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.

This poster provides an overview of the fast all-sky radiation model for solar applications with narrowband irradiances on tilted surfaces (FARMS-NIT).

This paper briefly reviews the National Renewable Energy Laboratory's recent efforts on developing all-sky solar irradiance models for solar energy applications. The Fast All-sky Radiation Model for Solar applications (FARMS) utilizes the simulation of clear-sky transmittance and reflectance and a parameterization of cloud transmittance and reflectance to rapidly compute broadband irradiances on horizontal surfaces. FARMS delivers accuracy that is comparable to the two-stream approximation, but it is approximately 1,000 times faster. A FARMS-Narrowband Irradiance over Tilted surfaces (FARMS-NIT) has been developed to compute spectral irradiances on photovoltaic (PV) panels in 2002 wavelength bands. Further, FARMS-NIT has been extended for bifacial PV panels.

A new physics-based model, the Fast All-sky Radiation Model for Solar applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT), accurately computes plane-of-array (POA) irradiances in both narrow- and broad wavelength bands within the solar region. The evaluation studies suggest that the new model provides increased accuracy than a model assuming isotropic diffuse solar radiation and an empirical model linking the POA irradiances with long-term surface observations at selected locations. This study anlyzes the surface observations used by FARMS-NIT and is intended to understand the error sources under clear-sky conditions as well as their impact to the performance of FARMS-NIT.

The rather specialized field of solar and infrared radiation measurements has become increasingly important due to the increased demands by the renewable energy and climate change research communities for data with higher accuracy and increased temporal and spatial resolutions. Recent advances in radiometry, measurement systems, and information dissemination also have increased the need for refreshing the literature available for this topic. This book provides the reader with an up-to-date review of the important aspects of solar and infrared radiation measurements: radiometer design; equipment installation, operation, maintenance, and calibration; data quality assessment parameters; and the knowledge necessary to properly interpret and apply the measured data to a variety of topics. Each of the authors has more than 40 years of experience with this subject, primarily as the result of developing and operating multiple measurement stations, working with the industry to improve radiometry, and conducting various research projects. The book’s scope and subject matter have been designed to help a wide audience gain a general understanding of this subject and to serve as a technical reference. A student new to the field will benefit from the review of terminology and the historical perspective for radiometry before addressing more detailed topics in radiometry that we hope will be of interest to the more experienced reader.  Describes the strengths and weaknesses of irradiance instruments  Provides detailed information on how to assess uncertainty in measurements  Offers comprehensive background information needed to understand the use of solar instrumentation  Discusses design concepts for shadowband radiometers, sky imagers, and satellite-based estimates of solar irradiance at the Earth’s surface  Includes chapter-end questions, references, and useful links

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 RRTM 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.