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Accelerating a consensus-based EV smart charging algorithm by user priority clustering
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AI
DOI：10.1016/j.scs.2024.105392.png)
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Abstract
En 中文
The rapid increase in Electric Vehicle (EV) adoption leads to significant challenges for charging station operators due to the unbalance between the growing demand for charging services and their limited power capacity connected to the grid. To tackle the challenge, this paper applies a two-step architecture in which an energy management system (EMS) in the first step determines the available capacity to charge the present fleet of EVs, after which in the second step this capacity is distributed over the individual EVs. To optimally allocate available power and satisfy user requirements, a user priority -based charging management strategy is proposed. Such priority can optimally order the set of EVs to be charged based on user input. However, relying solely on user -estimated input can be prone to incorrect priority due to inaccurate estimations. Therefore, we introduced a clustering of charging sessions based on the user -provided estimated information in the proposed priority function. These clusters relax the effect of inaccurately estimated user input by grouping charging sessions with similar behavior. Our proposed priority can increase user satisfaction by up to 30%, as measured by the percentage of requested energy that is delivered to users, compared to scenarios without priority, 10% more than priority based solely on estimation information, and 8% more than first -come -first -serve. To avoid exposing the personal behavior of the user, we introduce a decentralized approach, applying a consensusbased method that allows local control per EV charging station and only requires minimal communication of a consensus variable with neighboring charging stations. By introducing the priority in the communication weight matrix of the consensus -based algorithm, we accelerate the convergence rate more than 10 times. Simulation results based on real -world data sets in Belgium demonstrate the proposed method scales well with growing fleet sizes.
Keywords:
Electric vehicle
Smart charging
Decentralized
Consensus-based
Priority
Cluster