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The Construction of a Mock-Up Test Building and a Statistical Analysis of the Data Acquired to Evaluate the Power Generation Performance of Photovoltaic Modules

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  • Seung-Joon Lee

    (Energy Division, Korea Conformity Laboratories, Ducksan-myon, Jinchon-gun, Choongchongbuk-do 365-841, Korea)

  • Kyu-Jin Kim

    (Energy Division, Korea Conformity Laboratories, Ducksan-myon, Jinchon-gun, Choongchongbuk-do 365-841, Korea)

  • Da-Sol Kim

    (Energy Division, Korea Conformity Laboratories, Ducksan-myon, Jinchon-gun, Choongchongbuk-do 365-841, Korea)

  • Eui-Hwan Ryu

    (Energy Division, Korea Conformity Laboratories, Ducksan-myon, Jinchon-gun, Choongchongbuk-do 365-841, Korea)

  • Jae Lee

    (Department of Systems Engineering, Ajou University, Suwon 16499, Korea)

Abstract

Traditionally, studies on the power generation performance analysis of the photovoltaic (PV) modules used in building-integrated PV (BIPV) systems have been based on computer simulations and actual experiments with constraints, resulting in the results being inaccurate and limited. This paper proposes a two-step analysis method that results in a more versatile and reliable means of analysis. The steps are: (1) construction of a mock-up test building in the form of BIPV systems and the collection of a massive amount of operational data for one year; and (2) a statistical analysis of the acquired data using Minitab software (Version: 17, Manufacturer: Minitab Inc., State College, PA, USA) to examine the power generation performance. The constructed BIPV mock-up applies design elements such as material types (c-Si and a-Si) and various directions and angles for different module installations. Prior to the analysis, the reliability of the large database (DB) constructed from the acquired data is statistically validated. Then, from the statistical correlation analysis of the DB, several plots that visualize the performance characteristics governed by design elements, including contour plots that show the region of higher performance, are generated. Further, a regression model equation for power generation performance is derived and verified. The results of this study will be useful in determining whether a BIPV system should be adopted in a building’s architectural design and, subsequently, selecting design element values for an actual BIPV system.

Suggested Citation

  • Seung-Joon Lee & Kyu-Jin Kim & Da-Sol Kim & Eui-Hwan Ryu & Jae Lee, 2020. "The Construction of a Mock-Up Test Building and a Statistical Analysis of the Data Acquired to Evaluate the Power Generation Performance of Photovoltaic Modules," Energies, MDPI, vol. 13(7), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1546-:d:337388
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    References listed on IDEAS

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    1. Paul, D. & Mandal, S.N. & Mukherjee, D. & Bhadra Chaudhuri, S.R., 2010. "Optimization of significant insolation distribution parameters – A new approach towards BIPV system design," Renewable Energy, Elsevier, vol. 35(10), pages 2182-2191.
    2. Raugei, Marco & Frankl, Paolo, 2009. "Life cycle impacts and costs of photovoltaic systems: Current state of the art and future outlooks," Energy, Elsevier, vol. 34(3), pages 392-399.
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