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A GIS MILP framework for electric vehicle charging station placement and optimization : a case study in Eindhoven, Netherlands
ID
Katontoka, Moses
(
Author
),
ID
Kanellopoulos, Argyris
(
Author
),
ID
Orsi, Francesco
(
Author
),
ID
Sirnik, Igor
(
Author
)
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MD5: 06110CB0846568DF0DF5A43A070D5668
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https://www.sciencedirect.com/science/article/pii/S0198971526000591
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Abstract
Electric vehicle charging station planning requires decisions that account not only for spatial accessibility, but also for investment costs, charging demand, renewable energy availability, grid energy use, and storage requirements. Existing EV charging station location studies often address these components separately, limiting their ability to evaluate trade-offs between spatial suitability and system-level operation. This study develops an integrated GIS-MILP framework for electric vehicle charging station planning. The framework combines GIS-based spatial suitability analysis with a multi-objective mixed-integer linear programming model to optimize charging station location, energy flows, travel time, investment costs, grid energy use, battery storage, and vehicle-to-grid interactions. The approach is applied to Eindhoven, the Netherlands, using spatial indicators, seasonal solar generation profiles, charging demand, candidate locations, and infrastructure cost parameters. Results show that integrating spatial suitability with operational optimization supports the identification of accessible charging station locations while accounting for renewable variability, storage capacity, and grid energy requirements. The inclusion of PV, battery storage, and V2G enables the model to evaluate how local renewable generation and bidirectional energy flows may contribute to charging infrastructure planning, although their contribution depends on modeled assumptions and system conditions. The proposed framework provides a transferable decision-support approach for cities seeking to plan EV charging infrastructure under spatial, economic, and energy-system constraints.
Language:
English
Keywords:
spatial decision support
,
multi-objective optimization
,
vehicle-to-grid
,
battery energy storage systems
,
renewable integration
,
urban energy planning
,
sustainable mobility
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FGG - Faculty of Civil and Geodetic Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2026
Number of pages:
16 str.
Numbering:
Vol. 128, art. 102457
PID:
20.500.12556/RUL-182718
UDC:
621.313.2:502.131.1(492)
ISSN on article:
1873-7587
DOI:
10.1016/j.compenvurbsys.2026.102457
COBISS.SI-ID:
278905347
Publication date in RUL:
21.05.2026
Views:
364
Downloads:
287
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Record is a part of a journal
Title:
Computers, environment and urban systems
Publisher:
Elsevier
ISSN:
1873-7587
COBISS.SI-ID:
175280387
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
prostorska podpora odločanju
,
urbano energetsko načrtovanje
,
večkriterijska optimizacija
,
V2G
,
baterijski sistemi za shranjevanje energije
,
integracija obnovljivih virov energije
,
trajnostna mobilnost
Projects
Funder:
NWO - Dutch Research Council’s Knowledge
Funding programme:
Flexible Energy Communities (FlexECs) project
Project number:
KICH.ED03.20.012
Name:
Energy transition as a socio-technical challenge
Funder:
KIC - Innovation Covenant programme
Funding programme:
Flexible Energy Communities (FlexECs) project
Project number:
KICH.ED03.20.012
Name:
Energy transition as a socio-technical challenge
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
P2-0406
Name:
Opazovanje Zemlje in geoinformatika
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