Proposed charging scheduling approach reduces queuing time in electric vehicles, highlighting grid load balancing benefits.
The widespread adoption of electric vehicles intensifies the spatiotemporal mismatch between charging demand and station capacity, leading to operational inefficiencies. This paper proposes a cooperative charging scheduling strategy based on a novel queuing model that integrates virtual charging piles and state variables to accurately estimate queuing time, overcoming the limitations of conventional methods. A bi-level optimization model is established to coordinate grid load balancing and station-level queue management. An adaptive large-neighborhood search algorithm combining heuristic rules with mathematical solving is developed for efficient solution. Numerical experiments demonstrate that the proposed strategy outperforms existing approaches by significantly increasing fulfilled charging demand and reducing queuing times with only minimal travel distance increase. Analysis further reveals a computational performance trade-off related to scheduling frequency, providing critical insights for practical implementation.
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Wang et al. (2025) studied this question.
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