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Estimation of global radiation using clearness index model for sizing photovoltaic system

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  • Kumar, Ravinder
  • Umanand, L.

Abstract

A methodology for developing a simple theoretical model for calculating global insolation on a horizontal surface is described in this paper. The input parameters to the model are the latitude of the desired location and the amount of total precipitable water content in the vertical column at that location. Both the parameters are easily measurable with inexpensive instrument such as global positioning system (GPS). The principal idea behind the paper is to have a model that could be used for designing a photovoltaic system quickly and within reasonable accuracy. The model in this paper has been developed using measured data from 12 locations in India covering length and breadth of the country over a period of 9–22 years. The model is validated by calculating theoretical global insolation for five locations, one in north (New Delhi), one in south (Thiruvanandapuram), one in east (Kolkata), one in west (Mumbai) and one in central (Nagpur) part of India and comparing them with the measured insolation values for these five locations. The measured values of all these locations had been considered for developing the model. The model is further validated for a location (Goa) whose measured data is not considered for developing the model, by comparing the calculated and measured values of the insolation. Over the range of latitudes covering most parts of India, the error is within 20% of the measured value. This gives the credibility of the model and the methodology used for developing the model for any region in the world.

Suggested Citation

  • Kumar, Ravinder & Umanand, L., 2005. "Estimation of global radiation using clearness index model for sizing photovoltaic system," Renewable Energy, Elsevier, vol. 30(15), pages 2221-2233.
    • Handle: RePEc:eee:renene:v:30:y:2005:i:15:p:2221-2233
    DOI: 10.1016/j.renene.2005.02.009
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    Cited by:

    1. Makade, Rahul G. & Chakrabarti, Siddharth & Jamil, Basharat & Sakhale, C.N., 2020. "Estimation of global solar radiation for the tropical wet climatic region of India: A theory of experimentation approach," Renewable Energy, Elsevier, vol. 146(C), pages 2044-2059.
    2. Halabi, Laith M. & Mekhilef, Saad & Hossain, Monowar, 2018. "Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation," Applied Energy, Elsevier, vol. 213(C), pages 247-261.
    3. Mellit, A. & Kalogirou, S.A. & Shaari, S. & Salhi, H. & Hadj Arab, A., 2008. "Methodology for predicting sequences of mean monthly clearness index and daily solar radiation data in remote areas: Application for sizing a stand-alone PV system," Renewable Energy, Elsevier, vol. 33(7), pages 1570-1590.
    4. Harshavardhan Palahalli & Paolo Maffezzoni & Giambattista Gruosso, 2021. "Gaussian Copula Methodology to Model Photovoltaic Generation Uncertainty Correlation in Power Distribution Networks," Energies, MDPI, vol. 14(9), pages 1-16, April.
    5. Kosmopoulos, P.G. & Kazadzis, S. & Lagouvardos, K. & Kotroni, V. & Bais, A., 2015. "Solar energy prediction and verification using operational model forecasts and ground-based solar measurements," Energy, Elsevier, vol. 93(P2), pages 1918-1930.
    6. Jiang, Hou & Lu, Ning & Qin, Jun & Tang, Wenjun & Yao, Ling, 2019. "A deep learning algorithm to estimate hourly global solar radiation from geostationary satellite data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    7. Ayodele, T.R. & Ogunjuyigbe, A.S.O., 2015. "Prediction of monthly average global solar radiation based on statistical distribution of clearness index," Energy, Elsevier, vol. 90(P2), pages 1733-1742.
    8. Kaplani, E. & Kaplanis, S. & Mondal, S., 2018. "A spatiotemporal universal model for the prediction of the global solar radiation based on Fourier series and the site altitude," Renewable Energy, Elsevier, vol. 126(C), pages 933-942.
    9. Anjorin O.F. & Utah E.U & Likita M.S, 2014. "Estimation of Hourly Photo synthetically- Active Radiation (PAR) From Hourly Global Solar Radiation (GSR) In Jos, Nigeria," Asian Review of Environmental and Earth Sciences, Asian Online Journal Publishing Group, vol. 1(2), pages 43-50.
    10. Jiang, Yingni, 2009. "Computation of monthly mean daily global solar radiation in China using artificial neural networks and comparison with other empirical models," Energy, Elsevier, vol. 34(9), pages 1276-1283.
    11. Forero, N.L. & Caicedo, L.M. & Gordillo, G., 2007. "Correlation of global solar radiation values estimated and measured on an inclined surface for clear days in Bogotá," Renewable Energy, Elsevier, vol. 32(15), pages 2590-2602.
    12. Djafer, D. & Irbah, A. & Zaiani, M., 2017. "Identification of clear days from solar irradiance observations using a new method based on the wavelet transform," Renewable Energy, Elsevier, vol. 101(C), pages 347-355.
    13. Mellit, Adel & Kalogirou, Soteris A. & Drif, Mahmoud, 2010. "Application of neural networks and genetic algorithms for sizing of photovoltaic systems," Renewable Energy, Elsevier, vol. 35(12), pages 2881-2893.
    14. Sourav Malakar & Saptarsi Goswami & Bhaswati Ganguli & Amlan Chakrabarti & Sugata Sen Roy & K. Boopathi & A. G. Rangaraj, 2022. "Deep-Learning-Based Adaptive Model for Solar Forecasting Using Clustering," Energies, MDPI, vol. 15(10), pages 1-16, May.
    15. Pandey, Chanchal Kumar & Katiyar, A.K., 2009. "A comparative study to estimate daily diffuse solar radiation over India," Energy, Elsevier, vol. 34(11), pages 1792-1796.
    16. Roumpakias, Elias & Zogou, Olympia & Stamatelos, Anastassios, 2015. "Correlation of actual efficiency of photovoltaic panels with air mass," Renewable Energy, Elsevier, vol. 74(C), pages 70-77.
    17. Lu, Ning & Qin, Jun & Yang, Kun & Sun, Jiulin, 2011. "A simple and efficient algorithm to estimate daily global solar radiation from geostationary satellite data," Energy, Elsevier, vol. 36(5), pages 3179-3188.
    18. Seyed Abbas Mousavi Maleki & H. Hizam & Chandima Gomes, 2017. "Estimation of Hourly, Daily and Monthly Global Solar Radiation on Inclined Surfaces: Models Re-Visited," Energies, MDPI, vol. 10(1), pages 1-28, January.

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    Keywords

    Modelling; Solar; Insolation; PV;
    All these keywords.

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