Coordinating electric vehicle flow distribution and charger allocation by joint optimization
Coordinating electric vehicle flow distribution and charger allocation by joint optimization
A two-stage stochastic programming model is established to minimize EV's expected total journey time under stochastic traffic conditions, by jointly optimizing the allocation of chargers and the distribution of EV flows. Based on sample average approximation, a feasible deterministic equivalent of the original stochastic problem is obtained. Then, a hybrid solution method, composing of a Tabu-based search and sequential quadratic programming (SQP), is proposed. The Tabu heuristic manages the charger allocation problem, where each solution candidate undergoes a second-stage EV flow optimization. SQP is applied to optimially distribute the EV flows, which is proved to be a convex problem. Extensive simulations are carried out using the eastern Massachusetts highway network. Results show that the proposed algorithm outperforms existing approaches. Additionally, the two-stage model designates charging resource sufficiency by estimating a lower bound for the number of chargers to allocate, which in practice helps to prevent over-investment on charging resources.
Electric vehicle (EV), charger allocation, convex optimization, traffic flow distribution, two-stage stochastic programming
Bi, Xiaowen
6f314c97-3283-4439-a3ea-3444d4f70cd7
Chipperfield, Andrew
524269cd-5f30-4356-92d4-891c14c09340
Tang, Wallace K.S.
a6174fc4-3efe-4e99-8858-57d213f9f9e3
December 2021
Bi, Xiaowen
6f314c97-3283-4439-a3ea-3444d4f70cd7
Chipperfield, Andrew
524269cd-5f30-4356-92d4-891c14c09340
Tang, Wallace K.S.
a6174fc4-3efe-4e99-8858-57d213f9f9e3
Bi, Xiaowen, Chipperfield, Andrew and Tang, Wallace K.S.
(2021)
Coordinating electric vehicle flow distribution and charger allocation by joint optimization.
IEEE Transactions on Industrial Informatics.
(doi:10.1109/TII.2021.3059288).
Abstract
A two-stage stochastic programming model is established to minimize EV's expected total journey time under stochastic traffic conditions, by jointly optimizing the allocation of chargers and the distribution of EV flows. Based on sample average approximation, a feasible deterministic equivalent of the original stochastic problem is obtained. Then, a hybrid solution method, composing of a Tabu-based search and sequential quadratic programming (SQP), is proposed. The Tabu heuristic manages the charger allocation problem, where each solution candidate undergoes a second-stage EV flow optimization. SQP is applied to optimially distribute the EV flows, which is proved to be a convex problem. Extensive simulations are carried out using the eastern Massachusetts highway network. Results show that the proposed algorithm outperforms existing approaches. Additionally, the two-stage model designates charging resource sufficiency by estimating a lower bound for the number of chargers to allocate, which in practice helps to prevent over-investment on charging resources.
Text
TII_R1_v3
- Accepted Manuscript
More information
Accepted/In Press date: 7 February 2021
e-pub ahead of print date: 15 February 2021
Published date: December 2021
Additional Information:
Publisher Copyright:
IEEE
Keywords:
Electric vehicle (EV), charger allocation, convex optimization, traffic flow distribution, two-stage stochastic programming
Identifiers
Local EPrints ID: 447508
URI: http://eprints.soton.ac.uk/id/eprint/447508
ISSN: 1941-0050
PURE UUID: cdb9f1d8-e157-44aa-bf86-f0d392b36ddc
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Date deposited: 12 Mar 2021 17:35
Last modified: 17 Mar 2024 02:56
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Contributors
Author:
Xiaowen Bi
Author:
Wallace K.S. Tang
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