Highlight An ABMS study to evaluate strategies to deploy commercial electric LGV. The model was developed based on empirical home delivery data in Manchester. We investigate the relationship between charging power and the service level. We investigate strategies to charge the LGVs to maximize service level. We propose a tool to analyse robust mix of charging infrastructure and strategies.
Abstract This paper presents an agent-based simulation study aimed at evaluating the impact of different charging strategies on the performance of home grocery delivery operation using electric vans. In our previous work we established the quantity of orders that can be delivered using electric vans; in this paper we focus on the punctuality of the delivery. We present a baseline agent-based model imitating the operations of a real-world retailer. We then introduce electric vans into our model in order to ascertain how charging power and charging strategy influence the retailer’s operations. Even though electric vans cannot match the performance of diesel vehicles using the same fleet size, our simulation experiments suggest that, by considering the quantity of orders and the geographical distribution of its customers, an operator can determine a suitable charging strategy that can minimise late delivery. Additionally, by employing a suitable charging strategy, an operator might avoid making unnecessary investments and reduce the barriers for electric vehicle adoption.
Analysing charging strategies for electric LGV in grocery delivery operation using agent-based modelling: An initial case study in the United Kingdom
2021-02-07
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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