The Shape of U – On the Structure of Utility from Electric Vehicle Charging

With the growing adoption of electric vehicles, understanding user charging behavior is increasingly important for informing operational, investment, and policy decisions regarding their integration into the power system. While utility functions are commonly used to describe user preferences in charging behavior models, most existing studies rely on formulations with limited theoretical consistency and empirical validation, potentially leading to biased expectations. This paper empirically compares different utility function specifications and examines their implications for charging behavior modeling and charging station profitability. I introduce a novel discrete choice model framework to efficiently estimate utility function parameters from revealed preference data. Using a dataset of observed charging sessions at public charging stations in Germany, the model identifies accurate utility functions, uncovers charging preferences, and simulates station segment viability. The results suggest that charging utility is non-linear: marginal utility decreases with charged energy and marginal disutility increases with charging duration. An interaction between energy and duration leads to higher marginal valuation of energy for longer charging durations. Stations profit from inelastic demand driven by users who highly value energy content, are less price sensitive, and engage in high-value activities at the charging location, such as in urban areas or traffic hubs.