Distributed Optimal Charging Strategy of MVDC Electric Vehicle Ultra-fast Charging Station to Manage Peak Load and Consumer Convenience

초록

This paper proposes a distributed optimal charging strategy for medium-voltage direct current (MVDC) electric vehicle ultra-fast charging stations (EV UFCS) that simultaneously addresses the convenience of electric vehicle (EV) owners and the management of peak load conditions. The method employs a consensus-based algorithm to enable efficient data exchange of EV information over a sparse communication network. Unlike conventional optimization techniques, the proposed strategy generates active power reference for individual chargers through distributed decision-making, thereby mitigating risks of centralized control scheme. The strategy prioritizes higher charging power for EVs with lower state of charge (SOC) and shorter dwell times, while ensuring the total active power of the chargers remains within the rated capacity of the EV UFCS. The system stability is validated by constructing a small-signal state-space (SS) model of a consensus control loop, followed by eigenvalue analysis. Simulation studies are conducted using an electromagnetic transient model in PSCAD and a small-signal model of the proposed EV charging strategy in Python, demonstrating that the proposed method achieves comparable performance to centralized optimization-based control schemes, effectively managing the charging of multiple EVs in MVDC EV UFCS.

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