Optimizing the deployment of charging systems on an expressway network considering the construction time sequence and the dynamic charging demand

YANG Yang; ZHANG Tianyu; ZHU Yuting; YAO Enjian

doi:10.16511/j.cnki.qhdxxb.2022.26.017

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Journal of Tsinghua University(Science and Technology) ›› 2022, Vol. 62 ›› Issue (7) : 1163-1177,1219. DOI: 10.16511/j.cnki.qhdxxb.2022.26.017

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Optimizing the deployment of charging systems on an expressway network considering the construction time sequence and the dynamic charging demand

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Abstract

A bi-level optimization model was developed for planning charging facility deployment on an intercity highway network. The model balances the variable charging demand and the construction time sequence. The lower model is based on a dynamic traffic assignment model. The spatial-temporal distribution of the charging demand at equilibrium was obtained from simulations of multi-user driving and charging behavior. The upper model optimizes the charging station's locations and capacities using construction time sequence and level of service (LOS) constraints to minimize the operator investment. The model is then used to analyze the intercity highway network between Jinan and Qingdao in the Shandong Peninsula urban agglomeration. The model provides reliable estimates of the real-time charging system LOS and a satisfactory layout based on the user chargig preferences, network traffic conditions, and facility conditions. The layout was then analysed using forward and reverse construction time sequences. The results show that for the same LOS constraint, long-term deployment should consider future energy demands and the planners should use the reverse construction time sequence method.

Key words

traffic engineering / charging infrastructure / bi-level optimal deployment / electric vehicles / dynamic traffic assignment / construction time sequence

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YANG Yang, ZHANG Tianyu, ZHU Yuting, YAO Enjian. Optimizing the deployment of charging systems on an expressway network considering the construction time sequence and the dynamic charging demand[J]. Journal of Tsinghua University(Science and Technology). 2022, 62(7): 1163-1177,1219 https://doi.org/10.16511/j.cnki.qhdxxb.2022.26.017

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