Hierarchical Autonomous Coordination of EVs and Flexible Loads in Active Distribution Networks

Abstract

Large-scale electric vehicle (EV) integration can provide valuable flexibility for active distribution networks, but the practically available response is constrained by vehicle connection status, battery energy, departure urgency, travel demand, and user participation. This paper proposes a travelchain-aware hierarchical autonomous coordination method for EVs and flexible loads in an active distribution feeder. At the feeder level, regulation targets are allocated among transformer areas according to network loading, voltage conditions, and aggregated dispatchable flexibility. At the local level, each transformer area autonomously coordinates EV charging, discharging, and flexible demand while satisfying battery-energy and departure requirements. The proposed flexibility model distinguishes technically available capacity from practically dispatchable capacity by incorporating travel-chain information and participation willingness. Four control cases are evaluated on a feeder containing three transformer areas and six heterogeneous EV clusters. Simulation results show that the proposed method reduces the maximum feeder load from 931.60 to 764.97 kW and the peak-to-valley difference from 510.26 to 343.64 kW, while improving the minimum nodal voltage from 0.9539 to 0.9589 p.u. All EV clusters satisfy their departure-energy requirements, and the transformer-area target-tracking error is eliminated. By contrast, centralized coordination based only on technical flexibility achieves a lower theoretical peak but satisfies the departure requirements of only 50% of the EV clusters, while hierarchical coordination without travel-chain awareness produces a tracking error of 8.40 kW. The results demonstrate that practical flexibility estimation is essential for reliable feedertransformer coordination.