Low-carbon routing and charging planning for electric freight trucks utilizing local surplus solar power

Ryoji Miyabe, Yu Fujimoto, Yasuhiro Hayashi · 2025 · 5 citationsRead the paper

The decarbonization of freight transport via electric vehicles (EVs) is hampered not only by operational constraints but also by the CO 2 emission factor of charging electricity. This study addresses this challenge by proposing a novel Electric Vehicle Routing Problem (EVRP) framework that strategically absorbs local, spatiotemporally variable surplus photovoltaic (PV) power, based on transport-side access to surplus information. Unlike prior studies that passively assume the availability of renewable energy , our approach enables delivery operators to proactively adjust both the timing and location of charging in response to surplus forecasts, thereby optimizing charging behavior accordingly. Our primary innovation is a mixed-integer programming model with an objective function that directly minimizes CO 2 emissions by distinguishing between carbon-intensive grid power and low-carbon surplus PV based on smart metering data. The model optimizes delivery routes and en-route charging schedules by integrating day-ahead forecasts of regional surplus power. Through a data-driven case study in Utsunomiya, Japan , our method demonstrated a 16.6 % average reduction in CO 2 emissions from charging compared to conventional depot-only charging strategies. In high-surplus scenarios, reductions exceeded 60 %. Crucially, these reductions were achieved while satisfying delivery time window constraints and maintaining efficient routing in terms of total delivery time and travel distance. Our findings illustrate that commercial EV fleets can be leveraged as mobile assets to support local energy sustainability , providing a viable pathway to simultaneously decarbonize logistics and enhance grid stability.

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