Establishing a coordinated relationship among a distribution system operator (DSO) agent, electric vehicle integrator (EVA) agents, and electric vehicle (EV) agents is crucial for efficient charging scheduling considering the rapid expansion of the electric vehicle market. In light of the challenges posed by a large number of EVs with diverse physical parameters and stochastic charging behaviors, we introduce a virtual group (VG) approach based on deadlines to aggregate EV arrivals at charging stations. Subsequently, we develop a novel hierarchical distributed multi-agent system (HDMAS), where the coordination problem among a DSO agent, EVA agents, and VG agents is transformed into an exchange problem and effectively solved in a distributed manner using the alternating direction method of multipliers (ADMM). To address the charging issue for each EV, we propose a policy called deadline-differentiated threshold charging (DDTC), which ensures that the charging rate of EVs within each VG is solely determined by their VG threshold. Finally, we provide simulation results using an independently developed simulator for NEU-ITS (Northeastern University - Intelligent Transmission System) to demonstrate the effectiveness and applicability of our proposed model. The experimental results demonstrate that the algorithm’s complexity exhibits a linear relationship with the number of EVAs and VGs, while the complexity of the comparative models is linearly associated with the number of EVs.


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    Title :

    A Cooperative Multi-Agent Charging Scheduling by Regrouping EVs With Differentiated Deadlines


    Contributors:
    Cai, Ling (author) / Guo, Ge (author) / Wu, Dubin (author)


    Publication date :

    2025-05-01


    Size :

    5057277 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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