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A study of grid-connected photovoltaic (PV) system in Hong Kong

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  • Li, Danny H.W.
  • Cheung, K.L.
  • Lam, Tony N.T.
  • Chan, Wilco W.H.

Abstract

Photovoltaic (PV) is one of the promising solar energy applications. Measured data can give the realistic performance of PV systems under actual operating environments for product selection and system design. This paper studies a grid-connected PV system installed in an institutional building. Technical data including available solar radiation and output energy generated were systematically recorded and analyzed. The performance of the PV system is elaborated in terms of energy, environmental and financial aspects. Feed-in-tariff (FIT) schemes with high electricity selling price can encourage the deployment of PV system. The monetary payback period (MPBP) for the PV system was computed to be 72.4years when the electricity buying price is equal to the electricity selling price. If carbon trading was considered, the payback was shortened to 61.4years. The embodied energy payback period (EEPBP) was estimated to be 8.9years. The findings would be useful for planning grid-connected PV installations and applicable to other spaces with similar architectural layouts.

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  • Li, Danny H.W. & Cheung, K.L. & Lam, Tony N.T. & Chan, Wilco W.H., 2012. "A study of grid-connected photovoltaic (PV) system in Hong Kong," Applied Energy, Elsevier, vol. 90(1), pages 122-127.
  • Handle: RePEc:eee:appene:v:90:y:2012:i:1:p:122-127
    DOI: 10.1016/j.apenergy.2011.01.054
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    9. 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.
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    11. Hsu, Chiung-Wen, 2012. "Using a system dynamics model to assess the effects of capital subsidies and feed-in tariffs on solar PV installations," Applied Energy, Elsevier, vol. 100(C), pages 205-217.
    12. Ioana-Monica Pop-Calimanu & Septimiu Lica & Sorin Popescu & Dan Lascu & Ioan Lie & Radu Mirsu, 2019. "A New Hybrid Inductor-Based Boost DC-DC Converter Suitable for Applications in Photovoltaic Systems," Energies, MDPI, vol. 12(2), pages 1-32, January.
    13. Mosavi, Amir & Faghan, Yaser & Ghamisi, Pedram & Duan, Puhong & Ardabili, Sina Faizollahzadeh & Hassan, Salwana & Band, Shahab S., 2020. "Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics," OSF Preprints jrc58, Center for Open Science.
    14. Li, Danny H.W. & Lou, Siwei & Lam, Joseph C. & Wu, Ronald H.T., 2016. "Determining solar irradiance on inclined planes from classified CIE (International Commission on Illumination) standard skies," Energy, Elsevier, vol. 101(C), pages 462-470.
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    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. Ke Shi & Chuangyi Li & Choongwan Koo, 2021. "A Techno-Economic Feasibility Analysis of Mono-Si and Poly-Si Photovoltaic Systems in the Rooftop Area of Commercial Building under the Feed-In Tariff Scheme," Sustainability, MDPI, vol. 13(9), pages 1-22, April.
    18. Yao, Wanxiang & Zhang, Kang & Cao, Weixue & Li, Xianli & Wang, Yan & Wang, Xiao, 2022. "Research on the correlation between solar radiation and sky luminance based on the principle of photothermal integration," Renewable Energy, Elsevier, vol. 194(C), pages 1326-1342.
    19. Lou, Siwei & Li, Danny H.W. & Lam, Joseph C. & Chan, Wilco W.H., 2016. "Prediction of diffuse solar irradiance using machine learning and multivariable regression," Applied Energy, Elsevier, vol. 181(C), pages 367-374.
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