Spatiotemporal Bi-Level Charging Optimization of Electric Taxi Considering Scheduling Feasibility

Sheng TIAN , Leyang LI

›› 2025, Vol. 19 ›› Issue (2) : 57 -67.

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›› 2025, Vol. 19 ›› Issue (2) : 57 -67. DOI: 10.13648/j.cnki.issn1674-0629.2025.02.007
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Spatiotemporal Bi-Level Charging Optimization of Electric Taxi Considering Scheduling Feasibility

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Abstract

With the continuous expansion of electric taxi fleets in various cities, their large-scale and unregulated charging behaviors will not only aggravate the fluctuation of the power grid load curve, threaten the stability and security of the power grid, but also reduce the equipment utilization rates of remote charging stations. Therefore, an electric taxi orderly charging guidance system is established based on the information cooperation of “vehicle-station-network”, which proposes a spatiotemporal bi-level charging optimization of electric taxi considering the feasibility of user participation in scheduling. In the temporal level model, a multi-objective optimization model is established based on minimizing the peak-valley difference, standard deviation and the charging cost of users. This model optimizes the charging time load of electric taxis in advance and reserves charging time windows for each user. In the spatial level model, real-time scheduling of the spatial load of electric taxi charging is carried out with the objectives of balancing the average utilization rate of each charging station and minimizing users′ charging time cost, in order to allocate the optimal charging station for each user. Finally, the effectiveness of the proposed optimization strategy is verified through a case simulation, demonstrating its ability to balance the interests of power distribution network, charging station operators and electric taxi users.

Keywords

electric taxi / multi-objective optimization / spatiotemporal load scheduling / scheduling feasibility / charging guidance

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Sheng TIAN,Leyang LI. Spatiotemporal Bi-Level Charging Optimization of Electric Taxi Considering Scheduling Feasibility. 2025, 19(2): 57-67 DOI:10.13648/j.cnki.issn1674-0629.2025.02.007

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Funding

the National Key Research and Development Program(2021YFB2501104)

the Natural Science Foundation of Guangdong Province(2021A1515011587)

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