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Performance Evaluation and Prediction of BIPV Systems under Partial Shading Conditions Using Normalized Efficiency

Author

Listed:
  • Chul-sung Lee

    (Future Agricultural Division, Rural Research Institute, Gyeonggi-do 15634, Korea)

  • Hyo-mun Lee

    (Department of Architectural Engineering, Hanbat National University, Daejeon 34158, Korea)

  • Min-joo Choi

    (Department of Architectural Engineering, Hanbat National University, Daejeon 34158, Korea)

  • Jong-ho Yoon

    (Department of Architectural Engineering, Hanbat National University, Daejeon 34158, Korea)

Abstract

The performance of the Operable Building Integrated Photovoltaic (OBIPV) system applied to the building envelope to reduce the building energy consumption varies significantly depending on the operation method and influence of the surrounding environment. Therefore, optimization through performance monitoring is necessary to maximize power generation of the system. This study used temperature-corrected normalized efficiency (NE*) to evaluate the power generation performance of the operation methods and predict that of the OBIPV system based upon the measured data. It was confirmed that power generation performance decreased when the photovoltaic (PV) operation angle changed, the system remaining the same. A decrease in power generation performance due to partial shading from an overhang was also observed. As a result of the power generation prediction for two months using NE*, the error of the measured values was found to be less than 3%. In addition, with or without any partial shading of the OBIPV system, its performance degradation was predicted with an annual electricity generation decrease by 36 kWh/yr (6.5%). Therefore, NE* can be used as an indicator for evaluating the power generation performance of PV systems, and to predict generation performance considering partial shading.

Suggested Citation

  • Chul-sung Lee & Hyo-mun Lee & Min-joo Choi & Jong-ho Yoon, 2019. "Performance Evaluation and Prediction of BIPV Systems under Partial Shading Conditions Using Normalized Efficiency," Energies, MDPI, vol. 12(19), pages 1-16, October.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:19:p:3777-:d:273527
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    References listed on IDEAS

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    1. Germán Ramos Ruiz & Carlos Fernández Bandera, 2017. "Validation of Calibrated Energy Models: Common Errors," Energies, MDPI, vol. 10(10), pages 1-19, October.
    2. Mellit, A. & Tina, G.M. & Kalogirou, S.A., 2018. "Fault detection and diagnosis methods for photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1-17.
    3. Omer, S.A. & Wilson, R. & Riffat, S.B., 2003. "Monitoring results of two examples of building integrated PV (BIPV) systems in the UK," Renewable Energy, Elsevier, vol. 28(9), pages 1387-1399.
    4. Ishaque, Kashif & Salam, Zainal, 2013. "A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 475-488.
    5. Jin-Hee Kim & Ha-Ryeon Kim & Jun-Tae Kim, 2015. "Analysis of Photovoltaic Applications in Zero Energy Building Cases of IEA SHC/EBC Task 40/Annex 52," Sustainability, MDPI, vol. 7(7), pages 1-19, July.
    6. Touati, Farid & Al-Hitmi, M.A. & Chowdhury, Noor Alam & Hamad, Jehan Abu & San Pedro Gonzales, Antonio J.R., 2016. "Investigation of solar PV performance under Doha weather using a customized measurement and monitoring system," Renewable Energy, Elsevier, vol. 89(C), pages 564-577.
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