The accelerating transition toward sustainable transportation has led to a rapid deployment of Plug-in Hybrid Electric Vehicles (PHEVs), introducing significant operational challenges for active distribution networks, particularly in terms of voltage regulation and network flexibility. High and spatially concentrated charging demand, combined with stochastic vehicle behavior, can substantially reduce voltage headroom and compromise grid integrity if not properly managed. To address these challenges, this paper proposes a novel Active Distribution Network Management (ADNM) framework based on the Voltage Network Flexibility Index (VNFI) for coordinated PHEV charging and discharging. The VNFI is employed as an actionable steering signal to identify voltage-critical buses and time periods, enabling flexibility-aware scheduling decisions under strict network-security constraints. Stochastic PHEV arrival, departure, and energy demand are modeled using probabilistic distributions, and the proposed framework is implemented and validated through a high-fidelity MATLAB–OpenDSS co-simulation on a modified IEEE 33-bus distribution system. Numerical results demonstrate that the VNFI-driven coordination improves the voltage flexibility margin by up to 44.2% and reduces total power losses by 29.4% compared with a conventional TOU-based charging strategy. Moreover, even under 100% PHEV penetration, the maximum voltage deviation remains within 0.055 p.u., confirming the robustness and scalability of the proposed approach. The results highlight the effectiveness of VNFI-based management in transforming PHEVs into flexibility resources for future smart grid operations. • The study examines the operational challenges posed by electric vehicles (EVs) on distribution systems, focusing on voltage control and power losses. • A probabilistic model for aggregating plug-in hybrid electric vehicles (PHEVs) is proposed, based on parameters derived from the National Household Travel Survey (NHTS). • The concept of voltage flexibility is introduced, with the evaluation of a newly proposed index to assess it. • A smart charging/discharging approach is developed for optimal PHEV scheduling within active distribution networks (ADNs), addressing power demand throughout different hours. • A nonlinear optimization method for mixed integers is used to formulate and solve the scheduling problem. • The proposed method is tested on an IEEE 33-bus distribution system, demonstrating its effectiveness and validating the proposed index against previously reported strategies.
Hafezimagham et al. (Sat,) studied this question.