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Quantifying the photovoltaic potential of highways in China

Author

Listed:
  • Zhang, Kai
  • Chen, Min
  • Yang, Yue
  • Zhong, Teng
  • Zhu, Rui
  • Zhang, Fan
  • Qian, Zhen
  • Lü, Guonian
  • Yan, Jinyue

Abstract

Installing photovoltaic (PV) modules on highways is considered a promising way to support carbon neutrality in China. However, collecting the area of the highway, and precisely assessing the shadow area of the highway under complex terrain remain challenges. That severely hinders the assessment of highway PV potential.To address these challenges, a spatiotemporal model is developed in this study to estimate the annual solar PV potential on highways over the whole Chinese territory.First, the areas of different highway segments are calculated based on highway network and highway toll stations. Second, hourly shadow area on highways created by nearby terrain is estimated based on a digital elevation model (DEM). When calculating the highway PV potential, the solar irradiation received in these shadow areas is regarded as zero. Finally, the PV potential of all lanes and emergency lanes was estimated at the prefecture-level city scale using surface radiation data and radiation assessment models. Based on the highway data with a total mileage of 143,684 km at the end of 2020, the results show that the annual PV potential is 3,932 TW and that the corresponding installed capacity is 700.85 GW, which can generate clean electricity at a rate of up to 629.06 TWh. The annual PV potential of highways in the southeast is greater than that in the northwest owing to the higher highway density in the southeast. This study provides a reference basis for highway PV construction planning and suitably assessment in each region of China for PV highway development.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:appene:v:324:y:2022:i:c:s0306261922009072
    DOI: 10.1016/j.apenergy.2022.119600
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    Cited by:

    1. Saiz, Albert & Salazar-Miranda, Arianna, 2023. "Understanding Urban Economies, Land Use, and Social Dynamics in the City: Big Data and Measurement," IZA Discussion Papers 16501, Institute of Labor Economics (IZA).
    2. Liu, Jiang & Wu, Qifeng & Lin, Zhipeng & Shi, Huijie & Wen, Shaoyang & Wu, Qiaoyu & Zhang, Junxue & Peng, Changhai, 2023. "A novel approach for assessing rooftop-and-facade solar photovoltaic potential in rural areas using three-dimensional (3D) building models constructed with GIS," Energy, Elsevier, vol. 282(C).
    3. Jiang, Wei & Zhang, Shuo & Wang, Teng & Zhang, Yufei & Sha, Aimin & Xiao, Jingjing & Yuan, Dongdong, 2024. "Evaluation method for the availability of solar energy resources in road areas before route corridor planning," Applied Energy, Elsevier, vol. 356(C).
    4. Yujiang Ye & Ruifeng Shi & Yuqin Gao & Xiaolei Ma & Di Wang, 2023. "Two-Stage Optimal Scheduling of Highway Self-Consistent Energy System in Western China," Energies, MDPI, vol. 16(5), pages 1-18, March.
    5. Zhang, Kai & Wang, Dajiang & Chen, Min & Zhu, Rui & Zhang, Fan & Zhong, Teng & Qian, Zhen & Wang, Yazhou & Li, Hengyue & Wang, Yijie & Lü, Guonian & Yan, Jinyue, 2024. "Power generation assessment of photovoltaic noise barriers across 52 major Chinese cities," Applied Energy, Elsevier, vol. 361(C).

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