4.7 Article

Proposal of a regressive model for the hourly diffuse solar radiation under all sky conditions

Journal

ENERGY CONVERSION AND MANAGEMENT
Volume 51, Issue 5, Pages 881-893

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2009.11.024

Keywords

Solar radiation; Diffuse fraction; Regressive model; Logistic model

Funding

  1. Spanish Ministry of Science and Technology [ENE2007-67849-C02-01]
  2. Andalusian Ministry of Science and Technology [P07-RNM-02872]
  3. Agencia Estatal de Meteorologia de Espana(AEMET)
  4. Spanish International Cooperation Agency (Spanish Foreign Office Ministry)
  5. NREL

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In this work, we propose a new regressive model for the estimation of the hourly diffuse solar irradiation under all sky conditions. This new model is based on the sigmoid function and uses the clearness index and the relative optical mass as predictors. The model performance was compared against other five regressive models using radiation data corresponding to 21 stations in the USA and Europe. In a first part, the 21 stations were grouped into seven subregions (corresponding to seven different climatic regions) and all the models were locally-fitted and evaluated using these seven datasets. Results showed that the new proposed model provides slightly better estimates. Particularly, this new model provides a relative root mean square error in the range 25-35% and a relative mean bias error in the range -15% to 15%, depending on the region. In a second part, the potential global character of the new model was evaluated. To this end, the model was fitted using the whole dataset. Results showed that the global fitting model provides overall better estimates that the locally-fitted models, with relative root mean square error values ranging 20-35% and a relative mean bias error ranging -5% to -12%. Additionally, the new proposed model showed some advantages compared to other evaluated models. Particularly, the sigmoid behaviour of this model is able to provide physically reliable estimates for extreme values of the clearness index even though using less parameter than other tested models. (C) 2009 Elsevier Ltd. All rights reserved.

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