MATLAB-Assisted Regression Modeling of Mean Daily Global Solar Radiation in Al-Ain, UAE

Abstract

Many researchers have modeled weather data using classical regression, time-series regression and Artificial Neural Networks (ANN) techniques. MATLAB is used in handling data and writing task specific codes for models as well as in performing statistical analysis and curve fitting works. This is due to the dynamic nature of MATLAB and its rich toolboxes that cover almost every aspect of mathematical and statistical engineering applications. Numerous authors (Abdalla & Feregh, 1988; Assi & Jama, 2010; Akinoglu & Ecevit, 1990; Al Mahdi et al., 1992; Ampratwum & Drovlo, 1999; Elagib & Mansell, 2000; Khalil & Alnajjar, 1995; Menges et al., 2006; Newland, 1988; Podesta’ et al., 2004; Sahin, 2007; Samuel, 1991; Ulgen & Hepbasli, 2002) to count few developed empirical regression models to predict the monthly average daily global solar radiation (GSR) in their region using various parameters. The mean daily sunshine duration was the most commonly used and available parameter. The most popular model was the linear model by Angstrom-Prescott (Podesta’ et al., 2004; Assi & Jama, 2010) which establishes a linear relationship between GSR and sunshine duration with knowledge of extra-terrestrial solar radiation and the theoretical maximum daily solar hours. Many studies with empirical regression models were done for diverse regions around the world. (Menges et al. 2006) reviewed 50 GSR empirical models available in literature for computing the monthly average daily GSR on a horizontal surface. They tested the models on data recorded in Konya, Turkey for comparison of model accuracy. The number of weather parameters varied between models. The diverse regression models used include linear, logarithmic, quadratic, third order polynomial, logarithmic-linear and exponential and power models relating the normalized GSR to normalized sunshine hours. Other models included in Menges work used direct regression models involving various weather parameters such as precipitation, cloud cover, etc., in addition to geographical data (altitude, latitude). (Sahin, 2007) presented a novel method for estimating the solar irradiation and sunshine duration by incorporating the atmospheric effects due to extraterrestrial solar irradiation and length of day. The author compares his model with Angstrom’s equation with favourable advantages as his method does not use Least Square Method in addition to having no procedural restrictions or assumptions. (Ulgen & Hepbasli, 2002) developed two empirical correlations to estimate the monthly average daily GSR on a horizontal surface for Izmir, Turkey. Their models resemble Angstrom type equations. They