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Grid Capacity Impact from the Charging of Electrified Long-Haul Trucks

Jansson, Alice LU ; Ingelstrom, Mattias LU ; Samuelsson, Olof LU and Marquez-Fernandez, Francisco J. LU orcid (2025) 2025 IEEE Texas Power and Energy Conference, TPEC 2025 In 2025 IEEE Texas Power and Energy Conference, TPEC 2025
Abstract

The introduction of electric heavy trucks will lead to new charging power requirements on the power grid. This study examines how much charging power is required for the public fast charging of a fully electrified long-haul truck fleet. Probabilistic truck charging profiles are created using agent-based simulations, based on fully representative long-haul goods transport data from the study area. The modeled charging loads are introduced in probabilistic power grid simulations to examine the impact of truck charging on the grid capacity. The grid model used is the actual scale 1: 1 grid planning model of the transmission and sub-transmission grid, provided by the grid owner in the study area. A probabilistic load flow analysis is... (More)

The introduction of electric heavy trucks will lead to new charging power requirements on the power grid. This study examines how much charging power is required for the public fast charging of a fully electrified long-haul truck fleet. Probabilistic truck charging profiles are created using agent-based simulations, based on fully representative long-haul goods transport data from the study area. The modeled charging loads are introduced in probabilistic power grid simulations to examine the impact of truck charging on the grid capacity. The grid model used is the actual scale 1: 1 grid planning model of the transmission and sub-transmission grid, provided by the grid owner in the study area. A probabilistic load flow analysis is performed to examine the impact of the required truck charging on the loading of primary substation transformers and power lines. The results show that the aggregated truck charging leads to overloads in 6 out of the 18 substation transformers (135/22 or 135/11 kV) which were feeding the truck charging. The highest risk of overload in a single transformer is 3.4 %.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Capacity planning, charging stations, electric vehicles (EV), load flow, Monte Carlo methods, power distribution, road vehicles
host publication
2025 IEEE Texas Power and Energy Conference, TPEC 2025
series title
2025 IEEE Texas Power and Energy Conference, TPEC 2025
pages
6 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
2025 IEEE Texas Power and Energy Conference, TPEC 2025
conference location
College Station, United States
conference dates
2025-02-10 - 2025-02-11
external identifiers
  • scopus:105000947760
ISBN
9798331541125
DOI
10.1109/TPEC63981.2025.10906869
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2025 IEEE.
id
99ea0aaa-97c1-44a2-8e4f-288a86589a36
date added to LUP
2025-08-02 19:08:23
date last changed
2025-08-14 11:14:56
@inproceedings{99ea0aaa-97c1-44a2-8e4f-288a86589a36,
  abstract     = {{<p>The introduction of electric heavy trucks will lead to new charging power requirements on the power grid. This study examines how much charging power is required for the public fast charging of a fully electrified long-haul truck fleet. Probabilistic truck charging profiles are created using agent-based simulations, based on fully representative long-haul goods transport data from the study area. The modeled charging loads are introduced in probabilistic power grid simulations to examine the impact of truck charging on the grid capacity. The grid model used is the actual scale 1: 1 grid planning model of the transmission and sub-transmission grid, provided by the grid owner in the study area. A probabilistic load flow analysis is performed to examine the impact of the required truck charging on the loading of primary substation transformers and power lines. The results show that the aggregated truck charging leads to overloads in 6 out of the 18 substation transformers (135/22 or 135/11 kV) which were feeding the truck charging. The highest risk of overload in a single transformer is 3.4 %.</p>}},
  author       = {{Jansson, Alice and Ingelstrom, Mattias and Samuelsson, Olof and Marquez-Fernandez, Francisco J.}},
  booktitle    = {{2025 IEEE Texas Power and Energy Conference, TPEC 2025}},
  isbn         = {{9798331541125}},
  keywords     = {{Capacity planning; charging stations; electric vehicles (EV); load flow; Monte Carlo methods; power distribution; road vehicles}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{2025 IEEE Texas Power and Energy Conference, TPEC 2025}},
  title        = {{Grid Capacity Impact from the Charging of Electrified Long-Haul Trucks}},
  url          = {{http://dx.doi.org/10.1109/TPEC63981.2025.10906869}},
  doi          = {{10.1109/TPEC63981.2025.10906869}},
  year         = {{2025}},
}