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Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems

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  • Su, Yan
  • Chan, Lai-Cheong
  • Shu, Lianjie
  • Tsui, Kwok-Leung

Abstract

This paper develops new real time prediction models for output power and energy efficiency of solar photovoltaic (PV) systems. These models were validated using measured data of a grid-connected solar PV system in Macau. Both time frames based on yearly average and monthly average are considered. It is shown that the prediction model for the yearly/monthly average of the minutely output power fits the measured data very well with high value of R2. The online prediction model for system efficiency is based on the ratio of the predicted output power to the predicted solar irradiance. This ratio model is shown to be able to fit the intermediate phase (9am to 4pm) very well but not accurate for the growth and decay phases where the system efficiency is near zero. However, it can still serve as a useful purpose for practitioners as most PV systems work in the most efficient manner over this period. It is shown that the maximum monthly average minutely efficiency varies over a small range of 10.81% to 12.63% in different months with slightly higher efficiency in winter months.

Suggested Citation

  • Su, Yan & Chan, Lai-Cheong & Shu, Lianjie & Tsui, Kwok-Leung, 2012. "Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems," Applied Energy, Elsevier, vol. 93(C), pages 319-326.
    • Handle: RePEc:eee:appene:v:93:y:2012:i:c:p:319-326
    DOI: 10.1016/j.apenergy.2011.12.052
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    1. Joyce, A. & Rodrigues, C. & Manso, R., 2001. "Modelling a PV system," Renewable Energy, Elsevier, vol. 22(1), pages 275-280.
    2. Alam Hossain Mondal, Md. & Sadrul Islam, A.K.M., 2011. "Potential and viability of grid-connected solar PV system in Bangladesh," Renewable Energy, Elsevier, vol. 36(6), pages 1869-1874.
    3. Hove, Tawanda, 2000. "A method for predicting long-term average performance of photovoltaic systems," Renewable Energy, Elsevier, vol. 21(2), pages 207-229.
    4. Al-Ismaily, Hilal A. & Probert, Douglas, 1998. "Photovoltaic electricity prospects in oman," Applied Energy, Elsevier, vol. 59(2-3), pages 97-124, February.
    5. Celik, Ali Naci & Acikgoz, NasIr, 2007. "Modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules using four- and five-parameter models," Applied Energy, Elsevier, vol. 84(1), pages 1-15, January.
    6. 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.
    7. Mellit, A. & Benghanem, M. & Kalogirou, S.A., 2006. "An adaptive wavelet-network model for forecasting daily total solar-radiation," Applied Energy, Elsevier, vol. 83(7), pages 705-722, July.
    8. Cucumo, Mario & Rosa, Alessandro De & Ferraro, Vittorio & Kaliakatsos, Dimitrios & Marinelli, Valerio, 2006. "Performance analysis of a 3kW grid-connected photovoltaic plant," Renewable Energy, Elsevier, vol. 31(8), pages 1129-1138.
    9. Imtiaz Ashraf & A. Chandra, 2004. "Artificial neural network based models for forecasting electricity generation of grid connected solar PV power plant," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 21(1/2), pages 119-130.
    10. Ayompe, L.M. & Duffy, A. & McCormack, S.J. & Conlon, M., 2010. "Validated real-time energy models for small-scale grid-connected PV-systems," Energy, Elsevier, vol. 35(10), pages 4086-4091.
    11. Chow, T. T. & Chan, A. L. S., 2004. "Numerical study of desirable solar-collector orientations for the coastal region of South China," Applied Energy, Elsevier, vol. 79(3), pages 249-260, November.
    12. So, Jung Hun & Jung, Young Seok & Yu, Gwon Jong & Choi, Ju Yeop & Choi, Jae Ho, 2007. "Performance results and analysis of 3kW grid-connected PV systems," Renewable Energy, Elsevier, vol. 32(11), pages 1858-1872.
    13. Zhou, Wei & Yang, Hongxing & Fang, Zhaohong, 2007. "A novel model for photovoltaic array performance prediction," Applied Energy, Elsevier, vol. 84(12), pages 1187-1198, December.
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    8. Sabo, Mahmoud Lurwan & Mariun, Norman & Hizam, Hashim & Mohd Radzi, Mohd Amran & Zakaria, Azmi, 2017. "Spatial matching of large-scale grid-connected photovoltaic power generation with utility demand in Peninsular Malaysia," Applied Energy, Elsevier, vol. 191(C), pages 663-688.
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    10. Obara, Shin’ya & Konno, Daisuke & Utsugi, Yuta & Morel, Jorge, 2014. "Analysis of output power and capacity reduction in electrical storage facilities by peak shift control of PV system with bifacial modules," Applied Energy, Elsevier, vol. 128(C), pages 35-48.
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    12. Saleheen, Mohammed Zeehan & Salema, Arshad Adam & Mominul Islam, Shah Mohammad & Sarimuthu, Charles R. & Hasan, Md Zobaer, 2021. "A target-oriented performance assessment and model development of a grid-connected solar PV (GCPV) system for a commercial building in Malaysia," Renewable Energy, Elsevier, vol. 171(C), pages 371-382.
    13. Edalati, Saeed & Ameri, Mehran & Iranmanesh, Masoud & Tarmahi, Hakimeh & Gholampour, Maysam, 2016. "Technical and economic assessments of grid-connected photovoltaic power plants: Iran case study," Energy, Elsevier, vol. 114(C), pages 923-934.
    14. Alonso-Montesinos, J. & Batlles, F.J., 2015. "The use of a sky camera for solar radiation estimation based on digital image processing," Energy, Elsevier, vol. 90(P1), pages 377-386.
    15. Li, Danny H.W. & Yang, Liu & Lam, Joseph C., 2013. "Zero energy buildings and sustainable development implications – A review," Energy, Elsevier, vol. 54(C), pages 1-10.
    16. Edalati, Saeed & Ameri, Mehran & Iranmanesh, Masoud, 2015. "Comparative performance investigation of mono- and poly-crystalline silicon photovoltaic modules for use in grid-connected photovoltaic systems in dry climates," Applied Energy, Elsevier, vol. 160(C), pages 255-265.
    17. Shravanth Vasisht, M. & Vashista, G.A. & Srinivasan, J. & Ramasesha, Sheela K., 2017. "Rail coaches with rooftop solar photovoltaic systems: A feasibility study," Energy, Elsevier, vol. 118(C), pages 684-691.
    18. Manoel Henriques de Sá Campos & Chigueru Tiba, 2020. "Global Horizontal Irradiance Modeling for All Sky Conditions Using an Image-Pixel Approach," Energies, MDPI, vol. 13(24), pages 1-15, December.
    19. Christil Pasion & Torrey Wagner & Clay Koschnick & Steven Schuldt & Jada Williams & Kevin Hallinan, 2020. "Machine Learning Modeling of Horizontal Photovoltaics Using Weather and Location Data," Energies, MDPI, vol. 13(10), pages 1-14, May.
    20. Amrouche, Badia & Le Pivert, Xavier, 2014. "Artificial neural network based daily local forecasting for global solar radiation," Applied Energy, Elsevier, vol. 130(C), pages 333-341.
    21. Moslehi, Salim & Reddy, T. Agami & Katipamula, Srinivas, 2018. "Evaluation of data-driven models for predicting solar photovoltaics power output," Energy, Elsevier, vol. 142(C), pages 1057-1065.

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