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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.

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  • 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. Al-Ismaily, Hilal A. & Probert, Douglas, 1998. "Photovoltaic electricity prospects in oman," Applied Energy, Elsevier, vol. 59(2-3), pages 97-124, February.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Joyce, A. & Rodrigues, C. & Manso, R., 2001. "Modelling a PV system," Renewable Energy, Elsevier, vol. 22(1), pages 275-280.
    9. 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.
    10. 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.
    11. 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.
    12. Hove, Tawanda, 2000. "A method for predicting long-term average performance of photovoltaic systems," Renewable Energy, Elsevier, vol. 21(2), pages 207-229.
    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.
    Full references (including those not matched with items on IDEAS)

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    7. 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.
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    9. 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.
    10. Li, Yanting & He, Yong & Su, Yan & Shu, Lianjie, 2016. "Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines," Applied Energy, Elsevier, vol. 180(C), pages 392-401.
    11. 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.
    12. Pang, Zhihong & Niu, Fuxin & O’Neill, Zheng, 2020. "Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons," Renewable Energy, Elsevier, vol. 156(C), pages 279-289.
    13. Yonghui Li & Qiuwei Wu & Haiyu Zhu, 2015. "Hierarchical Load Tracking Control of a Grid-Connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation," Energies, MDPI, vol. 8(3), pages 1-21, March.
    14. Siwei Lou & Wenqiang Chen & Danny H.W. Li & Mo Wang & Hainan Chen & Isaac Y.F. Lun & Dawei Xia, 2019. "Tilted Photovoltaic Energy Outputs in Outdoor Environments," Sustainability, MDPI, vol. 11(21), pages 1-17, October.
    15. 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.
    16. 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.
    17. 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.
    18. Gulin, Marko & Vašak, Mario & Perić, Nedjeljko, 2013. "Dynamical optimal positioning of a photovoltaic panel in all weather conditions," Applied Energy, Elsevier, vol. 108(C), pages 429-438.
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    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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