Assessing the Performance of the Fast All-sky Radiation Model for Solar Applications with Narrowband Irradiances on Tilted Surfaces (FARMS-NIT): Preprint

Title: Assessing the Performance of the Fast All-sky Radiation Model for Solar Applications with Narrowband Irradiances on Tilted Surfaces (FARMS-NIT): Preprint

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Abstract

This study evaluates the performance of a new radiative transfer model, Fast All-sky Radiation Model for Solar Applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT), that efficiently computes spectral irradiances on inclined photovoltaic panels. FARMS-NIT numerically solves the spatial distribution of solar radiation in 2,002 wavelength bands and thereby accurately provides plane-of-array (POA) irradiances by integrating radiances over inclined surfaces. The FARMS-NIT for clear- and cloudy-sky conditions are used to compute POA irradiances for Typical Meteorological Year 3 sites and compared with the simulation by TMYSPEC. Our results indicate that FARMS-NIT leads to approximately 5% greater spectral irradiances compared to TMYSPEC. The difference in POA irradiance with a latitude tilt angle is slightly larger than global horizontal irradiance.

Authors:

Xie, Yu ^[1];

^[1]

National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Publication Date:: 2018-06-02

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:: 1457333

Report Number(s):: NREL/CP-5D00-71595

DOE Contract Number:: AC36-08GO28308

Resource Type:: Conference

Resource Relation:: Conference: Presented at the 2018 World Conference on Photovoltaic Energy Conversion (WCPEC-7), 10-15 June 2018, Waikoloa, Hawaii

Country of Publication:: United States

Language:: English

Subject:: 14 SOLAR ENERGY; Fast All-sky Radiation Model for Solar Applications with Narrowband Irradiances on Tilted Surfaces; FARMS-NIT; plane-of-array; POA; irradiance

Citation Formats


                    Xie, Yu, and Sengupta, Manajit. Assessing the Performance of the Fast All-sky Radiation Model for Solar Applications with Narrowband Irradiances on Tilted Surfaces (FARMS-NIT): Preprint.  United States: N. p., 2018. 
        Web.

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                    Xie, Yu, & Sengupta, Manajit. Assessing the Performance of the Fast All-sky Radiation Model for Solar Applications with Narrowband Irradiances on Tilted Surfaces (FARMS-NIT): Preprint.  United States.

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                    Xie, Yu, and Sengupta, Manajit. Sat .  
        "Assessing the Performance of the Fast All-sky Radiation Model for Solar Applications with Narrowband Irradiances on Tilted Surfaces (FARMS-NIT): Preprint".  United States.  https://www.osti.gov/servlets/purl/1457333.

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@article{osti_1457333,

  title        = {Assessing the Performance of the Fast All-sky Radiation Model for Solar Applications with Narrowband Irradiances on Tilted Surfaces (FARMS-NIT): Preprint},

  author       = {Xie, Yu and Sengupta, Manajit},

  abstractNote = {This study evaluates the performance of a new radiative transfer model, Fast All-sky Radiation Model for Solar Applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT), that efficiently computes spectral irradiances on inclined photovoltaic panels. FARMS-NIT numerically solves the spatial distribution of solar radiation in 2,002 wavelength bands and thereby accurately provides plane-of-array (POA) irradiances by integrating radiances over inclined surfaces. The FARMS-NIT for clear- and cloudy-sky conditions are used to compute POA irradiances for Typical Meteorological Year 3 sites and compared with the simulation by TMYSPEC. Our results indicate that FARMS-NIT leads to approximately 5% greater spectral irradiances compared to TMYSPEC. The difference in POA irradiance with a latitude tilt angle is slightly larger than global horizontal irradiance.},

  doi          = {},

  url          = {https://www.osti.gov/biblio/1457333},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {2018},

  month        = {6}

}

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