Mobility profiles from charging processes by electric vehicles at workplace: A Case Study in Southern Germany

The dataset shows eight cluster groups that depict the mobility behavior of electric vehicle users in the employee context. For this purpose, 23.9 million data entries were analyzed, corresponding to 37,238 charging sessions. These data were collected over the year 2023. The 220 charging points were exclusively accessible to employees (private use case). From the data, cluster groups were derived using the Gaussian Mixture Model. The dataset contains eight files. Each file represents a cluster group characterized by 1000 cluster-specific entries, which are based on the results of this study and generated using the Monte Carlo method. Each cluster is represented by the mean parking start hours (arrival time - in decimal hours), mean parking duration (in decimal hours), the average energy recharged, and the average charging duration, each including the cluster-specific standard deviation and median. Further information can be obtained from the upcoming publication: "Load flexibilities from charging processes by electric vehicles at workplace: A Case Study in Southern Germany ."