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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Modelling and design of high performance indium phosphide solar cells

A first principles pn junction device model has predicted new designs for high voltage, high efficiency InP solar cells. Measured InP material properties were applied and device parameters (thicknesses and doping) were adjusted to obtain optimal performance designs. Results indicate that p/n InP designs will provide higher voltages and higher energy conversion efficiencies than n/p structures. Improvements to n/p structures for increased efficiency are predicted. These new designs exploit the high absorption capabilities, relatively long diffusion lengths, and modest surface recombination velocities characteristic of InP. Predictions of performance indicate achievable open-circuit voltage values as high as 943 mV for InP and a practical maximum AM0 efficiency of 22.5 percent at 1 sun and 27 C. The details of the model, the optimal InP structure and the effect of individual parameter variations on device performance are presented.

Rhoads, Sandra L.↗
DOE OSTI2025

Wind and solar energy droughts: Potential impacts on energy system dynamics and research needs

This Perspective article provides a brief overview of the topic of wind and solar energy droughts (henceforth WSDs). It does not attempt to provide a complete literature review of the subject but rather highlights some of the main concepts associated with WSDs. These include wind and solar energy drought definitions and metrics; meteorological conditions producing WSDs; a comparison of their characteristics with hydrologic droughts and hydropower droughts; model-based and observational datasets useful for WSD analyses; the linkage of WSDs to transmission, storage, and demand response; the potential impacts of WSDs vs energy demand variations; wind and solar flood events; WSD predictability; WSD dependency on climate modes of variability; climate change impacts on WSDs; and the special challenge of evaluating the characteristics of WSDs in developing countries that have limited historical data available. Finally, the manuscript identifies research areas that the authors believe would provide immediate benefit to energy system planners.

14 SOLAR ENERGY↗
DOE OSTI2024

Moving beyond the Aerosol Climatology of WRF-Solar: A Case Study over the North China Plain

Numerical weather prediction (NWP), when accessible, is a crucial input to short-term solar power forecasting. WRF-Solar, the first NWP model specifically designed for solar energy applications, has shown promising predictive capability. Nevertheless, few attempts have been made to investigate its performance under high aerosol loading, which attenuates incoming radiation significantly. The North China Plain is a polluted region due to industrialization, which constitutes a proper testbed for such investigation. Here, in this paper, aerosol direct radiative effect (DRE) on three surface shortwave radiation components (i.e., global, beam, and diffuse) during five heavy pollution episodes is studied within the WRF-Solar framework. Results show that WRF-Solar overestimates instantaneous beam radiation up to 795.3 W m -2 when the aerosol DRE is not considered. Although such overestimation can be partially offset by an underestimation of the diffuse radiation of about 194.5 W m -2 , the overestimation of the global radiation still reaches 160.2 W m -2 . This undesirable bias can be reduced when WRF-Solar is powered by Copernicus Atmosphere Monitoring Service (CAMS) aerosol forecasts, which then translates to accuracy improvements in photovoltaic (PV) power forecasts. This work also compares the forecast performance of the CAMS-powered WRF-Solar with that of the European Centre for Medium-Range Weather Forecasts model. Under high aerosol loading conditions, the irradiance forecast accuracy generated by WRF-Solar increased by 53.2% and the PV power forecast accuracy increased by 6.8%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.8% and 1.2% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.8% and 2.7% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections: Preprint

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.6\% and 1.1\% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.4\% and 2.5\% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
DOE OSTI2021

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗
NASA NTRS2005

Solar Wind Fluctuations and Their Consequences on the Magnetosphere

Efforts have been made to extract the physical meaning of each term in our prediction model of the Dst index using the solar wind as the only input. The work has been published Journal of Geophysical Research (Temerin and Li, 21002). We found different terms in the model representing different current in the magnetospheric system and each current has different rise and decay times, with the symmetric ring current the slowest, then the partial ring current, then the tail current. We also have been trying to understand the physical meaning of the diffusion coefficient used in our prediction model of relativistic electron fluxes at geostationary orbit. The model reproduced the observations of MeV electron flux variations well, the diffusion coefficient had be assumed only die to local magnetic field fluctuations, leading to its 10th power dependence on the L. We have studied the theoretical derivation of the diffusion coefficient and we believe that the effect electric field fluctuations at smaller L could become more significant. We have expanded our previous radiation belt electron prediction model, which predicted MeV electron geosynchronous orbit based on solar wind measurements, to predict MeV electrons inside geosynchronous orbit. The model results are compared with measurements from Polar/CEPPAD. Prediction efficiencies of 0.56 and 0.54, respectively, at L=6 and L=4, have been achieved over the entire year of 1998. This work wa reported at 2003 Fall AGU and has been accepted for publication in Space Weather (Barker et al., 2005). We also have used simultaneous measurements of the upstream solar wind and of energetic electrons at geosynchronous orbit to analyze the response of electrons over a very wide energy range, 50 keV-6MeV, to solar wind variations. Enhancements of energetic electron fluxes over this whole energy range are modulated by the solar wind speed and the polarity of the interplanetary magnetic field (IMF). The solar wind speed seems to be a dominant controlling parameter for electrons of all energy. This work has been published in Space Weather (Li et al., 2005).

Li, Xin-Lin↗
DOE OSTI2020

Electron temperature of the solar wind

Significance The problem of solar wind heating is one of the long-standing fundamental problems of space plasma physics. We propose that the electron component of the solar wind plasma is heated by electrons streaming from the hot solar corona and slowly losing their energy due to weak Coulomb collisions. Our first-principle kinetic derivation predicts the scaling of the solar wind electron temperature with the heliocentric distance, which is in good agreement with observations. Our theory reveals the role of the non-Maxwellian electron distribution function in the heating mechanism, and it may be valuable for interpreting the results of in situ satellite measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1996

Determination of Thermal State of Charge in Solar Heat Receivers

The research project at Howard University seeks to develop analytical and numerical capabilities to study heat transfer and fluid flow characteristics, and the prediction of the performance of solar heat receivers for space applications. Specifically, the study seeks to elucidate the effects of internal and external thermal radiation, geometrical and applicable dimensionless parameters on the overall heat transfer in space solar heat receivers. Over the last year, a procedure for the characterization of the state-of-charge (SOC) in solar heat receivers for space applications has been developed. By identifying the various factors that affect the SOC, a dimensional analysis is performed resulting in a number of dimensionless groups of parameters. Although not accomplished during the first phase of the research, data generated from a thermal simulation program can be used to determine values of the dimensionless parameters and the state-of-charge and thereby obtain a correlation for the SOC. The simulation program selected for the purpose is HOTTube, a thermal numerical computer code based on a transient time-explicit, axisymmetric model of the total solar heat receiver. Simulation results obtained with the computer program are presented the minimum and maximum insolation orbits. In the absence of any validation of the code with experimental data, results from HOTTube appear reasonable qualitatively in representing the physical situations modeled.

Glakpe, E. K.↗
NASA NTRS1989

Comparison of the measured and predicted response of the Earth Radiation Budget Experiment active cavity radiometer during solar observations

The Earth Radiation Budget Experiment consists of an array of radiometric instruments placed in earth orbit by the National Aeronautics and Space Administration to monitor the longwave and visible components of the earth's radiation budget. Presented is a dynamic electrothermal model of the active cavity radiometer used to measure the earth's total radiative exitance. Radiative exchange is modeled using the Monte Carlo method and transient conduction is treated using the finite element method. Also included is the feedback circuit which controls electrical substitution heating of the cavity. The model is shown to accurately predict the dynamic response of the instrument during solar calibration.

Mahan, J. R.↗
NASA NTRS1978

CNO abundances and hydrodynamic studies of the Nova outburst. V - 1.00-solar-mass models with small mass envelopes

The paper reports on an investigation into the consequences of thermonuclear runaways in accreted hydrogen envelopes of 100 millionths of a solar mass on 1-solar-mass white dwarfs. These evolutionary sequences predict that from 10 to 50 millionths of a solar mass will be ejected with speeds from 300 to 3800 km/s (kinetic energies of 10 to the 44th-45th power ergs). Absolute visual magnitudes as high as -8.1 are attained, well within the observed range for fast novae. In addition, the shapes of the theoretical light curves are more reminiscent of an observed fast-nova light curve than those in earlier studies. The ejected material is strongly enhanced in the products of incomplete CNO burning; the most abundant of the ejected nuclei is C-13, followed by N-14 and C-12. The differences from previous studies are attributable to the lower peak temperatures reached in these sequences. These models also produce a large overabundance of Li-7, suggesting that novae may represent significant contributors to the galactic enrichment of this nucleus.

Starrfield, S.↗
NASA NTRS1979

Prediction of energetic particle disturbances

The prediction of fluxes of energetic particles of solar or magnetospheric origin is addressed. Topics include the prediction of the properties of the particle populations generated by magnetospheric storms and substorms, and the prediction of long term variations in the populations of magnetospheric particles.

Paulikas, G. A.↗
NASA NTRS1985

Thermodynamics of clathrate hydrate at low and high pressures with application to the outer solar system

The thermodynamic stability of clathrate hydrate is calculated to predict the formation conditions corresponding to a range of solar system parameters. The calculations were performed using the statistical mechanical theory developed by van der Waals and Platteeuw (1959) and existing experimental data concerning clathrate hydrate and its components. Dissociation pressures and partition functions (Langmuir constants) are predicted at low pressure for CO clathrate (hydrate) using the properties of chemicals similar to CO. It is argued that nonsolar but well constrained noble gas abundances may be measurable by the Galileo spacecraft in the Jovian atmosphere if the observed carbon enhancement is due to bombardment of the atmosphere by clathrate-bearing planetesimals sometime after planetary formation. The noble gas abundances of the Jovian satellite Titan are predicted, assuming that most of the methane in Titan is accreted as clathrate. It is suggested that under thermodynamically appropriate conditions, complete clathration of water ice could have occurred in high-pressure nebulas around giant planets, but probably not in the outer solar nebula. The stability of clathrate in other pressure ranges is also discussed.

Lunine, J. I.↗
NASA NTRS1984

Solar cell degradation in proton radiation orbits

Significant discrepancies have been observed between predicted and actual in-orbit silicon solar array degradation in orbits other than LEO (low Earth orbits) and GEO (geosynchronous orbit). These discrepancies have been diagnosed to arise probably from a combination of a lack of appropriate solar cell test data and from inadequacies in the models that relate the unidirectional and mono-energetic proton test data to the omnidirectional flux-energy spectra actually found in orbit. Relative damage coefficients and solar cell power outputs were discussed, and also were presented in graph form. Silicon and gallium arsenide solar cells were considered.

Rauschenbach, H. S.↗
NASA NTRS1995

Experimental Results From the Thermal Energy Storage-1 (TES-1) Flight Experiment

The Thermal Energy Storage (TES) experiments are designed to provide data to help researchers understand the long-duration microgravity behavior of thermal energy storage fluoride salts that undergo repeated melting and freezing. Such data, which have never been obtained before, have direct application to space-based solar dynamic power systems. These power systems will store solar energy in a thermal energy salt, such as lithium fluoride (LiF) or a eutectic of lithium fluoride/calcium difluoride (LiF-CaF2) (which melts at a lower temperature). The energy will be stored as the latent heat of fusion when the salt is melted by absorbing solar thermal energy. The stored energy will then be extracted during the shade portion of the orbit, enabling the solar dynamic power system to provide constant electrical power over the entire orbit. Analytical computer codes have been developed to predict the performance of a spacebased solar dynamic power system. However, the analytical predictions must be verified experimentally before the analytical results can be used for future space power design applications. Four TES flight experiments will be used to obtain the needed experimental data. This article focuses on the flight results from the first experiment, TES-1, in comparison to the predicted results from the Thermal Energy Storage Simulation (TESSIM) analytical computer code.

Jacqmin, David↗
DOE OSTI2022

Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis

In recent work, we developed a Markov Chain Monte Carlo (MCMC) procedure to predict the ground state masses capable of forming the observed Solar r-process rare-earth abundance peak. By applying this method to nucleosynthesis calculations which make use of distinct astrophysical conditions and comparing our results to the latest precision mass measurements, we are able to shed light on the conditions/masses capable of producing a rare-earth peak which matches Solar data. Here we examine how our mass predictions change when using a few different sets of r-process Solar abundance residuals that have been reported in the literature. We explore how the differing error estimates of these Solar evaluations propagate through the Markov Chain Monte Carlo to our mass predictions. We find that Solar data which reports the rare-earth peak to have its highest abundance at mass number A = 162 can require distinctly different mass predictions from data with the peak centered at A = 164. Nevertheless, we find that two important general conclusions from past work, regarding the inconsistency of ‘cold’ astrophysical outflows with current mass measurements and the need for local stability at N = 104 in ‘hot’ scenarios, remain robust in the face of differing Solar data evaluations. Additionally, we show that the masses our procedure finds capable of producing a peak at A < 164 are not in line with the latest precision mass measurements.

79 ASTRONOMY AND ASTROPHYSICS↗