Scientists in Japan have developed a model that predicts surplus PV generation and creates a route for optimized charging of vehicles of electric delivery. They defined their work as a “practical blueprint for logistics operators.”
Researchers from Japanese Waseda University have developed a new model that optimizes the route of electric delivery vehicles (EDVs) to maximize the local PV surplus use.
For this purpose, the Academics have designed a new electric vehicle routering problem (EVRP) that uses any forest realization model to predict where and when the surplus solar energy will be available in the vicinity of charging stations in the next day.
“Our work offers a practical blueprint for logistics operators to actively reduce the carbon emissions by strategically charging their EV -Vlooten with spatial local surplus PV power,” said researcher Ryoji Miyabe PV -Magazine. “Crucially, our model isn’t limited to a company’s own depot. It dynamically incorporates Public Charging Stations Into Delivery Routes, Turning Evs Into Mobile Assets That Can Absorb Excess Solar Power Acreaty A Winwinies A Winwin’s A Win-Wwinnies A Winwinnies A Win-Wwin. Footprint, while also promotion the local production and consumption or renewable energy. ”
The proposed model focuses on mid-mile route-based delivery activities, in which EDV’s goods from logistics depots transport to stores, using a small fleet of vehicles. For charging, EDV’s have access to Fast Chargers (FCS) with an output of 50 kW, either on the road or in the operator’s depot. With the given ones, the operator is asked to fill in a few parameters, such as customer locations of the next day and the required service time windows.
In the next step, a random forest registration model uses smart meter data and weather forecasts to predict the timing and location of PV surplus the next day. Subsequently, it formalizes a mixed-integer linear programming (MILP) problem with the purpose of minimizing CO2 emissions, while adhering to some limitations. Among these are customer, vehicle, timing and loading restrictions. It then delivers the exact mission plan for delivery, including the customer list, route and loading time and locations.
Image: Waseda University, Journal of Energy Storage, CC by 4.0
To demonstrate the effectiveness of the new approach, the Numeric team simulated a case study using Real-World data from the city of Utsunomiya in Central Japan. The operation included a delivery service with three Mitsubishi Fuso New Evanter EVs, each equipped with a 41 kWh battery and a range of 80 km.
The simulation included one depot, 14-16 customers and five charging stations in the city. A week of simulations was performed in each season, with two services per day, which resulted in 56 cases.
For compression, the proposed carbon -poor EVRP was measured against a normal EVRP and a normal VRP. “In the normal VRP method, no EN-Route chargates are carried out and only charged place at the depot after completion of the delivery activities. Charging after completion of the operations is supposed to start immediately upon return to the depot, and the amount of accusations of the electricity that is submitted during travel.
The analysis showed that the proposed carbon-poor EVRP achieved considerable CO2 emission reductions, on average 16.6% lower than the regular VRP (30.8 versus 25.7 kg-CO2/case) and 21.4% lower than the regular EVRP (32.7 versus 25.7 kg-CO2/case). In comparison with the ordinary VRP, the proposed method reduced the emissions by 22.7%, 17.9%, 19.6% and 7.2% in spring, summer, autumn and winter respectively. The most substantial CO2 reduction was measured in the early shift of 17.5.2023, with the new method CO2 emissions reduced by 66.1% compared to the VRP.
“The most striking result was to discover how crucial charging strategy is for the low -carbon – even more than minimizing the travel distance,” concluded Miyabe. “Our method sometimes selects routes that are longer, which of course increases energy consumption. However, the most important finding is that by the right amount in the right place and the right moment to be charged – specifically aimed at locations with abundant excess PV power – the CO2 savings are considerable and by far the extra energy consumption.”
They presented their research in ‘Low-carbon routing and charging planning for electric trucks using local surplus solar energy“Which was recently published in the Journal of Energy Storage.
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