  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).
