A complementarity equilibrium model for electric vehicles with charging
This paper presents a complementarity equilibrium model for electric vehicles (EVs). Under the equilibrium conditions, each EV takes the path that is shortest and does not violate the driving range. When the driving range has to be violated, the EVs are allowed to choose a path with a charging stati...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2017-12-01
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| Series: | International Journal of Transportation Science and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2046043017300205 |
| _version_ | 1797727854856765440 |
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| author | Sina Bahrami Hedayat Z. Aashtiani Mehdi Nourinejad Matthew J. Roorda |
| author_facet | Sina Bahrami Hedayat Z. Aashtiani Mehdi Nourinejad Matthew J. Roorda |
| author_sort | Sina Bahrami |
| collection | DOAJ |
| description | This paper presents a complementarity equilibrium model for electric vehicles (EVs). Under the equilibrium conditions, each EV takes the path that is shortest and does not violate the driving range. When the driving range has to be violated, the EVs are allowed to choose a path with a charging station to extend their driving range. To find the shortest such path, a constrained shortest path problem with replenishment (CSPP with replenishment) is formulated that considers the driving range limit of EVs. The CSPP is solved with a label-correcting algorithm with two additional steps that substantially reduce the computation time and the required memory. The first procedure is a pruning technique that eliminates exploring branches (of an enumeration tree) that can no longer become incumbent and the second procedure is an indexing technique that works as a pointer for navigating the generated (enumeration) tree when it becomes too large. Numerical experiments on a number of networks show a substantially lower computation time compared to existing algorithms and the results provide several insights into the driving patterns of EVs. When charging time is increased, the EVs shift to paths that have a longer travel time but a shorter distance. Hence, the total network distance decreases but the total network travel time increases. We also show that unregulated expansion of the charging infrastructure can actually increase the total network travel time due to the presence of Braess’ paradox. |
| first_indexed | 2024-03-12T11:05:31Z |
| format | Article |
| id | doaj.art-75ee428b208f41deab19e310233d2afc |
| institution | Directory Open Access Journal |
| issn | 2046-0430 |
| language | English |
| last_indexed | 2024-03-12T11:05:31Z |
| publishDate | 2017-12-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | International Journal of Transportation Science and Technology |
| spelling | doaj.art-75ee428b208f41deab19e310233d2afc2023-09-02T03:57:44ZengKeAi Communications Co., Ltd.International Journal of Transportation Science and Technology2046-04302017-12-016425527110.1016/j.ijtst.2017.05.007A complementarity equilibrium model for electric vehicles with chargingSina Bahrami0Hedayat Z. Aashtiani1Mehdi Nourinejad2Matthew J. Roorda3Department of Civil Engineering, University of Toronto, Toronto, CanadaDepartment of Civil Engineering, Sharif University of Technology, Tehran, IranDepartment of Civil Engineering, University of Toronto, Toronto, CanadaDepartment of Civil Engineering, University of Toronto, Toronto, CanadaThis paper presents a complementarity equilibrium model for electric vehicles (EVs). Under the equilibrium conditions, each EV takes the path that is shortest and does not violate the driving range. When the driving range has to be violated, the EVs are allowed to choose a path with a charging station to extend their driving range. To find the shortest such path, a constrained shortest path problem with replenishment (CSPP with replenishment) is formulated that considers the driving range limit of EVs. The CSPP is solved with a label-correcting algorithm with two additional steps that substantially reduce the computation time and the required memory. The first procedure is a pruning technique that eliminates exploring branches (of an enumeration tree) that can no longer become incumbent and the second procedure is an indexing technique that works as a pointer for navigating the generated (enumeration) tree when it becomes too large. Numerical experiments on a number of networks show a substantially lower computation time compared to existing algorithms and the results provide several insights into the driving patterns of EVs. When charging time is increased, the EVs shift to paths that have a longer travel time but a shorter distance. Hence, the total network distance decreases but the total network travel time increases. We also show that unregulated expansion of the charging infrastructure can actually increase the total network travel time due to the presence of Braess’ paradox.http://www.sciencedirect.com/science/article/pii/S2046043017300205Shortest pathLabel correctingElectric vehiclesCharging stations |
| spellingShingle | Sina Bahrami Hedayat Z. Aashtiani Mehdi Nourinejad Matthew J. Roorda A complementarity equilibrium model for electric vehicles with charging International Journal of Transportation Science and Technology Shortest path Label correcting Electric vehicles Charging stations |
| title | A complementarity equilibrium model for electric vehicles with charging |
| title_full | A complementarity equilibrium model for electric vehicles with charging |
| title_fullStr | A complementarity equilibrium model for electric vehicles with charging |
| title_full_unstemmed | A complementarity equilibrium model for electric vehicles with charging |
| title_short | A complementarity equilibrium model for electric vehicles with charging |
| title_sort | complementarity equilibrium model for electric vehicles with charging |
| topic | Shortest path Label correcting Electric vehicles Charging stations |
| url | http://www.sciencedirect.com/science/article/pii/S2046043017300205 |
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