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Optimization of Solar Panel Orientation Considering Temporal Volatility and Scenario-Based Photovoltaic Potential: A Case Study in Seoul National University

Author

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  • Myeongchan Oh

    (Department of Energy Systems Engineering, Seoul National University, Seoul 08826, Korea)

  • Hyeong-Dong Park

    (Department of Energy Systems Engineering, Seoul National University, Seoul 08826, Korea
    Research Institute of Energy and Resources, Seoul National University, Seoul 08826, Korea)

Abstract

University campuses accommodate large numbers of people and are suitable places to organize a microgrid. The solar potential in the university area is estimated and the optimal orientation of solar panels is presented in this study. The optimal orientation is analyzed considering temporal volatility to increase the stability of the grid. Several variables are selected and scenarios are designed to consider various investments and technologies. Scenario-specific photovoltaic potentials were estimated using Geographic Information Systems analysis technology. Analysis of temporal volatility was conducted based on the difference between demand and supply of electricity. Optimal panel orientations were presented according to project objectives, such as highest efficiency or low volatility. As a result, the total potential of the study area was tens to hundreds of GWh/year depending on the scenario. The university has an advantage in hourly volatility, but has some problems in monthly volatility. The optimal orientation varies according to objectives and solar power supply ratio. The results of this study are expected to help researchers and technicians in the solar energy industry and assist in urban planning.

Suggested Citation

  • Myeongchan Oh & Hyeong-Dong Park, 2019. "Optimization of Solar Panel Orientation Considering Temporal Volatility and Scenario-Based Photovoltaic Potential: A Case Study in Seoul National University," Energies, MDPI, vol. 12(17), pages 1-17, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:17:p:3262-:d:260617
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    References listed on IDEAS

    as
    1. Benghanem, M., 2011. "Optimization of tilt angle for solar panel: Case study for Madinah, Saudi Arabia," Applied Energy, Elsevier, vol. 88(4), pages 1427-1433, April.
    2. Diane Palmer & Elena Koumpli & Ian Cole & Ralph Gottschalg & Thomas Betts, 2018. "A GIS-Based Method for Identification of Wide Area Rooftop Suitability for Minimum Size PV Systems Using LiDAR Data and Photogrammetry," Energies, MDPI, vol. 11(12), pages 1-22, December.
    3. Blakers, Andrew & Lu, Bin & Stocks, Matthew, 2017. "100% renewable electricity in Australia," Energy, Elsevier, vol. 133(C), pages 471-482.
    4. Yadav, Amit Kumar & Chandel, S.S., 2013. "Tilt angle optimization to maximize incident solar radiation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 503-513.
    5. Lave, Matthew & Kleissl, Jan, 2011. "Optimum fixed orientations and benefits of tracking for capturing solar radiation in the continental United States," Renewable Energy, Elsevier, vol. 36(3), pages 1145-1152.
    6. Suomalainen, Kiti & Wang, Vincent & Sharp, Basil, 2017. "Rooftop solar potential based on LiDAR data: Bottom-up assessment at neighbourhood level," Renewable Energy, Elsevier, vol. 111(C), pages 463-475.
    7. Brito, M.C. & Freitas, S. & Guimarães, S. & Catita, C. & Redweik, P., 2017. "The importance of facades for the solar PV potential of a Mediterranean city using LiDAR data," Renewable Energy, Elsevier, vol. 111(C), pages 85-94.
    8. Martin Libra & Milan Daneček & Jan Lešetický & Vladislav Poulek & Jan Sedláček & Václav Beránek, 2019. "Monitoring of Defects of a Photovoltaic Power Plant Using a Drone," Energies, MDPI, vol. 12(5), pages 1-9, February.
    9. Cao Yu & Yong Sheng Khoo & Jing Chai & Shuwei Han & Jianxi Yao, 2019. "Optimal Orientation and Tilt Angle for Maximizing in-Plane Solar Irradiation for PV Applications in Japan," Sustainability, MDPI, vol. 11(7), pages 1-8, April.
    10. Khan, Jibran & Arsalan, Mudassar Hassan, 2016. "Estimation of rooftop solar photovoltaic potential using geo-spatial techniques: A perspective from planned neighborhood of Karachi – Pakistan," Renewable Energy, Elsevier, vol. 90(C), pages 188-203.
    11. Xiaoyang Song & Yaohuan Huang & Chuanpeng Zhao & Yuxin Liu & Yanguo Lu & Yongguo Chang & Jie Yang, 2018. "An Approach for Estimating Solar Photovoltaic Potential Based on Rooftop Retrieval from Remote Sensing Images," Energies, MDPI, vol. 11(11), pages 1-14, November.
    12. Hong, Taehoon & Lee, Minhyun & Koo, Choongwan & Jeong, Kwangbok & Kim, Jimin, 2017. "Development of a method for estimating the rooftop solar photovoltaic (PV) potential by analyzing the available rooftop area using Hillshade analysis," Applied Energy, Elsevier, vol. 194(C), pages 320-332.
    13. Hai Lan & Jinfeng Dai & Shuli Wen & Ying-Yi Hong & David C. Yu & Yifei Bai, 2015. "Optimal Tilt Angle of Photovoltaic Arrays and Economic Allocation of Energy Storage System on Large Oil Tanker Ship," Energies, MDPI, vol. 8(10), pages 1-16, October.
    14. Jo, J.H. & Otanicar, T.P., 2011. "A hierarchical methodology for the mesoscale assessment of building integrated roof solar energy systems," Renewable Energy, Elsevier, vol. 36(11), pages 2992-3000.
    15. Oh, Myeongchan & Park, Hyeong-Dong, 2018. "A new algorithm using a pyramid dataset for calculating shadowing in solar potential mapping," Renewable Energy, Elsevier, vol. 126(C), pages 465-474.
    16. Kunta Yoshikawa & Hayato Kawasaki & Wataru Yoshida & Toru Irie & Katsunori Konishi & Kunihiro Nakano & Toshihiko Uto & Daisuke Adachi & Masanori Kanematsu & Hisashi Uzu & Kenji Yamamoto, 2017. "Silicon heterojunction solar cell with interdigitated back contacts for a photoconversion efficiency over 26%," Nature Energy, Nature, vol. 2(5), pages 1-8, May.
    17. Good, Clara & Shepero, Mahmoud & Munkhammar, Joakim & Boström, Tobias, 2019. "Scenario-based modelling of the potential for solar energy charging of electric vehicles in two Scandinavian cities," Energy, Elsevier, vol. 168(C), pages 111-125.
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    2. Quetzalcoatl Hernandez-Escobedo & Alida Ramirez-Jimenez & Jesús Manuel Dorador-Gonzalez & Miguel-Angel Perea-Moreno & Alberto-Jesus Perea-Moreno, 2020. "Sustainable Solar Energy in Mexican Universities. Case Study: The National School of Higher Studies Juriquilla (UNAM)," Sustainability, MDPI, vol. 12(8), pages 1-22, April.
    3. Oh, Myeongchan & Kim, Sung-Min & Park, Hyeong-Dong, 2020. "Estimation of photovoltaic potential of solar bus in an urban area: Case study in Gwanak, Seoul, Korea," Renewable Energy, Elsevier, vol. 160(C), pages 1335-1348.
    4. Chan, Lok Shun, 2022. "Neighbouring shading effect on photovoltaic panel system: Its implication to green building certification scheme," Renewable Energy, Elsevier, vol. 188(C), pages 476-490.
    5. James Torres Moreno & Carlos Acevedo Penaloza & Milton Coba Salcedo, 2022. "Applied Bibliometric in the Advancement of Solar Energy Research," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 424-429, July.

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