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Title: Advances in the Modeling of All-Sky Radiative Transfer for Solar Energy Applications

Abstract

This presentation provides a high-level overview of advances in modeling all-sky radiative transfer for solar energy applications.

Authors:
; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1340648
Report Number(s):
NREL/PO-5D00-67725
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the American Meteorological Society (AMS) 97th Annual Meeting, 22-26 January 2017, Seattle, Washington
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 24 POWER TRANSMISSION AND DISTRIBUTION; solar energy; radiative transfer model; irradiance; National Renewable Energy Laboratory

Citation Formats

Xie, Yu, Sengupta, Manajit, and Clifton, Andrew. Advances in the Modeling of All-Sky Radiative Transfer for Solar Energy Applications. United States: N. p., 2017. Web.
Xie, Yu, Sengupta, Manajit, & Clifton, Andrew. Advances in the Modeling of All-Sky Radiative Transfer for Solar Energy Applications. United States.
Xie, Yu, Sengupta, Manajit, and Clifton, Andrew. Sun . "Advances in the Modeling of All-Sky Radiative Transfer for Solar Energy Applications". United States. doi:. https://www.osti.gov/servlets/purl/1340648.
@article{osti_1340648,
title = {Advances in the Modeling of All-Sky Radiative Transfer for Solar Energy Applications},
author = {Xie, Yu and Sengupta, Manajit and Clifton, Andrew},
abstractNote = {This presentation provides a high-level overview of advances in modeling all-sky radiative transfer for solar energy applications.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 22 00:00:00 EST 2017},
month = {Sun Jan 22 00:00:00 EST 2017}
}

Conference:
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  • Solar radiation can be computed using radiative transfer models, such as the Rapid Radiation Transfer Model (RRTM) and its general circulation model applications, and used for various energy applications. Due to the complexity of computing radiation fields in aerosol and cloudy atmospheres, simulating solar radiation can be extremely time-consuming, but many approximations--e.g., the two-stream approach and the delta-M truncation scheme--can be utilized. To provide a new fast option for computing solar radiation, we developed the Fast All-sky Radiation Model for Solar applications (FARMS) by parameterizing the simulated diffuse horizontal irradiance and direct normal irradiance for cloudy conditions from the RRTMmore » runs using a 16-stream discrete ordinates radiative transfer method. The solar irradiance at the surface was simulated by combining the cloud irradiance parameterizations with a fast clear-sky model, REST2. To understand the accuracy and efficiency of the newly developed fast model, we analyzed FARMS runs using cloud optical and microphysical properties retrieved using GOES data from 2009-2012. The global horizontal irradiance for cloudy conditions was simulated using FARMS and RRTM for global circulation modeling with a two-stream approximation and compared to measurements taken from the U.S. Department of Energy's Atmospheric Radiation Measurement Climate Research Facility Southern Great Plains site. Our results indicate that the accuracy of FARMS is comparable to or better than the two-stream approach; however, FARMS is approximately 400 times more efficient because it does not explicitly solve the radiative transfer equation for each individual cloud condition. Radiative transfer model runs are computationally expensive, but this model is promising for broad applications in solar resource assessment and forecasting. It is currently being used in the National Solar Radiation Database, which is publicly available from the National Renewable Energy Laboratory at http://nsrdb.nrel.gov.« less
  • The light curves produced by all-sky monitors, such as the Rossi X-ray Timing Explorer All-Sky Monitor and the Swift Burst Alert Telescope (BAT), generally have non-uniform error bars. In searching for periodic modulation in this type of data using power spectra it can be important to use appropriate weighting of data points to achieve the best sensitivity. It was recently demonstrated that for Swift BAT data a simple weighting scheme can actually sometimes reduce the sensitivity of the power spectrum depending on source brightness. Instead, a modified weighting scheme, based on the Cochran semi-weighted mean, gives improved results independent ofmore » source brightness. We investigate the benefits of weighting power spectra in period searches using simulated GLAST LAT observations of {gamma}-ray binaries.« less
  • This study introduces the National Renewable Energy Laboratory's (NREL's) recent efforts to extend the capability of the Fast All-sky Radiation Model for Solar applications (FARMS) by computing spectral solar irradiances over both horizontal and inclined surfaces. A new model is developed by computing the optical thickness of the atmosphere using a spectral irradiance model for clear-sky conditions, SMARTS2. A comprehensive lookup table (LUT) of cloud bidirectional transmittance distribution functions (BTDFs) is precomputed for 2002 wavelength bands using an atmospheric radiative transfer model, libRadtran. The solar radiation transmitted through the atmosphere is given by considering all possible paths of photon transmissionmore » and the relevent scattering and absorption attenuation. Our results indicate that this new model has an accuracy that is similar to that of state-of-the-art radiative transfer models, but it is significantly more efficient.« less
  • A large fraction of the anticipated source detections by the Gamma-ray Large Area Space Telescope (GLAST-LAT) will initially be unidentified. We argue that traditional approaches to identify individuals and/or populations of gamma ray sources will encounter procedural limitations. Those limitations are discussed on the background of source identifications from EGRET observations. Generally, our ability to classify (faint) source populations in the anticipated GLAST dataset with the required degree of statistical confidence will be hampered by sheer source wealth. A new paradigm for achieving the classification of gamma ray source populations is discussed.
  • Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time-consuming, though many approximations (e.g., two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. In this study, we developed a fast all-sky radiation model for solar applications (FARMS)more » using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a 16-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances are created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters are fitted to the cloud transmittances and reflectances to develop the model. The all-sky solar irradiance at the land surface can then be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1,000 times faster than those currently utilized in solar resource assessment and forecasting because it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate that the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.« less