4.7 Article

New sunshine-based models for predicting global solar radiation using PSO (particle swarm optimization) technique

期刊

ENERGY
卷 36, 期 5, 页码 3036-3049

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2011.02.048

关键词

PSO (Particle swarm optimization); SRTs (Statistical regression techniques); GSR (Global solar radiation); Sunshine hours; Modeling

资金

  1. Islamic Republic of Iran Meteorological Office (IRIMO)
  2. Islamic Azad University, Dezful Branch

向作者/读者索取更多资源

PSO (particle swarm optimization) technique is applied to estimate monthly average daily GSR (global solar radiation) on horizontal surface for different regions of Iran. To achieve this, five new models were developed as well as six models were chosen from the literature. First, for each city, the empirical coefficients for all models were separately determined using PSO technique. The results indicate that new models which are presented in this study have better performance than existing models in the literature for 10 cities from 17 considered cities in this study. It is also shown that the empirical coefficients found for a given latitude can be generalized to estimate solar radiation in cities at similar latitude. Some case studies are presented to demonstrate this generalization with the result showing good agreement with the measurements. More importantly, these case studies further validate the models developed, and demonstrate the general applicability of the models developed. Finally, the obtained results of PSO technique were compared with the obtained results of SRTs (statistical regression techniques) on Angstrom model for all 17 cities. The results showed that obtained empirical coefficients for Angstrom model based on PSO have more accuracy than SRTs for all 17 cities. (C) 2011 Elsevier Ltd. All rights reserved.

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