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Quantifying spatio-temporal carbon intensity within a city using large-scale smart meter data: Unveiling the impact of behind-the-meter generation

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  • Sugano, Soma
  • Fujimoto, Yu
  • Ihara, Yuto
  • Mitsuoka, Masataka
  • Tanabe, Shin-ichi
  • Hayashi, Yasuhiro

Abstract

This study introduces a novel method for calculating spatio-temporal carbon intensity variations within a city using smart meter data. By integrating smart meter data with solar radiation data from weather satellites, the method predicts electricity demand and solar power generation across 1-km grid areas, achieving higher spatial resolution for carbon intensity distribution than existing models. Accounting for behind-the-meter self-consumption enables dynamic visualisation of carbon intensity variations driven by renewable energy adoption in localised urban areas, offering a more detailed assessment compared to conventional methods focusing solely on temporal fluctuations in the grid's energy mix. The method was applied to a dataset of approximately 410,000 smart meters in Utsunomiya City, Japan. Findings reveal that carbon intensity variations are affected by weather and seasonal changes. Notably, suburban areas with a higher proportion of prosumers exhibit lower carbon intensity than urban centres, highlighting significant intra-city variations linked to local renewable energy utilisation. This method can enhance the efficient use of distributed energy resources within cities and support prioritising low-carbon renewable energy through strategies such as demand response program development, optimising electric vehicle charging schedules, and identifying priority areas for photovoltaic and battery storage deployment.

Suggested Citation

  • Sugano, Soma & Fujimoto, Yu & Ihara, Yuto & Mitsuoka, Masataka & Tanabe, Shin-ichi & Hayashi, Yasuhiro, 2025. "Quantifying spatio-temporal carbon intensity within a city using large-scale smart meter data: Unveiling the impact of behind-the-meter generation," Applied Energy, Elsevier, vol. 383(C).
    • Handle: RePEc:eee:appene:v:383:y:2025:i:c:s0306261925001035
    DOI: 10.1016/j.apenergy.2025.125373
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    References listed on IDEAS

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    1. Bo Tranberg & Olivier Corradi & Bruno Lajoie & Thomas Gibon & Iain Staffell & Gorm Bruun Andresen, 2018. "Real-Time Carbon Accounting Method for the European Electricity Markets," Papers 1812.06679, arXiv.org, revised May 2019.
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