An accuracy assessment of an empirical sine model, a novel sine model and an artificial neural network model for forecasting illuminance/irradiance on horizontal plane of all sky types at Mahasarakham, Thailand
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Author list: Pattanasethanon S., Lertsatitthanakorn C., Atthajariyakul S., Soponronnarit S.
Publisher: Elsevier
Publication year: 2008
Journal: Energy Conversion and Management (0196-8904)
Volume number: 49
Issue number: 8
Start page: 1999
End page: 2005
Number of pages: 7
ISSN: 0196-8904
Languages: English-Great Britain (EN-GB)
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Abstract
The results of a study on all sky modeling and forecasting daylight availability for the tropical climate found in the central region of the northeastern part of Thailand (16°14′ N, 103°15′ E) is presented. The required components of sky quantities, namely, global and diffuse horizontal irradiance and global horizontal illuminance for saving energy used in buildings are estimated. The empirical sinusoidal models are validated. A and B values of the empirical sinusoidal model for all sky conditions are determined and developed to become a form of the sky conditions. In addition, a novel sinusoidal model, which consists of polynomial or exponential functions, is validated. A and B values of the empirical sinusoidal model for all sky conditions are determined and developed to become a new function in the polynomial or exponential form of the sky conditions. Novelettes, an artificial intelligent agent, namely, artificial neural network (ANN) model is also identified. Back propagation learning algorithms were used in the networks. Moreover, a one year data set and a next half year data set were used in order to train and test the neural network, respectively. Observation results from one year's round data indicate that luminosity and energy from the sky on horizontal in the area around Mahasarakham are frequently brighter than those of Bangkok. The accuracy of the validated model is determined in terms of the mean bias deviation (MBD), the root-mean-square-deviation (RMSD) and the coefficient of correlation (R2) values. A comparison of the estimated solar irradiation values and the observed values revealed a small error slide in the empirical sinusoidal model as well. In addition, some results of the sky quantity forecast by the ANN model indicate that the ANN model is more accurate than the empirical models and the novel sinusoidal models. This study confirms the ability of the ANN to predict highly accurate solar radiance/illuminance values. We believe that the ANN model is suitable as an alternative model for forecasting the sky quantities. © 2008 Elsevier Ltd. All rights reserved.
Keywords
Alternative model, Coefficient of correlation, Mean bias deviation, Root-mean-square-deviation
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