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Improving the prediction of DNI with physics-based representation of all-sky circumsolar radiation

Journal Article · · Solar Energy
 [1];  [1];  [1];  [2];  [2]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States)
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Direct normal irradiance (DNI) is often interpreted differently in ground measurements and forecasts using numerical weather prediction (NWP) models, leading to substantial bias in DNI forecasting especially under cloudy-sky conditions. To mitigate the bias, we use the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) to conduct physics-based simulations of solar radiation in the circumsolar region. The DNI is quantified using the sum of the radiation along the sun direction and the scattered radiation within the circumsolar region. FARMS-DNI is coupled with the Weather Research and Forecasting model with solar extensions (WRF-Solar) to predict day-ahead DNI in 9-km pixels over an extended domain covering the contiguous United States. The DNI forecasts for the entire year of 2018 are validated using surface-based observations at the Atmospheric Radiation Measurement (ARM) and Surface Radiation Budget Network (SURFRAD) sites and a satellite-based solar radiation product developed by the procedure of the National Solar Radiation Data Base (NSRDB). The results show that the WRF-Solar coupled with the conventional Beer-Bouguer-Lambert law underestimes the overall DNI forecasts by 30%-60%, which is a joint effect of the uncertainties in computing the circumsolar radiation and forecasting cloud properties. This bias is significantly reduced by using FARMS-DNI.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1839922
Report Number(s):
NREL/JA--5D00-80201; MainId:42404; UUID:b680c653-a5ef-4aee-9d13-8053a3e855e2; MainAdminID:63597
Journal Information:
Solar Energy, Journal Name: Solar Energy Vol. 231; ISSN 0038-092X
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

14 SOLAR ENERGY
DNI
solar forecasting
solar radiation