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Long-term energy output estimation for photovoltaic energy systems using synthetic solar irradiation data

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  • Celik, A.N.

Abstract

A general methodology is presented to estimate the monthly average daily energy output from photovoltaic energy systems. Energy output is estimated from synthetically generated solar radiation data. The synthetic solar radiation data are generated based on the cumulative frequency distribution of the daily clearness index, given as a function of the monthly clearness index. Two sets of synthetic solar irradiation data are generated: 3- and 4-day months. In the 3-day month, each month is represented by 3 days and in the 4-day month, by 4 days. The 3- and 4-day solar irradiation data are synthetically generated for each month and the corresponding energy outputs are calculated. A total of 8-year long measured hourly solar irradiation data, from five different locations in the world, is used to validate the new model. The monthly energy output values calculated from the synthetic solar irradiation data are compared to those calculated from the measured hour-by-hour data. It is shown that when the measured solar radiation data do not exist for a particular location or reduced data set is advantageous, the energy output from photovoltaic converters could be correctly calculated.

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  • Celik, A.N., 2003. "Long-term energy output estimation for photovoltaic energy systems using synthetic solar irradiation data," Energy, Elsevier, vol. 28(5), pages 479-493.
    • Handle: RePEc:eee:energy:v:28:y:2003:i:5:p:479-493
    DOI: 10.1016/S0360-5442(02)00140-8
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    References listed on IDEAS

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    1. Meyer, E.L & van Dyk, E.E, 2000. "Development of energy model based on total daily irradiation and maximum ambient temperature," Renewable Energy, Elsevier, vol. 21(1), pages 37-47.
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    Cited by:

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    5. Tiwari, G.N. & Mishra, R.K. & Solanki, S.C., 2011. "Photovoltaic modules and their applications: A review on thermal modelling," Applied Energy, Elsevier, vol. 88(7), pages 2287-2304, July.
    6. DeBenedictis, A. & Hoff, T.E. & Price, S. & Woo, C.K., 2010. "Statistically adjusted engineering (SAE) modeling of metered roof-top photovoltaic (PV) output: California evidence," Energy, Elsevier, vol. 35(10), pages 4178-4183.
    7. Lam, K.H. & Lai, T.M. & Lo, W.C. & To, W.M., 2012. "The application of dynamic modelling techniques to the grid-connected PV (photovoltaic) systems," Energy, Elsevier, vol. 46(1), pages 264-274.
    8. Peillón, Manuel & Sánchez, Raúl & Tarquis, Ana M. & García-Fernández, José L., 2013. "The use of wind pumps for greenhouse microirrigation: A case study for tomato in Cuba," Agricultural Water Management, Elsevier, vol. 120(C), pages 107-114.
    9. Eltawil, Mohamed A. & Zhao, Zhengming, 2010. "Grid-connected photovoltaic power systems: Technical and potential problems--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 112-129, January.
    10. Park, K.E. & Kang, G.H. & Kim, H.I. & Yu, G.J. & Kim, J.T., 2010. "Analysis of thermal and electrical performance of semi-transparent photovoltaic (PV) module," Energy, Elsevier, vol. 35(6), pages 2681-2687.

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