Voltage Control for Active Distribution Networks Considering Coordination of EV Charging Stations

Modern distribution networks are increasingly affected by the widespread adoption of photovoltaic (PV) generation and electric vehicles (EVs). The variability of PV output and the fluctuating demand of EVs may cause voltage violations that threaten the safe operation of active distribution networks (ADNs). This paper proposes a voltage control strategy for ADNs to address the voltage violation problem by utilizing the control flexibility of EV charging stations (EVCSs). In the proposed strategy, a state-driven margin algorithm is first employed to generate training data comprising response capability (RC) of EVs and state parameters, which are used to train a multi-layer perceptron (MLP) model for real-time estimation of EVCS response capability. To account for uncertainties in EV departure times, a relevance vector machine (RVM) model is applied to refine the estimated RC of EVCSs. Then, based on the estimated RC of EVCSs, a second-order cone programming (SOCP)-based voltage regulation problem is formulated to obtain the optimal dispatch signal of EVCSs. Finally, a broadcast control scheme is adopted to distribute the dispatch signal across individual charging piles and the energy storage system (ESS) within each EVCS to realize the voltage regulation. Simulation results on the IEEE 34-bus feeder validate the effectiveness and advantages of the proposed approach.