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Hybrid Performance Modeling of an Agrophotovoltaic System in South Korea

Author

Listed:
  • Sojung Kim

    (Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul 04620, Korea)

  • Youngjin Kim

    (Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul 04620, Korea)

  • Youngjae On

    (Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul 04620, Korea)

  • Junyong So

    (Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul 04620, Korea)

  • Chang-Yong Yoon

    (Fruit Research Institute of JARES, Haenam 59021, Korea)

  • Sumin Kim

    (Department of Environmental Horticulture & Landscape Architecture, College of Life Science & Biotechnology, Dankook University, Cheonan-si 31116, Korea)

Abstract

APV systems producing both crops and electricity are becoming popular as an alternative way of producing renewable energy in many countries with land shortage issues (e.g., South Korea). This study aims at developing a hybrid performance model of an Agrophotovoltaic (APV) system that produces crops underneath the PV modules. In this study, the physical model used to estimate solar radiation is integrated with a polynomial regression approach to forecast the amount of electricity generation and crop production in the APV system. The model takes into account not only the environmental factors (i.e., daily temperature, precipitation, humidity, and wind speed) but also physical factors (i.e., shading ratio of the APV system) related to the performance of the APV system. For more accurate modelling, the proposed approach is validated based on field experiment data collected from the APV system at Jeollanam-do Agricultural Research and Extension Services in South Korea. As a result, the proposed approach can predict the electricity generation quantity in the APV system with an R 2 of 80.4%. This will contribute to the distribution of the APV system, which will increase farmers’ income as well as the sustainability of our society.

Suggested Citation

  • Sojung Kim & Youngjin Kim & Youngjae On & Junyong So & Chang-Yong Yoon & Sumin Kim, 2022. "Hybrid Performance Modeling of an Agrophotovoltaic System in South Korea," Energies, MDPI, vol. 15(18), pages 1-13, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6512-:d:908316
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    References listed on IDEAS

    as
    1. Mohammed H. Alsharif & Jeong Kim & Jin Hong Kim, 2018. "Opportunities and Challenges of Solar and Wind Energy in South Korea: A Review," Sustainability, MDPI, vol. 10(6), pages 1-23, June.
    2. Sojung Kim & Sumin Kim, 2021. "Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea," Energies, MDPI, vol. 14(20), pages 1-13, October.
    3. Nenad Sijakovic & Aleksandar Terzic & Georgios Fotis & Ioannis Mentis & Magda Zafeiropoulou & Theodoros I. Maris & Emmanouil Zoulias & Charalambos Elias & Vladan Ristic & Vasiliki Vita, 2022. "Active System Management Approach for Flexibility Services to the Greek Transmission and Distribution System," Energies, MDPI, vol. 15(17), pages 1-31, August.
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    Cited by:

    1. Youngjin Kim & Yeongjae On & Junyong So & Sumin Kim & Sojung Kim, 2023. "A Decision Support Software Application for the Design of Agrophotovoltaic Systems in Republic of Korea," Sustainability, MDPI, vol. 15(11), pages 1-17, May.
    2. Sojung Kim & Sumin Kim, 2023. "Economic Feasibility Comparison between Building-Integrated Photovoltaics and Green Systems in Northeast Texas," Energies, MDPI, vol. 16(12), pages 1-14, June.
    3. Aidana Chalgynbayeva & Zoltán Gabnai & Péter Lengyel & Albiona Pestisha & Attila Bai, 2023. "Worldwide Research Trends in Agrivoltaic Systems—A Bibliometric Review," Energies, MDPI, vol. 16(2), pages 1-25, January.

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