Load Flexibilities from Charging Processes by Electric Vehicles at the Workplace: A Case Study in Southern Germany

The workplace, as a promising location for Electric Vehicle Supply Equipment (EVSE), presents a particular challenge, as different user requirements (e.g., parking and charging durations) meet a spatially and quantitatively limited offer of EVSE. However, integrating electric vehicles synergistically into the energy system of the employer can increase the profitability of the system and, correspondingly, increase the number of EVSE. For this, a deep understanding of employees’ charging behavior is key. For providing some evidence of empirical charging patterns at the workplace, this work examined a dataset of 23.9 million observations on empirical charging processes at workplaces in 2023. To identify user groups, a probabilistic model (Gaussian Mixture Model) and a K-Means clustering approach were applied and the results compared. Eight groups were identified, including full-time and part-time employees, pool vehicle users, and opportunists. The group-specific probability distributions are used to publish a synthetic dataset of parking and charging patterns at workplaces. The openly provided dataset helps to identify the right composition of EVSE in the employee context and to optimize potential fields of action.