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Power demand and queuing at heavy truck semi-public charging points: forestry transport as a case study
Skogforsk, Uppsala Science Park, 75183, Uppsala, Sweden.
KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. Skogforsk, Uppsala Science Park, 75183, Uppsala, Sweden.ORCID iD: 0000-0003-2011-6273
2025 (English)In: European Transport Research Review, ISSN 1867-0717, E-ISSN 1866-8887, Vol. 17, no 1, article id 47Article in journal (Refereed) Published
Abstract [en]

Electrification of heavy-duty transport will play a key role in achieving the EU climate goals to cut CO2 emission. To enable electrification, an extensive network of charging infrastructure will be needed. This paper takes the perspective of the charging station. The Swedish forestry industry is used as a case. The study explores the relation between transport work, truck specifications, and charging infrastructure setup. A stochastic, discrete-event model is developed, simulating the power demand and queue situation when charging electric heavy roundwood trucks at the receiving industries. The simulations show that with 600 kWh available energy in the battery, 71–83% of the incoming trucks or 48–71% of the incoming transport work (measured in tonne-km) can be electrified. The variations depend primarily on differences in average transport lengths. With unlimited number of chargers, the peak power needed is 6.2–6.6 MW, but there are large variations in power demand over the day. If the number of chargers is limited, the peak power is also limited, but there might instead be queues. However, if the number of chargers is selected appropriately or the truck inflow is actively and efficiently planned, the peak power can be reduced to around a third while still keep average queue time on acceptable levels. Reducing peak power is important, as it reduces investment costs, and limiting the capacity cost for the grid connection.

Place, publisher, year, edition, pages
Springer Nature , 2025. Vol. 17, no 1, article id 47
Keywords [en]
Charging, Charging power, Discrete-event simulation, Electric truck, Forestry transport, Modeling, Systems analyses
National Category
Transport Systems and Logistics Energy Systems Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-372040DOI: 10.1186/s12544-025-00744-7ISI: 001585580500001Scopus ID: 2-s2.0-105017825353OAI: oai:DiVA.org:kth-372040DiVA, id: diva2:2011612
Note

QC 20251105

Available from: 2025-11-05 Created: 2025-11-05 Last updated: 2025-11-05Bibliographically approved

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Pernestål Brenden, Anna

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