A validated agent-based model for stress testing charging infrastructure utilization
Deployment and management of environmental infrastructures, such as charging infrastructure for Electric Vehicles (EV), is a challenging task. For policy makers, it is particularly difficult to estimate the capacity of current deployed public charging infrastructure for a given EV user population. While data analysis of charging data has shown added value for monitoring EV systems, it is not valid to linearly extrapolate charging infrastructure performance when increasing population size. The authors developed a data-driven agent-based model that can explore future scenarios to identify non-trivial dynamics that may be caused by EV user interaction, such as competition or collaboration, and that may affect performance metrics. The authors validated the model by comparing EV user activity patterns in time and space. The authors performed stress tests on the 4 largest cities the Netherlands to explore the capacity of the existing charging network. The authors' results demonstrate that (i) a non-linear relation exists between system utilization and inconvenience even at the base case; (ii) from 2.5x current population, the occupancy of non-habitual charging increases at the expense of habitual users, leading to an expected decline of occupancy for habitual users; and (iii) from a ratio of 0.6 non-habitual users to habitual users competition effects intensify. For the infrastructure to which the stress test is applied, a ratio of approximately 0.6 may indicate a maximum allowed ratio that balances performance with inconvenience. For policy makers, this implies that when they see diminishing marginal performance of KPIs in their monitoring reports, they should be aware of potential exponential increase of inconvenience for EV users.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
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Supplemental Notes:
- © 2022 Jurjen R. Helmus et al. Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
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Authors:
- Helmus, Jurjen R
- Lees, Michael H
- van den Hoed, Robert
- Publication Date: 2022-5
Language
- English
Media Info
- Media Type: Web
- Features: Appendices; Figures; References; Tables;
- Pagination: pp 237-262
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Serial:
- Transportation Research Part A: Policy and Practice
- Volume: 159
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0965-8564
- Serial URL: http://www.sciencedirect.com/science/journal/09658564
Subject/Index Terms
- TRT Terms: Electric vehicle charging; Infrastructure; Metrics (Quantitative assessment); Monitoring; Multi-agent systems; Policy; Simulation
- Subject Areas: Energy; Highways; Planning and Forecasting; Terminals and Facilities;
Filing Info
- Accession Number: 01842938
- Record Type: Publication
- Files: TRIS
- Created Date: Apr 21 2022 11:59AM