An Optimisation Method for the Micro-Engineering Upgrade of Urban Electric Vehicle Charging Infrastructure based on Queueing Theory and Graph Theory

Abstract

Addressing key engineering challenges in existing urban areas-such as the mismatch between supply and demand for electric vehicle charging infrastructure, queuing and congestion, and construction-related disturbances to residents-this paper takes Fengrun District in Tangshan City, Hebei Province, as its study area. It proposes a three-tiered, progressive micro-renewal approach comprising ‘macro-queuing theory diagnosis-micro-graph theory optimisation-low-impact construction implementation’, thereby establishing a complete technical closed-loop process ranging from bottleneck identification and precise optimisation to construction implementation. Firstly, by comprehensively utilising KNN, Linear SVM and RBF SVM algorithms, the study systematically identifies user charging behaviour patterns, issues early warnings for facility anomalies and assesses battery health, thereby providing data support for subsequent optimisation. Secondly, an asymmetric double-queue queuing theory model is constructed to conduct a macro-level performance diagnosis of charging stations serving local users in the core area of Fengrun District, accurately identifying and locating bottleneck sites requiring optimisation. Thirdly, by selecting these bottleneck sites and establishing an undirected graph model, the Dijkstra shortest path algorithm is applied to optimise the layout of charging piles and vehicle guidance strategies, thereby achieving a balanced improvement in pile utilisation rates; Furthermore, by integrating key factors affecting user charging costs and construction disruption, we conducted scientific measurement and quantitative analysis to design a low-impact construction plan that integrates Gantt charts, network diagrams and BIM technology, ensuring the efficient implementation of the optimisation plan whilst simultaneously enhancing the user charging experience and the operational efficiency of the construction team. SimPy discrete-event simulation results indicate that, following the application of the method proposed in this paper, the average queuing time at bottleneck sites is reduced by 39.9%-45.5%, users’ average daily charging costs decrease by 15.0%-16.4%. This significantly reduces disruption to surrounding traffic and residents’ daily lives, effectively safeguarding users’ needs for convenient and economical charging whilst significantly improving contractors’ operational efficiency and reducing construction costs and safety risks. The three-tier progressive micro-upgrade method proposed in this paper achieves a closed-loop process spanning regional bottleneck identification, precise on-site optimisation, and construction implementation. It provides a systematic technical pathway and practical reference for the micro-upgrade of charging infrastructure in existing urban areas, effectively balancing the dual benefits for both users and contractors.