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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Modeled soft X-ray solar irradiances

Solar soft X-rays have historically been inaccurately modeled in both relative variations and absolute magnitudes by empirical solar extreme ultraviolet (EUV) irradiance models. This is a result of the use of a limited number of rocket data sets which were primarily associated with the calibration of the AE-E satellite EUV data set. In this work, the EUV91 solar EUV irradiance model has been upgraded to improve the accuracy of the 3.0 to 5.0 nm relative irradiance variations. The absolute magnitude estimate of the flux in this wavelength range has also been revised upwards. The upgrade was accomplished by first digitizing the SOLRAD 11 satellite 4.4 to 6.0 nm measured energy flux data set, then extracting and extrapolating a derived 3.0 to 5.0 nm photon flux from these data, and finally by performing a correlation between these derived data and the daily and 81-day mean 10.7 cm radio flux emission using a multiple linear regression technique. A correlation coefficient of greater than 0.9 was obtained between the dependent and independent data sets. The derived and modeled 3.0 to 5.0 nm flux varies by more than an order of magnitude over a solar cycle, ranging from a flux below 1 x 10(exp 8) to a flux greater than 1 x 10(exp 9) photons per sq cm per sec. Solar rotational (27-day) variations in the flux magnitude are a factor of 2. The derived and modeled irradiance absolute values are an order of magnitude greater than previous values from rocket data sets related to the calibration of the AE-E satellite.

Tobiska, W. Kent↗
DOE OSTI2021

Prediction of Solar Irradiance and Photovoltaic Solar Energy Product Based on Cloud Coverage Estimation Using Machine Learning Methods

Cloud cover estimation from images taken by sky-facing cameras can be an important input for analyzing current weather conditions and estimating photovoltaic power generation. The constant change in position, shape, and density of clouds, however, makes the development of a robust computational method for cloud cover estimation challenging. Accurately determining the edge of clouds and hence the separation between clouds and clear sky is difficult and often impossible. Toward determining cloud cover for estimating photovoltaic output, we propose using machine learning methods for cloud segmentation. We compare several methods including a classical regression model, deep learning methods, and boosting methods that combine results from the other machine learning models. To train each of the machine learning models with various sky conditions, we supplemented the existing Singapore whole sky imaging segmentation database with hazy and overcast images collected by a camera-equipped Waggle sensor node. We found that the U-Net architecture, one of the deep neural networks we utilized, segmented cloud pixels most accurately. However, the accuracy of segmenting cloud pixels did not guarantee high accuracy of estimating solar irradiance. We confirmed that the cloud cover ratio is directly related to solar irradiance. Additionally, we confirmed that solar irradiance and solar power output are closely related; hence, by predicting solar irradiance, we can estimate solar power output. This study demonstrates that sky-facing cameras with machine learning methods can be used to estimate solar power output. This ground-based approach provides an inexpensive way to understand solar irradiance and estimate production from photovoltaic solar facilities.

14 SOLAR ENERGY↗
NASA NTRS1982

Solar irradiance variations and solar activity

A mean value for the 1 AU total solar irradiance of 1368.2 W/sq m and a downward trend of 0.05% per year were derived from measurements by the Active Cavity Radiometer Irradiance Monitor (ACRIM) experiment on the Solar Maximum Mission during 1980. Distinct temporary solar irradiance decreases associated with solar activity maxima were observed with a series of nine dips from April to October recurring at fairly regular intervals averaging 24 days. The decreases correlate inversely with sunspot area, 2800-MHz flux, and Zurich sunspot number. Dominant periods common to the irradiance and sunspot area power spectra link the irradiance decreases to sunspot flux deficit in solar active regions. Evidence of significant total irradiance modulation by facular flux excess is cited. A persistent radiative cycle of active regions consistent with the ACRIM irradiance results and the morphology of solar active regions was found. The pattern of regularly recurrent active region maxima between April and October suggests an asymmetry in solar activity generation during this period.

Willson, R. C.↗
NASA NTRS2003

Future Satellite Observations of Solar Irradiance

Required solar irradiance measurements for climate studies include those now being made by the Total Irradiance Monitor (TIM) and the Spectral Irradiance Monitor (SIM) onboard the SORCE satellite, part of the Earth Observing System fleet of NASA satellites. Equivalent or better measures of Total Solar Irradiance (TSI) and Spectral Solar Irradiance (SSI, 200 to 2000 nm) are planned for the post-2010 satellites of the National Polar-orbiting Operational Environmental Satellite System ("OESS). The design life of SORCE is 5 years, so a "Solar Irradiance Gap Filler" EOS mission is being planned for launch in the 2007 time frame, to include the same TSI and SSI measurements. Besides avoiding any gap, overlap of the data sources is also necessary for determination of possible multi-decadal trends in solar irradiance. We discuss these requirements and the impacts of data gaps, and data overlaps, that may occur in the monitoring of the critical solar radiative forcing.

Cahalan, R. F.↗
DOE OSTI2021

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

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

Cholesky factor↗
NASA NTRS1990

Solar irradiance variability during solar cycles 21 and 22

Total solar irradiance observations by the Active Cavity Radiometer Irradiance Monitor (ACRIM) on the Solar Maximum Mission, the Nimbus 7/Earth Radiation Budget (ERB), the NASA/Earth Radiation Budget Satellite (ERBS), and NOAA 9/Earth Radiation Budget Experiment (ERBE) are combined to demonstrate the characteristics of the variation of solar luminosity over the solar cycles 21 and 22 between 1978 and 1990. Observations of solar Lyman Alpha and 10.7 MHz fluxes are used to demonstrate a total irradiance variability asymmetry relative to the maximum of solar activity.

Willson, Richard C.↗
NASA NTRS2012

Nanostructured Solar Irradiation Control Materials for Solar Energy Conversion

Tailoring the solar absorptivity (alpha(sub s)) and thermal emissivity (epsilon(sub T)) of materials constitutes an innovative approach to solar energy control and energy conversion. Numerous ceramic and metallic materials are currently available for solar absorbance/thermal emittance control. However, conventional metal oxides and dielectric/metal/dielectric multi-coatings have limited utility due to residual shear stresses resulting from the different coefficient of thermal expansion of the layered materials. This research presents an alternate approach based on nanoparticle-filled polymers to afford mechanically durable solar-absorptive and thermally-emissive polymer nanocomposites. The alpha(sub s) and epsilon(sub T) were measured with various nano inclusions, such as carbon nanophase particles (CNPs), at different concentrations. Research has shown that adding only 5 wt% CNPs increased the alpha(sub s) and epsilon(sub T) by a factor of about 47 and 2, respectively, compared to the pristine polymer. The effect of solar irradiation control of the nanocomposite on solar energy conversion was studied. The solar irradiation control coatings increased the power generation of solar thermoelectric cells by more than 380% compared to that of a control power cell without solar irradiation control coatings.

Kang, Jinho↗
NASA NTRS2003

SORCE and Future Satellite Observations of Solar Irradiance

With solar activity just passing the maximum of cycle 23, SORCE is beginning a 5 year mission to measure total solar irradiance (TSI) with unprecedented accuracy using phase-sensitive detection, and to measure spectral solar irradiance (SSI) with unprecedented spectral coverage, from 1 to 2000 nm. The new Total Irradiance Monitor (TIM) has 4 active cavity radiometers, any one of which can be used as a fixed-temperature reference against any other that is exposed to the Sun via a shutter that cycles at a rate designed to minimize noise at the shutter frequency. The new Spectral Irradiance Monitor (SIM) is a dual Fery prism spectrometer that can employ either prism as a monochromatic source on the other prism, thus monitoring its transmission during the mission lifetime. Either prism can measure SSI from 200 to 2000 nm, employing the same phase-sensitive electrical substitution strategy as TIM. SORCE also carries dual SOLSTICE instruments to cover the spectral range 100-320 nm, similar to the instruments onboard UARS, and also an XUV Photometer System (XPS) similar to that on TIMED. SSI has now been added to TSI as a requirement of EOS and NPOESS, because different spectral components drive different components of the climate system - UV into upper atmosphere and stratospheric ozone, IR into tropospheric water vapor and clouds, and Visible into the oceans and biosphere. Succeeding satellite missions being planned for 2006 and 2011 will continue to monitor these critical solar variables.

Cahalan, Robert F.↗
NASA NTRS1991

Two-parameter model of total solar irradiance variation over the solar cycle

Total solar irradiance measured by the SMM/ACRIM radiometer is modelled from the Photometric Sunspot Index and the Mg II core-to-wing ratio with multiple regression analysis. Considering that the formation of the Mg II line is very similar to that of the Ca II K line, the Mg II core-to-wing ratio, measured by the Nimbus-7 and NOAA9 satellites, is used as a proxy for the bright magnetic elements, including faculae and the magnetic network. It is shown that the relationship between the variations in total solar irradiance and the above solar activity indices depends upon the phase of the solar cycle. Thus, a better fit between total irradiance and its model estimates can be achieved if the irradiance models are calculated for the declining portion and minimum of solar cycle 21, and the rising portion of solar cycle 22, respectively. There is an indication that during the rising portion of solar cycle 22, similar to the maximum time of solar cycle 21, the modelled total irradiance values underestimate the measured values. This suggests that there is an asymmetry in the long-term total irradiance variability.

Pap, Judit M.↗
DOE OSTI2021

Improving Prediction of Surface Solar Irradiance Variability by Integrating Observed Cloud Characteristics and Machine Learning

A 5-year, 1-minute resolution observational dataset of clouds and solar radiation was produced that includes two metrics of the variability in surface solar irradiance due to cloud type and fractional sky cover. Multiple regression models were trained to fit observations of surface solar irradiance variability from those two cloud property predictors. We found that ensemble tree-based methods, Random Forest and Gradient Boosting Machine, have the least overfitting issues and showed the best performance with an R2 of 0.42. While the observational data trained in this study was only from one site, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, initial comparisons of the seasonality of the statistics suggest that these results are relatively weather regime independent; the generality of such a finding across sites will be tested in future work. The observational data and developed machine learning model are being used to create a numerical weather prediction model parameterization to enable day-ahead solar variability prediction in a computationally efficient way. This is a first step towards creating a new paradigm of predicting day-ahead variability with the potential to provide a new tool to improve grid operation, planning, and resilience.

Riihimaki, Laura↗
NASA NTRS1982

Active-region evolution and solar rotation variations in solar UV irradiance, total solar irradiance, and soft X rays

Variations in the total solar irradiance, solar UV spectral irradiance, and solar soft X-ray emission caused by active region evolution and solar rotation are analyzed by using concurrent measurements from the NIMBUS 7 and GOES satellites. The observations are interpreted by using simple empirical models that relate ground-based observations of the size and location of sunspots and plages to the full-disk temporal variations. It is found that the major dips in the photospheric total solar irradiance S, which are evident in both satellite measurements and model predictions, are usually not accompanied by outstanding enhancements in the chromospheric and upper photospheric UV spectral irradiance or coronal X rays. The main cause of this difference between the variability of S and of the UV flux is that the total chromospheric plage enhancements are not outstanding at those times when the total sunspot are outstanding. X rays are even more variable because of a much wider CMD sensitivity.

Donnelly, R. F.↗
DOE OSTI2023

Influences of Cloud Microphysics on the Components of Solar Irradiance in the WRF-Solar Model

An accurate forecast of Global Horizontal solar Irradiance (GHI) and Direct Normal Irradiance (DNI) in cloudy conditions remains a major challenge in the solar energy industry. This study focuses on the impact of cloud microphysics on GHI and its partition into DNI and Diffuse Horizontal Irradiance (DHI) using the Weather Research and Forecasting model specifically designed for solar radiation applications (WRF-Solar) and seven microphysical schemes. Three stratocumulus (Sc) and five shallow cumulus (Cu) cases are simulated and evaluated against measurements at the US Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility, Southern Great Plains (SGP) site. Results show that different microphysical schemes lead to spreads in simulated solar irradiance components up to 75% and 350% from their ensemble means in the Cu and Sc cases, respectively. The Cu cases have smaller microphysical sensitivity due to a limited cloud fraction and smaller domain-averaged cloud water mixing ratio compared to Sc cases. Cloud properties also influence the partition of GHI into DNI and DHI, and the model simulates better GHI than DNI and DHI due to a non-physical error compensation between DNI and DHI. The microphysical schemes that produce more accurate liquid water paths and effective radii of cloud droplets have a better overall performance.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Comparison of high-resolution solar irradiance spectra and the solar luminosity in the period 1980-1989

In this research, we aim to determine to what extent the solar irradiance changes measured through the 1980's from orbiting vehicles are accompanied by spectroscopic irradiance changes observable from the ground. We describe fractional changes in line absorption as 'blanketing'. In section 2, we briefly review results obtained in an earlier project and which have been published. Section 3 describes the data of this investigation; section 4 describes the data reduction; section 5 describes the observational results in terms of blanketing; and section 6 describes the interpretation of the measured changes. Section 7 contains an outline of possible uses for Doppler-shift data that emerges with the measurements of the blanketing variations. Section 8 is an outline for future research suggested by our results in this project.

Mitchell, Walter E., Jr.↗
NASA NTRS1991

Solar irradiance measurements - Minimum through maximum solar activity

The Earth Radiation Budget Satellite (ERBS) and the NOAA-9 spacecraft solar monitors were used to measure the total solar irradiance during the period October 1984 to December 1989. Decreasing trends in the irradiance measurements were observed as sunspot activity decreased to minimum levels in 1986; after 1986, increasing trends were observed as sunspot activity increased. The magnitude of the irradiance variability was found to be approximately 0.1 percent between sunspot minimum and maximum (late 1989). When compared with the 1984 to 1989 indices of solar magnetic activity, the irradiance trends appear to be in phase with the 11-year sunspot cycle. Both irradiance series yielded 1,365/sq Wm as the mean value of the solar irradiance, normalized to the mean earth/sun distance. The monitors are electrical substitution, active-cavity radiometers with estimated measurement precisions and accuracies of less than 0.02 and 0.2 percent, respectively.

Lee, R. B., III↗
DOE OSTI2022

Calibration of cloud and aerosol related parameters for solar irradiance forecasts in WRF-solar

Model parameters are a major source of uncertainty in numerical weather prediction. Recently, the Weather Research and Forecasting model with Solar extensions (WRF-Solar) has been upgraded by enhancing the treatment of sub-grid scale cloud and aerosols with augmentations of a sub-grid scale cloud scheme (CLD3) and an upgraded aerosol-aware Thompson-Eidhammer scheme (TE14). However, the value of model parameters associated with these parameterizations are assigned based on limited measurements or theoretical calculations. Calibrating the most sensitive parameters has the potential to improve solar irradiance predictions. Here, we adopted a multiobjective surrogate-based optimization (SBO) framework to calibrate nine parameters used in CLD3 and TE14 that lead to the largest sensitivity in simulated irradiance. The normalized mean-absolute-error (NMAE) of global horizontal irradiance (GHI) and direct normal irradiance (DNI) are minimized by calibrating WRF-Solar over two regions including the Southern Great Plains (SGP) and Central California, in order to focus on parameter calibration under cloudy conditions with different aerosol loading. The results show that generalized linear model (GLM)-based surrogate models approximate physical models well, particularly when the third order and three-way interaction terms are considered. The SBO framework efficiently searches the parameter space for optimal solutions with less computational costs than directly calibrating the physical model. We first calibrate CLD3 parameters over the less-polluted SGP region. Optimized CLD3 parameters alone result in NMAE reduction by 14% for the site-mean and up to 33% for individual cases over the SGP region. With further calibration of TE14 parameters over the Central California during active fire periods, the optimized parameters lead to over 20% reductions of NMAE. Our investigation reveals, however, that optimizing TE14 has a limited impact on irradiance simulations under less-polluted conditions in the SGP.

14 SOLAR ENERGY↗