A Simulation Model For Bio-Inspired Charging Strategies For Electric Vehicles In Industrial Areas

Berry Gerrits*, Martijn Mes, Robert Andringa

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

This paper presents an open-source agent-based simulation model to study bio-inspired charging policies for local sustainable energy systems in an industrial setting where electric vehicles (EVs) perform transportation jobs. Within this context, we focus on a system that allows to control the charging-schemes of individual EVs. To this end, we develop an agent-based simulation model in NetLogo. We present and implement a bio-inspired approach based on the foraging behavior of honeybees and our approach results in simple, yet effective decision-making logic. Our approach provides the necessary parameters to control and balance sustainable energy systems in terms of EV productivity and the consumption of locally generated energy. Our simulation results look promising: the balance between EV productivity and the use of sustainable energy can be efficiently tweaked in a predictable manner using the parameters and thresholds of the model, yielding close-to-optimal performance.

Original languageEnglish
Title of host publication2023 Winter Simulation Conference, WSC 2023
PublisherIEEE
Pages197-208
Number of pages12
ISBN (Electronic)9798350369663
DOIs
Publication statusPublished - 31 Jan 2024
EventWinter Simulation Conference, WSC 2023 - San Antonio, United States
Duration: 10 Dec 202313 Dec 2023

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Conference

ConferenceWinter Simulation Conference, WSC 2023
Abbreviated titleWSC 2023
Country/TerritoryUnited States
CitySan Antonio
Period10/12/2313/12/23

Keywords

  • 2024 OA procedure

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