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Digital numerical map-oriented estimation of solar energy potential for site selection of photovoltaic solar panels on national highway slopes

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  • Jung, Jaehoon
  • Han, SangUk
  • Kim, Byungil

Abstract

Photovoltaic systems are promising replacements for fossil fuels at places where high solar energy is available. The estimation of available solar energy is the key to maximizing energy generation because sites with high available solar energy must be selected. Previous approaches to site selection required several experts to avoid subjective biases, often relying on rough estimations where the topography was not fully considered. Therefore, this study proposes a computational method that estimates the potential of solar energy for prioritizing and selecting sites for photovoltaic solar panels using publicly available digital numerical maps. These maps provide various kinds of spatial data to support proper land utilization. We focus on the use of national highway slopes as potential installation sites because they are typically unused public areas with high accessibility and few restrictions. For the estimation of annual solar irradiation, elevation contours and highway networks are first separated from the digital numerical maps. The extracted contours are subsequently used to generate a set of topographic data for the estimation. The extracted highway network is used to produce a binary mask representing fill slopes within which grid cells of high solar energy are identified and clustered to locate suitable sites. The proposed method is applied to a test site near Gongju, South Korea, where top 10 potential installation sites are clustered and ranked based on their estimated annual solar irradiation. The most suitable site is identified in eastern Gongju with an annual solar energy of approximately 49,623.7 MWh.

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  • Jung, Jaehoon & Han, SangUk & Kim, Byungil, 2019. "Digital numerical map-oriented estimation of solar energy potential for site selection of photovoltaic solar panels on national highway slopes," Applied Energy, Elsevier, vol. 242(C), pages 57-68.
    • Handle: RePEc:eee:appene:v:242:y:2019:i:c:p:57-68
    DOI: 10.1016/j.apenergy.2019.03.101
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    7. José Eduardo Tafula & Constantino Dário Justo & Pedro Moura & Jérôme Mendes & Ana Soares, 2023. "Multicriteria Decision-Making Approach for Optimum Site Selection for Off-Grid Solar Photovoltaic Microgrids in Mozambique," Energies, MDPI, vol. 16(6), pages 1-41, March.
    8. Heo, Jae & Jung, Jaehoon & Kim, Byungil & Han, SangUk, 2020. "Digital elevation model-based convolutional neural network modeling for searching of high solar energy regions," Applied Energy, Elsevier, vol. 262(C).
    9. ur Rehman, Naveed & Hijazi, Mohamad & Uzair, Muhammad, 2020. "Solar potential assessment of public bus routes for solar buses," Renewable Energy, Elsevier, vol. 156(C), pages 193-200.
    10. Kim, Byungil & Han, SangUk & Heo, Jae & Jung, Jaehoon, 2020. "Proof-of-concept of a two-stage approach for selecting suitable slopes on a highway network for solar photovoltaic systems: A case study in South Korea," Renewable Energy, Elsevier, vol. 151(C), pages 366-377.
    11. Lindberg, O. & Birging, A. & Widén, J. & Lingfors, D., 2021. "PV park site selection for utility-scale solar guides combining GIS and power flow analysis: A case study on a Swedish municipality," Applied Energy, Elsevier, vol. 282(PA).
    12. Zhang, Kai & Chen, Min & Yang, Yue & Zhong, Teng & Zhu, Rui & Zhang, Fan & Qian, Zhen & Lü, Guonian & Yan, Jinyue, 2022. "Quantifying the photovoltaic potential of highways in China," Applied Energy, Elsevier, vol. 324(C).
    13. Tuhibur Rahman & Ahmed Al Mansur & Molla Shahadat Hossain Lipu & Md. Siddikur Rahman & Ratil H. Ashique & Mohamad Abou Houran & Rajvikram Madurai Elavarasan & Eklas Hossain, 2023. "Investigation of Degradation of Solar Photovoltaics: A Review of Aging Factors, Impacts, and Future Directions toward Sustainable Energy Management," Energies, MDPI, vol. 16(9), pages 1-30, April.
    14. Zhang, Yuhu & Ren, Jing & Pu, Yanru & Wang, Peng, 2020. "Solar energy potential assessment: A framework to integrate geographic, technological, and economic indices for a potential analysis," Renewable Energy, Elsevier, vol. 149(C), pages 577-586.
    15. Mengjin Hu & Xiaoyang Song & Zhongxu Bao & Zhao Liu & Mengju Wei & Yaohuan Huang, 2022. "Evaluation of the Economic Potential of Photovoltaic Power Generation in Road Spaces," Energies, MDPI, vol. 15(17), pages 1-16, September.
    16. Gardashov, Rauf & Eminov, Murad & Kara, Gökhan & Emecen Kara, Esma Gül & Mammadov, Tural & Huseynova, Xedce, 2020. "The optimum daily direction of solar panels in the highlands, derived by an analytical method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    17. Yiqing Dai & Yan Yin & Yundi Lu, 2021. "Strategies to Facilitate Photovoltaic Applications in Road Structures for Energy Harvesting," Energies, MDPI, vol. 14(21), pages 1-14, October.

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