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Methodology for estimating building integrated photovoltaics electricity production under shadowing conditions and case study

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  • Masa-Bote, Daniel
  • Caamaño-Martín, Estefanía

Abstract

Building integrated photovoltaic (BIPV) systems are a relevant application of photovoltaics. In countries belonging to the International Energy Agency countries, 24% of total installed PV power corresponds to BIPV systems. Electricity losses caused by shadows over the PV generator have a significant impact on the performance of BIPV systems, being the major source of electricity losses. This paper presents a methodology to estimate electricity produced by BIPV systems which incorporates a model for shading losses. The proposed methodology has been validated on a one year study with real data from two similar PV systems placed on the south façade of a building belonging to the Technical University of Madrid. This study has covered all weather conditions: clear, partially overcast and fully overcast sky. Results of this study are shown at different time scales, resulting that the errors committed by the best performing model are below 1% and 3% in annual and daily electricity estimation. The use of models which account for the reduced performance at low irradiance levels also improves the estimation of generated electricity.

Suggested Citation

  • Masa-Bote, Daniel & Caamaño-Martín, Estefanía, 2014. "Methodology for estimating building integrated photovoltaics electricity production under shadowing conditions and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 492-500.
    • Handle: RePEc:eee:rensus:v:31:y:2014:i:c:p:492-500
    DOI: 10.1016/j.rser.2013.12.019
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    Cited by:

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    2. Oh, Jeongyoon & Koo, Choongwan & Hong, Taehoon & Jeong, Kwangbok & Lee, Minhyun, 2017. "An economic impact analysis of residential progressive electricity tariffs in implementing the building-integrated photovoltaic blind using an advanced finite element model," Applied Energy, Elsevier, vol. 202(C), pages 259-274.
    3. Lamnatou, Chr. & Mondol, J.D. & Chemisana, D. & Maurer, C., 2015. "Modelling and simulation of Building-Integrated solar thermal systems: Behaviour of the system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 36-51.
    4. Solano, J.C. & Olivieri, L. & Caamaño-Martín, E., 2017. "Assessing the potential of PV hybrid systems to cover HVAC loads in a grid-connected residential building through intelligent control," Applied Energy, Elsevier, vol. 206(C), pages 249-266.
    5. Koo, Choongwan & Hong, Taehoon & Oh, Jeongyoon & Choi, Jun-Ki, 2018. "Improving the prediction performance of the finite element model for estimating the technical performance of the distributed generation of solar power system in a building façade," Applied Energy, Elsevier, vol. 215(C), pages 41-53.
    6. Ribeiro, Alan Emanuel Duailibe & Arouca, Maurício Cardoso & Coelho, Daniel Moreira, 2016. "Electric energy generation from small-scale solar and wind power in Brazil: The influence of location, area and shape," Renewable Energy, Elsevier, vol. 85(C), pages 554-563.
    7. Park, Hyo Seon & Koo, Choongwan & Hong, Taehoon & Oh, Jeongyoon & Jeong, Kwangbok, 2016. "A finite element model for estimating the techno-economic performance of the building-integrated photovoltaic blind," Applied Energy, Elsevier, vol. 179(C), pages 211-227.

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