Identifying Differentiated User Preferences for Spatial Flexibility Assessment of Fast Charging Station Loads

The spatial flexibility of fast-charging station (FCS) loads refers to the potential to redistribute these loads by influencing users’ FCS selections via incentives. Such spatial flexibility can benefit power systems by alleviating congestion and promoting renewable energy integration. Since user preferences directly influence FCS selections, they play a key role in assessing the spatial flexibility of FCS loads. From the perspective of charging station operators (CSOs), this paper aims to identify user preferences using real-world data (station, user, and order data) and a data-driven discrete choice model. The target is to identify differentiated user preferences across various influencing attributes (charging price, charging power, station facilities, and surrounding points of interest), and differences between private and commercial electric vehicles (EVs). Case studies validate the proposed approach for identifying user preferences, with the accuracy of predicting FCS selections exceeding 80%. These insights provide a foundation for CSOs to effectively utilize EV spatial flexibility through price incentives.