stair‐step" differential flux spectra observed by the Apollo 14 Suprathermal Ion Detector Experiment on the lunar dayside surface in Earth's magnetotail. These spectra exhibit a relatively constant differential flux below some cutoff energy and then drop off precipitously, by about an order of magnitude or more, at higher energies. We propose that these spectra result from photoions accelerated on the lunar dayside by nonmonotonic potentials (i.e.,potentials that do not decay to zero monotonically) and present a model for the expected differential flux. The energy of the cutoff and the magnitude of the differential flux are related to the properties of the local space environment and are consistent with the observed flux spectra. If this interpretation is correct, these surface‐based ion observations provide a unique perspective that both complements and enhances the conclusions obtained by remote‐sensing orbiter observations on the Moon's exospheric and electrostatic properties.

Stair-step↗

DOE OSTI2023

Evolution and feedback of AGN jets of different cosmic ray composition

Jet feedback from active galactic nuclei (AGN) is one of the most promising mechanisms for suppressing cooling flows in cool-core clusters. However, the composition of AGN jets and bubbles remains uncertain; they could be thermally dominated, or dominated by cosmic ray proton (CRp), cosmic ray electron (CRe), or magnetic energy. In this work, we investigate the evolution and feedback effects of CRp and CRe dominated jets by conducting 3D magnetohydrodynamic simulations of AGN jet-inflated bubbles in the intracluster medium using the FLASH code. We present the evolution of their energies, dynamics, and heating, and model their expected cavity-power versus radio-luminosity relation (P cav –L R ). We find that bubbles inflated by CRe dominated jets follow a very similar dynamical evolution to CRp dominated bubbles even though CRe within bubbles suffer significantly stronger synchrotron and inverse-Compton cooling. This is because, as CRe lose their energy, the jet-inflated bubbles quickly become thermally dominated within ∼30 Myr. Their total energy stops decreasing with CR energy and evolves similarly to CRp dominated bubbles. The ability of CRe and CRp dominated bubbles to heat the intracluster medium is also comparable; the cold gas formed via local thermal instabilities is well suppressed in both cases. The CRp and CRe bubbles follow different evolutionary trajectories on the P cav –L R plane, but the values are broadly consistent with observed ranges for FR-I sources. We also discuss observational techniques that have potential for constraining the composition of AGN jets and bubbles.

79 ASTRONOMY AND ASTROPHYSICS↗