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Statistical approach to the proposition and validation of daily diffuse irradiation models

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  • Munawwar, Saima
  • Muneer, Tariq

Abstract

This paper explores the prospects of using sunshine duration and cloud cover in estimations of daily diffuse irradiation besides the conventional use of global irradiation, where all the parameters are gathered from typical ground-based measurements and proposes optimal region-based models. Data from eight locations across four countries are used for model proposition and subsequent evaluation. Daily sunshine fraction (SF) and daily cloudiness factor (CF) are used along with daily clearness index (Kt) by inter-combination to develop a series of diffuse ratio (K) empirical models for each site. Various statistical tools are employed to establish the criterion of best performing model. Each model's performance is initially assessed, based on the data it is derived from, and then validated against an independent dataset. This validation is demonstrated by two means: first by testing the models developed for one site against another site in the same region and, secondly by testing the models derived from one section of data against a reserved section from the same site covering a different period of time. The accuracy of prediction is evaluated using three statistical measures (AS, SD, t-statistic). The final assessment also includes calculated versus measured diffuse irradiation plots and indicators such as percent MBD and percent RMSD for potential models. It was found that a model based on Kt and SF (and/or CF) performs better than a model based on Kt alone within the same data set. However, if these models are tested against the data belonging to a different period of time or a different site, the improvement is less significant. Such model-specificity can be attributed to the fact that the proposed models involve more than one measured parameter, hence greater uncertainty, as against the single-input Kt model. Given the climatological variants that differ from site-to-site and measurement uncertainties owing to the poor meteorological standards within the same dataset, validation of such models becomes a challenging task. Nevertheless, it is found that the Kt, SF model is an optimum choice when estimating diffuse radiation for independent data, as it yields improved results even over the local K-Kt model. Thus, this investigation establishes the improvement in estimation of daily diffuse irradiation that can possibly be achieved through incorporating effective variables along with global radiation for both local as well as independent sites.

Suggested Citation

  • Munawwar, Saima & Muneer, Tariq, 2007. "Statistical approach to the proposition and validation of daily diffuse irradiation models," Applied Energy, Elsevier, vol. 84(4), pages 455-475, April.
  • Handle: RePEc:eee:appene:v:84:y:2007:i:4:p:455-475
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    References listed on IDEAS

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    1. Myers, Daryl R., 2005. "Solar radiation modeling and measurements for renewable energy applications: data and model quality," Energy, Elsevier, vol. 30(9), pages 1517-1531.
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    1. El-Sebaii, A.A. & Al-Hazmi, F.S. & Al-Ghamdi, A.A. & Yaghmour, S.J., 2010. "Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia," Applied Energy, Elsevier, vol. 87(2), pages 568-576, February.
    2. Li, Huashan & Bu, Xianbiao & Long, Zhen & Zhao, Liang & Ma, Weibin, 2012. "Calculating the diffuse solar radiation in regions without solar radiation measurements," Energy, Elsevier, vol. 44(1), pages 611-615.
    3. Wang, Lunche & Lu, Yunbo & Zou, Ling & Feng, Lan & Wei, Jing & Qin, Wenmin & Niu, Zigeng, 2019. "Prediction of diffuse solar radiation based on multiple variables in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 151-216.
    4. Miguel, A.F. & Silva, A., 2010. "Solar irradiation in diffusely enclosures with partitions," Applied Energy, Elsevier, vol. 87(3), pages 836-842, March.
    5. Li, Huashan & Ma, Weibin & Wang, Xianlong & Lian, Yongwang, 2011. "Estimating monthly average daily diffuse solar radiation with multiple predictors: A case study," Renewable Energy, Elsevier, vol. 36(7), pages 1944-1948.
    6. Furlan, Claudia & de Oliveira, Amauri Pereira & Soares, Jacyra & Codato, Georgia & Escobedo, João Francisco, 2012. "The role of clouds in improving the regression model for hourly values of diffuse solar radiation," Applied Energy, Elsevier, vol. 92(C), pages 240-254.
    7. Evseev, Efim G. & Kudish, Avraham I., 2009. "An assessment of a revised Olmo et al. model to predict solar global radiation on a tilted surface at Beer Sheva, Israel," Renewable Energy, Elsevier, vol. 34(1), pages 112-119.

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