Adaptive EV Charging Strategies for Voltage Regulation and System Strength Enhancement in Low Voltage Distribution Network

Al-Amin

doi:10.60867/00000149

The rapid growth of electric vehicles (EVs) is crucial to decarbonising transportation; however, the large-scale, uncoordinated integration of EVs poses significant technical challenges for low-voltage distribution networks. Fast chargers and simultaneous electric vehicle (EV) charging can burden distribution networks. Renewable energy intermittency poses additional challenges by affecting voltage stability, increasing peak demand, and limiting hosting capacity (HC). These encounters underscore the need for grid-supportive EV charging strategies that transcend static, purely optimisation-based, or worst-case approaches. To address these challenges, this thesis investigates the adverse impacts of large-scale EV integration and develops adaptive, grid-aware EV charging strategies combining real-time control, coordinated energy management, HC enhancement, and optimisation-based scheduling to improve voltage regulation, system strength, and practical EV integration in low-voltage distribution networks. Preliminary studies assess the impact of EV charger specifications, penetration levels, and reactive power capabilities on grid performance utilising standard IEEE test systems. The findings indicate that high deployment of fast chargers can notably degrade voltage profiles, whereas providing reactive power support from EVs markedly enhances network resilience. Building on these insights, a Weighted Average Power Estimator (WAPE)–based real-time control framework has been developed for bidirectional EV chargers. Unlike predictive or optimisation-based approaches, WAPE dynamically determines active and reactive power references using the instantaneous point-of-common-coupling (PCC) voltage and the EV battery’s state-of-charge (SoC). The controller operates in all four quadrants, requires minimal computation, and is inherently scalable. Extensive dynamic simulations on IEEE 13- and 33- bus networks demonstrate that WAPE consistently maintains bus voltages within acceptable limits (400–430 V). The results show improvements in voltage stability margins by up to 157% and reductions in EV charging time by up to 50% compared with uncontrolled charging. The performance is observed under variable photovoltaic (PV) generation, sudden load disturbance, and EVs with different SoC. Additionally, the effectiveness of this support is highly contingent on the distribution network's electrical characteristics, particularly the X/R ratio, underscoring the need for network-informed EV control strategies. To further enhance system-level coordination, this thesis integrates WAPE-controlled EV charging within a Virtual Power Plant (VPP) framework that combines EV charging, battery energy storage, PV, and vehicle-to-grid support. Results show that coordinated VPP operation significantly improves voltage regulation, reduces EV waiting and charging times, and increases overall network robustness. The thesis also addresses the critical gap between theoretically optimised and practically usable EV HC by demonstrating that WAPE-based dynamic control can preserve higher HC under real-world disturbances, thereby reducing unnecessary derating and enhancing sustainable network utilisation. Finally, a multi-objective optimisation framework based on particle swarm optimisation (PSO) is developed for coordinated multi-EV charging with a novel penalty modelling. The results suggest that fragmented (multi-session) charging can maximise economic and network benefits, whereas continuous (single session) charging enables a more practical, feasible implementation, despite higher costs and reduced flexibility.

Adaptive EV Charging Strategies for Voltage Regulation and System Strength Enhancement in Low Voltage Distribution Network

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