Global greenhouse gas emissions must be reduced to meet the targets of the Paris Climate Accords. This study quantifies the potential energy cost savings of a holistic disposition approach for mixed-electrified heavy-duty truck fleets. Electrifying heavy-duty trucks reduces energy costs compared to traditional diesel-powered baselines. On-site energy generation further decreases electrification expenses. Bidirectional vehicle-to-grid participation also contributes to lowering energy costs. A mixed-integer linear programming optimization algorithm has been developed to incorporate these three approaches into the fleet’s disposition decisions. Real-world data have been utilized, including commercial order datasets, diesel prices, on-site-generated electrical energy prices, and vehicle-to-grid prices. Cost savings start at an average of 17% for small fleets with limited electrification and unfavorable price scenarios. However, they can reach net revenue generation for large fleets with high electrification and favorable price scenarios. A daily surplus of fleet energy costs can be achieved, with vehicle-to-grid revenues surpassing the costs of energy consumed. Ensuring battery electric heavy-duty trucks are available during high-revenue periods and operating during low-revenue times can lower overall fleet energy costs for commercial operators and improve power grid stability. By turning energy costs into net surpluses, this approach provides a financial incentive that could accelerate the transition to greenhouse-gas-neutral transport.

Fleet electrification is essential for achieving the EU’s heavy-duty vehicle greenhouse gas emission reduction targets, aiming for a 90% reduction by 2040 versus 2019. However, transition from internal combustion engine to battery electric trucks often requires adapting both fleet and depot infrastructure, presenting significant economic challenges for logistics companies. Logistics Infrastructure and Fleet Transformation (LIFT) is an open-source Python tool supporting planning for heavy-duty vehicle fleet electrification and the depot energy system’s accompanying upgrade. Through a web-based graphical user interface, users define both the status quo of fleet and depot as well as an electrification/expansion scenario. An energy system simulation backend then calculates key techno-economic KPIs for both scenarios and compares them, enabling quick insights into the effects of intended measures and allowing for preliminary expansion planning of the depot extension to be derived. Optional direct access to the backend ensures scalability. This publication presents both LIFT’s setup and its application in three illustrative hypothetical freight forwarding depot electrification examples.