Spatially transferable regional model for half-hourly values of diffuse solar radiation for general sky conditions based on perceptron artificial neural networks

Marija Zlata Božnar, Boštjan Grašič, Amauri Pereira de Oliveira, Jacyra Soares and Primož Mlakar

Renewable Energy, 2017, vol. 103, issue C, 794-810

Abstract: We describe a procedure to build an artificial neural network model of half-hourly values of diffuse solar radiation at the surface that can be repeated for other locations in a region. The model was developed for the location of the Portorož Airport (Slovenia) using data gathered by a standard automatic meteorological station and diffuse solar radiation measured over one year. The model was constructed based on a perceptron artificial neural network, which is a universal approximator for highly nonlinear systems. To date, models of this type have been restricted to a single chosen location. An inland location at Maribor was tested as a benchmark for comparison. It is shown that the Portorož model can be directly transferable without significant quality loss to the inland location of Maribor Airport, which has a different climate. Comparison to the Maribor benchmark model gives a correlation ranging from the initial value of 0.9030 to 0.9004, RMSE increases from 40.5 to 43.7 Wm−2, coefficient of variation of the RMSE increases from 38% to 41%; values for the initial location of Portorož are 0.9453, 28.7 Wm−2, 26.4%. To the best of our knowledge, this report describes the first such regional model that is spatially transferable.

Keywords: Diffuse solar radiation model; Perceptron artificial neural networks; Geographically transferable model (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:103:y:2017:i:c:p:794-810

DOI: 10.1016/j.renene.2016.11.013

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