A review of solar energy modeling techniques

Tamer Khatib, Azah Mohamed and K. Sopian

Renewable and Sustainable Energy Reviews, 2012, vol. 16, issue 5, 2864-2869

Abstract: Solar radiation data provide information on how much of the sun's energy strikes a surface at a location on the earth during a particular time period. These data are needed for effective research in solar-energy utilization. Due to the cost of and difficulty in solar radiation measurements and these data are not readily available, alternative ways of generating these data are needed. In this paper, a review is made on the solar energy modeling techniques which are classified based on the nature of the modeling technique. Linear, nonlinear, artificial intelligence models for solar energy prediction have been considered in this review. The outcome of the review showed that the sunshine ratio, ambient temperature and relative humidity are the most correlated coefficients to solar energy.

Keywords: Solar energy; Solar radiation; Modeling; ANN (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (47)

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DOI: 10.1016/j.rser.2012.01.064

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