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Agent-Based Modeling of Urban Residential Electricity Demand Incorporating EV Charging Behavior

Alaliyat, Saleh and Oucheikh, Rachid LU (2025) 39th ECMS International Conference on Modelling and Simulation, ECMS 2025 In Proceedings - European Council for Modelling and Simulation, ECMS 2025-June. p.455-461
Abstract

By 2050, electric vehicles (EVs) are expected to be 40% of all cars on the road1. In some countries like Norway, more than 90% of the new cars sold are electric2. This rise in EVs presents challenges to the current electricity infrastructure to meet this rapid increase in electricity demand. In this study, we simulate urban residential electricity demand using an agent-based model to investigate the effects of EVs' charging behavior on the electricity demand profile and how using smart charging behavior helps in reducing the peak demand pressure. The simulation results of different scenarios show how it can be effective to schedule the charging time in the off-peak.

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
Agent-Based Modeling, Charging Behaviour, Electricity Demand, EV, Simulation
host publication
Proceedings of the 39th ECMS International Conference on Modelling and Simulation, ECMS 2025
series title
Proceedings - European Council for Modelling and Simulation, ECMS
editor
Scarpa, Marco ; Cavalieri, Salvatore ; Serrano, Salvatore and De Vita, Fabrizio
volume
2025-June
pages
7 pages
publisher
European Council for Modelling and Simulation
conference name
39th ECMS International Conference on Modelling and Simulation, ECMS 2025
conference location
Catania, Italy
conference dates
2025-06-24 - 2025-06-27
external identifiers
  • scopus:105010578101
ISSN
2522-2414
ISBN
9783937436869
DOI
10.7148/2025-0455
language
English
LU publication?
yes
id
c6ebf6c4-0247-41e7-82c3-0ed850415681
date added to LUP
2026-01-20 11:13:07
date last changed
2026-01-21 08:43:58
@inproceedings{c6ebf6c4-0247-41e7-82c3-0ed850415681,
  abstract     = {{<p>By 2050, electric vehicles (EVs) are expected to be 40% of all cars on the road<sup>1</sup>. In some countries like Norway, more than 90% of the new cars sold are electric<sup>2</sup>. This rise in EVs presents challenges to the current electricity infrastructure to meet this rapid increase in electricity demand. In this study, we simulate urban residential electricity demand using an agent-based model to investigate the effects of EVs' charging behavior on the electricity demand profile and how using smart charging behavior helps in reducing the peak demand pressure. The simulation results of different scenarios show how it can be effective to schedule the charging time in the off-peak.</p>}},
  author       = {{Alaliyat, Saleh and Oucheikh, Rachid}},
  booktitle    = {{Proceedings of the 39th ECMS International Conference on Modelling and Simulation, ECMS 2025}},
  editor       = {{Scarpa, Marco and Cavalieri, Salvatore and Serrano, Salvatore and De Vita, Fabrizio}},
  isbn         = {{9783937436869}},
  issn         = {{2522-2414}},
  keywords     = {{Agent-Based Modeling; Charging Behaviour; Electricity Demand; EV; Simulation}},
  language     = {{eng}},
  pages        = {{455--461}},
  publisher    = {{European Council for Modelling and Simulation}},
  series       = {{Proceedings - European Council for Modelling and Simulation, ECMS}},
  title        = {{Agent-Based Modeling of Urban Residential Electricity Demand Incorporating EV Charging Behavior}},
  url          = {{http://dx.doi.org/10.7148/2025-0455}},
  doi          = {{10.7148/2025-0455}},
  volume       = {{2025-June}},
  year         = {{2025}},
}