Design and Implementation of Low-Cost Electric Vehicles (Evs) Supercharger: A Comprehensive Review
<|reference_start|>Design and Implementation of Low-Cost Electric Vehicles (Evs) Supercharger: A Comprehensive Review: This article presents a probabilistic modeling method utilizing smart meter data and an innovative agent-based simulator for electric vehicles (EVs). The aim is to assess the effects of different cost-driven EV charging strategies on the power distribution network (PDN). We investigate the effects of a 40% EV adoption on three parts of Frederiksberg's low voltage distribution network (LVDN), a densely urbanized municipality in Denmark. Our findings indicate that cable and transformer overloading especially pose a challenge. However, the impact of EVs varies significantly between each LVDN area and charging scenario. Across scenarios and LVDNs, the share of cables facing congestion ranges between 5% and 60%. It is also revealed that time-of-use (ToU)-based and single-day cost-minimized charging could be beneficial for LVDNs with moderate EV adoption rates. In contrast, multiple-day optimization will likely lead to severe congestion, as such strategies concentrate demand on a single day that would otherwise be distributed over several days, thus raising concerns about how to prevent it. The broader implications of our research suggest that, despite initial worries primarily centered on congestion due to unregulated charging during peak hours, a transition to cost-based smart charging, propelled by an increasing awareness of time-dependent electricity prices, may lead to a significant rise in charging synchronization, bringing about undesirable consequences for the power distribution network (PDN).<|reference_end|>
@article{rahman2024design,
    title={Design and Implementation of Low-Cost Electric Vehicles (Evs)
  Supercharger: A Comprehensive Review},
    author={Md Khaledur Rahman, Faysal Amin Tanvir, Md Saiful Islam, Md Shameem
  Ahsan and Manam Ahmed},
    journal={arXiv preprint arXiv:2402.15728},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.15728},
    primaryClass={eess.SY cs.SY}
}