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Impact of Ultra-Fast Electric Vehicle Charging on Distribution-System Voltage Stability: A Monte Carlo V–Q Sensitivity Approach

  † These authors contributed equally to this work.

Submitted:

02 December 2025

Posted:

04 December 2025

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Abstract
This paper assesses the steady-state voltage impact of ultra-fast electric vehicle (EV) charging on the IEEE 33-bus radial distribution feeder. Four practical scenarios are examined by combining two penetration levels (6 and 12 charging points, representing approximately 20% and 40% of PQ buses) with two charger ratings (1 MW and 350 kW per point). Candidate buses for EV station integration are selected through a nodal voltage–reactive sensitivity ranking (∂V/∂Q), prioritizing electrically robust locations. To capture realistic operating uncertainty, a 24-hour quasi-static time-series power-flow study is performed using Monte Carlo sampling, which jointly models residential-demand variability and stochastic EV charging activation. Whenever the expected minimum-hourly voltage violates the 0.95 p.u. threshold, a closed-form sensitivity-guided reactive compensation is computed and injected at the critical bus, and the power flow is re-solved. Results show that ultra-fast charging can produce sustained under-voltage even under robust siting, particularly at high penetration and 1 MW ratings; however, the proposed compensation consistently raises the minimum-voltage trajectory by about 0.03–0.12 p.u., substantially reducing the depth and duration of violations. The cross-case comparison confirms that lowering unit charger power mitigates voltage degradation and reactive-support requirements, while charger clustering accelerates stability-margin depletion. Overall, the Monte Carlo V–Q sensitivity framework provides a lightweight and reproducible tool for probabilistic voltage-stability assessment and targeted mitigation in EV-rich distribution networks.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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