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<p>The rapid growth of electric vehicles (EVs) in low-voltage (LV) distribution networks poses significant challenges to voltage regulation, transformer loading, and charging fairness, particularly in networks with high EV penetration and spatially dispersed charging locations. Conventional droop-based EV charging strategies primarily focus on local electrical constraints and often neglect system reliability aspects, leading to unequal charging performance and limited adaptability under stressed operating conditions. This paper proposes an adaptive multi-objective droop control framework for coordinated EV charging in smart parking lots, explicitly integrating voltage deviation, transformer loading, and network reliability indices into the charging control mechanism. EV parking areas are modeled as active nodes in a European benchmark LV distribution network, considering dynamic state-of-charge and battery capacity constraints across residential, commercial, and industrial zones. To address the limitations of existing approaches, a reliability-driven adaptive droop strategy is introduced, where droop coefficients are dynamically tuned based on local reliability sensitivity, enabling location-aware and fairness-oriented charging control. Furthermore, a combined droop control scheme is developed to simultaneously account for voltage constraints, transformer thermal limits, and reliability performance, allowing coordinated power sharing among EVs and distributed generation units without relying on centralized optimization. Simulation results demonstrate that the proposed framework reduces transformer overloading by up to 40%, improves minimum bus voltages by approximately 10%, and significantly enhances charging equity among EV users at different network locations. These results confirm that incorporating reliability metrics into adaptive droop control offers a distinct performance advantage over conventional droop-based charging strategies and provides a scalable, resilient solution for reliable EV integration in LV distribution networks.</p>

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Adaptive Droop Control for Smart Electric Vehicle Parking to Enhance Distribution Network Performance

  • 期刊论文

  • 发表日期：

    2026年6月22日

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  • Ghasem Ansari,
  • Reza Keypour

摘要

The rapid growth of electric vehicles (EVs) in low-voltage (LV) distribution networks poses significant challenges to voltage regulation, transformer loading, and charging fairness, particularly in networks with high EV penetration and spatially dispersed charging locations. Conventional droop-based EV charging strategies primarily focus on local electrical constraints and often neglect system reliability aspects, leading to unequal charging performance and limited adaptability under stressed operating conditions. This paper proposes an adaptive multi-objective droop control framework for coordinated EV charging in smart parking lots, explicitly integrating voltage deviation, transformer loading, and network reliability indices into the charging control mechanism. EV parking areas are modeled as active nodes in a European benchmark LV distribution network, considering dynamic state-of-charge and battery capacity constraints across residential, commercial, and industrial zones. To address the limitations of existing approaches, a reliability-driven adaptive droop strategy is introduced, where droop coefficients are dynamically tuned based on local reliability sensitivity, enabling location-aware and fairness-oriented charging control. Furthermore, a combined droop control scheme is developed to simultaneously account for voltage constraints, transformer thermal limits, and reliability performance, allowing coordinated power sharing among EVs and distributed generation units without relying on centralized optimization. Simulation results demonstrate that the proposed framework reduces transformer overloading by up to 40%, improves minimum bus voltages by approximately 10%, and significantly enhances charging equity among EV users at different network locations. These results confirm that incorporating reliability metrics into adaptive droop control offers a distinct performance advantage over conventional droop-based charging strategies and provides a scalable, resilient solution for reliable EV integration in LV distribution networks.