The geographical location (Latitude: 24 deg 28′ N and Longitude: 54 deg 22′ E) of Abu Dhabi city in the United Arab Emirates (UAE) favors the development and utilization of solar energy. This paper presents an artificial neural network (ANN) approach for the estimation of monthly mean global solar radiation (GSR) on a horizontal surface in Abu Dhabi. The ANN models are presented and implemented on a 16-yr measured meteorological data set for Abu Dhabi comprising the maximum daily temperature, mean daily wind speed, mean daily sunshine hours, and mean daily relative humidity between 1993 and 2008. The meteorological data between 1993 and 2003 are used for training the ANN and data between 2004 and 2008 are used for testing the estimated values. Multilayer perceptron (MLP) and radial basis function (RBF) are used as ANN learning algorithms. The results attest to the capability of ANN techniques and their ability to produce accurate estimation models.
Estimation of Global Solar Radiation Using Artificial Neural Networks in Abu Dhabi City, United Arab Emirates
Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING. Manuscript received April 12, 2012; final manuscript received October 20, 2013; published online November 26, 2013. Assoc. Editor: Philippe Blanc.
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Al-Shamisi, M., Assi, A., and Hejase, H. (November 26, 2013). "Estimation of Global Solar Radiation Using Artificial Neural Networks in Abu Dhabi City, United Arab Emirates." ASME. J. Sol. Energy Eng. May 2014; 136(2): 024502. https://doi.org/10.1115/1.4025826
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