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GIS-based solar irradiance estimation method in vehicle integrated photovoltaic

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  • Bunme, Pawita
  • Mizuno, Hidenori
  • Takashima, Takumi
  • Oozeki, Takashi

Abstract

Vehicle Integrated Photovoltaics (VIPV), introduced to Japan’s mobility market in 2017, support the transition to carbon neutrality by 2050. However, solar power generation decreases during driving due to environmental shading. This study presents a method to estimate solar irradiance (W/m2) for VIPV using GIS and Himawari-8/9 satellite data in a time series analysis. The method was validated in Fukushima City, where VIPV operates as a community car service. GIS-based solar maps were created from elevation models to identify shading effects during VIPV operation. Simulated direct and diffuse irradiation were used to calculate shading factors, and satellite-estimated irradiance data were applied to estimate total irradiance in a geographic coordinate system. Estimated irradiance at five-minute intervals were validated with actual data collected from VIPV along the specified route. The estimation results aligned with measured data on different operation dates and routes, with normalized mean absolute error (nMAE) of 3%–7% under clear-sky and 12%–13% under partly cloudy conditions. Additional error metrics including mean bias error (MBE) and root mean square error (RMSE), were calculated. The proposed method is expected to improve future VIPV route planning and advance VIPV technology in transportation systems.

Suggested Citation

  • Bunme, Pawita & Mizuno, Hidenori & Takashima, Takumi & Oozeki, Takashi, 2026. "GIS-based solar irradiance estimation method in vehicle integrated photovoltaic," Renewable Energy, Elsevier, vol. 256(PG).
    • Handle: RePEc:eee:renene:v:256:y:2026:i:pg:s0960148125021184
    DOI: 10.1016/j.renene.2025.124454
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    References listed on IDEAS

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    1. Olga Kanz & Angèle Reinders & Johanna May & Kaining Ding, 2020. "Environmental Impacts of Integrated Photovoltaic Modules in Light Utility Electric Vehicles," Energies, MDPI, vol. 13(19), pages 1-14, October.
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    3. Pawita Bunme & Shuhei Yamamoto & Atsushi Shiota & Yasunori Mitani, 2021. "GIS-Based Distribution System Planning for New PV Installations," Energies, MDPI, vol. 14(13), pages 1-18, June.
    4. Kim, Hanjin & Ku, Jiyoon & Kim, Sung-Min & Park, Hyeong-Dong, 2022. "A new GIS-based algorithm to estimate photovoltaic potential of solar train: Case study in Gyeongbu line, Korea," Renewable Energy, Elsevier, vol. 190(C), pages 713-729.
    5. Pochont, Nitin Ralph & Sekhar Y, Raja, 2023. "Recent trends in photovoltaic technologies for sustainable transportation in passenger vehicles – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 181(C).
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