Application of a Genetic Algorithm With a Fuzzy Objective Function for Optimized Siting of Electric Vehicle Charging Devices in Urban Road Networks
Minimization of negative environmental impact of transport cannot be pursued through mobility limiting, but rather through efficient utilization of natural resources. Some of the ways to reduce harmful pollution and noise include increasing the use of electric energy for transportation and developing electromobility. However, municipalities face difficult decisions connected with the siting of charging stations, for example, budget limitations are an important factor. The presented method allows for selecting a subset of existing parking lots where the charging devices will be sited. As the inputs, only easily accessible data is required. Applying a genetic algorithm combined with fuzzy logic and the Pareto front analysis, one could establish a set of optimal solutions for multiple pre-defined restrictive and partially contradictory criteria. The method has been discussed using a real example of a medium-sized city in southern Poland. Its results have also made it possible to verify whether a budget required for the planned investment is substantiated.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
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Supplemental Notes:
- Copyright © 2022, IEEE.
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Authors:
- Król, Aleksander
- Sierpiński, Grzegorz
- Publication Date: 2022-7
Language
- English
Media Info
- Media Type: Web
- Pagination: pp 8680-8691
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Serial:
- IEEE Transactions on Intelligent Transportation Systems
- Volume: 23
- Issue Number: 7
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 1524-9050
- Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979
Subject/Index Terms
- TRT Terms: Electric vehicle charging; Location; Urban highways
- Geographic Terms: Poland
- Subject Areas: Energy; Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01885392
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 20 2023 10:17AM