AIMS Energy, 2017, 5(5): 798-813. doi: 10.3934/energy.2017.5.798

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Estimating solar irradiance using genetic programming technique and meteorological records

1 Department of Math and Statistics for Engineering, American University of the Middle East, Egaila, Kuwait
2 Department of Electrical and Electronics Engineering, International University of Beirut, Lebanon

Solar irradiance is one of the most important parameters that need to be estimated and modeled before engaging in any solar energy project. This article describes a non-linear regression model based on genetic programming technique for estimating solar irradiance in a specific region in the United Arab Emirates. The genetic programming is an evolutionary computing technique that enables automatic search for complex solutions. The best nonlinear modeling function that can estimate the global solar radiation on horizontal will be developed taking into account measured meteorological data. A reference approach to model the solar radiation is first presented. An enhanced approach is then presented which consists of multi nonlinear functions of regression in a parallel structure where each function is designed to estimate the global solar irradiance in a specific seasonal period of the year. Statistical analysis measures have been used to evaluate the performance of the proposed approaches. The obtained results are comparable with the outcomes of models developed by other researchers in the field.
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Copyright Info: © 2017, Rami Al-Hajj, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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