Assessing the impact of EHGV charging on distribution network infrastructure

The decarbonisation of Heavy Goods Vehicles (HGVs) is essential to reduce carbon emissions in the transport sector. Battery electric HGVs (eHGVs) are one potentially viable solution, with numerous successful trials in recent years supporting their viability. However, challenges remain due to the large battery capacities of these vehicles, grid capacity limitations and the need for charging infrastructure deployment. Existing research has primarily focused on infrastructure at service stations for long-haul haulage with research on urban-focused HGV activities and depot charging comparatively scarce. Therefore, this study assesses the impact of installing eHGV chargers at depot sites across Scotland on the electrical distribution network. Using spatial mapping, the study associates existing depot sites with their primary substations and applies a probabilistic methodology to distribute chargers across depots based on fleet size under different future scenarios. The impact of this new demand on substation loading is then evaluated. The findings indicate that significant upgrades to network infrastructure will be necessary to sup port the high-power demands of eHGVs, particularly at substations near major depots. The study also emphasises the importance of coordinated planning among fleet operators, policymakers and distribution network operators to address these challenges.

Authors

Institutions

Publication Details

Journal
IET conference proceedings.
Published
2025-10-14
DOI
https://doi.org/10.1049/icp.2025.1907
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the impact of EHGV charging on distribution network infrastructure

Connor McGarry, L. Hunter, James Dixon, Stuart Galloway
IET conference proceedings.
Electric Vehicles and Infrastructure
article

Assessing the impact of EHGV charging on distribution network infrastructure

Connor McGarry, L. Hunter, James Dixon, Stuart Galloway
article en

Abstract

The decarbonisation of Heavy Goods Vehicles (HGVs) is essential to reduce carbon emissions in the transport sector. Battery electric HGVs (eHGVs) are one potentially viable solution, with numerous successful trials in recent years supporting their viability. However, challenges remain due to the large battery capacities of these vehicles, grid capacity limitations and the need for charging infrastructure deployment. Existing research has primarily focused on infrastructure at service stations for long-haul haulage with research on urban-focused HGV activities and depot charging comparatively scarce. Therefore, this study assesses the impact of installing eHGV chargers at depot sites across Scotland on the electrical distribution network. Using spatial mapping, the study associates existing depot sites with their primary substations and applies a probabilistic methodology to distribute chargers across depots based on fleet size under different future scenarios. The impact of this new demand on substation loading is then evaluated. The findings indicate that significant upgrades to network infrastructure will be necessary to sup port the high-power demands of eHGVs, particularly at substations near major depots. The study also emphasises the importance of coordinated planning among fleet operators, policymakers and distribution network operators to address these challenges.

IET conference proceedings.Vol. 2025(14)
University of Strathclyde (GB)
Openalex Percentile: Top 71%
Electric Vehicles and Infrastructure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.