 Radial Basis Function Network-based prediction of global solar radiation data: Application for sizing of a stand-alone photovoltaic system at Al-Madinah, Saudi ArabiaMohamed Benghanem and Adel Mellit Energy, 2010, vol. 35, issue 9, 3751-3762 Abstract: In this paper, Radial Basis Function network (RBF) is used for modelling and predicting the daily global solar radiation data using other meteorological data such as air temperature, sunshine duration, and relative humidity. These data were recorded in the period 1998–2002 at Al-Madinah (Saudi Arabia) by the National Renewable Energy Laboratory. Four RBF-models have been developed for predicting the daily global solar radiation. It was found that the RBF-model which uses the sunshine duration and air temperature as input parameters, gives accurate results as the correlation coefficient in this case is 98.80%. A comparative study between developed RBF, Multilayer perceptron and conventional regression models are presented and discussed in this paper, In addition, an application for estimating the sizing of a stand-alone PV system at Al-Maidinah is presented in order to show the effectiveness of the developed RBF-model. Keywords: Solar radiation; Prediction; Sizing; Photovoltaic; RBF network (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:35:y:2010:i:9:p:3751-3762 DOI: 10.1016/j.energy.2010.05.024 Access Statistics for this article Energy is currently edited by Henrik Lund and Mark J. Kaiser More articles in Energy from Elsevier |
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