Rapidly increasing electric vehicle (EV) numbers in the biggest European EV market Germany provoke the need for appropriate charging infrastructure. The rapid doubling of EV numbers each year raises concerns about the potential risk for the electricity grid. At the same time, the comparatively slower 40% annual increase in public EV charging station (EVCS) numbers raise questions about sufficiently available charging spots. Therefore, this paper analyses the utilization rates of more than 9700 public EVCSs in Germany and proposes clustering techniques to differentiate EVCS usage behavior. Instead of the EVCS location, it is shown through unsupervised learning techniques including K-means and K-medoids, that cluster behavior almost evenly distributes among scenarios. Slight tendencies indicate that fast and ultra-fast EVCSs are used throughout the day peaking in the evening. EVCSs with high arrival rates in the morning tend to be rather little utilized. Furthermore, usage is overall low with more than half of public charging points being used less than once a day. Although usage has been increasing over the years, still in 2022, 10% of public EVCSs were used less than once a week.
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Starosta et al. (2024) studied this question.
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