A new method to estimate average hourly global solar radiation on the horizontal surface

Pramod Pandey, Michelle L. Soupir

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

A new model, Global Solar Radiation on Horizontal Surface (GSRHS), was developed to estimate the average hourly global solar radiation on the horizontal surfaces (G h). The GSRHS model uses the transmission function (T f,ij), which was developed to control hourly global solar radiation, for predicting solar radiation. The inputs of the model were: hour of day, day (Julian) of year, optimized parameter values, solar constant (H 0), latitude, and longitude of the location of interest. The parameter values used in the model were optimized at a location (Albuquerque, NM), and these values were applied into the model for predicting average hourly global solar radiations at four different locations (Austin, TX; El Paso, TX; Desert Rock, NV; Seattle, WA) of the United States. The model performance was assessed using correlation coefficient (r), Mean Absolute Bias Error (MABE), Root Mean Square Error (RMSE), and coefficient of determinations (R 2). The sensitivities of parameter to prediction were estimated. Results show that the model performed very well. The correlation coefficients (r) range from 0.96 to 0.99, while coefficients of determination (R 2) range from 0.92 to 0.98. For daily and monthly prediction, error percentages (i.e. MABE and RMSE) were less than 20%. The approach we proposed here can be potentially useful for predicting average hourly global solar radiation on the horizontal surface for different locations, with the use of readily available data (i.e. latitude and longitude of the location) as inputs.

Original languageEnglish (US)
Pages (from-to)83-90
Number of pages8
JournalAtmospheric Research
Volume114-115
DOIs
StatePublished - Oct 1 2012
Externally publishedYes

Keywords

  • Hourly global solar radiation
  • Model
  • Optimum parameter values
  • Sensitivity

ASJC Scopus subject areas

  • Atmospheric Science

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