Vehicle grid integration planning tool: Novel approach in case of Tokyo

Reza Nadimi and Mika Goto

Applied Energy, 2025, vol. 399, issue C, No S0306261925012395

Abstract: The large-scale integration of Battery Electric Vehicles (BEVs) into the power grid poses significant challenges in demand forecasting, infrastructure planning, and energy management. This study introduces an open-source Vehicle Grid Integration (VGI) tool designed to simulate BEV driving and charging behaviors, specifically for the deployment of 58,900 BEVs in the Tokyo Metropolitan area by 2035. Unlike prior studies that focus solely on either Grid-to-Vehicle (G2V) services or charging systems, this research simultaneously investigates both G2V and Vehicle-to-Grid (V2G) services, while optimizing public charging infrastructure. Three charging strategies (slow, medium, and fast) are analyzed, and an IF-THEN rule-based engine is implemented to ensure charging adequacy after V2G discharging operations. The tool uniquely incorporates inter-zonal driver movement across 14 zones—covering approximately 18 million households—whereas existing approaches only a single region. The results indicate that under V2G scenario, an additional 11.54 MW of generation capacity is needed to meet the annual BEV energy demand of 213.8 GWh, with peak demand occurring during daytime hours, highlighting the need for investments in renewable energy. The study also finds that under V2G scenario, the annual energy flow per BEV for G2V and potential V2G operations is 3630 kWh and 3528 kWh, respectively. Furthermore, the research specifies that under V2G scenario, for every 1000 BEVs, optimal charging infrastructure includes 2 fast chargers and 59 medium-speed chargers to ensure accessibility and alleviate range anxiety. These findings provide important insights for the development of BEV infrastructure and energy management strategies.

Keywords: Vehicle grid integration; Synthetic data generation; Vehicle trip profile; Charging strategy (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2025.126509

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