Deadline Differentiated Dynamic EV Charging Price Menu Design

The increasing number of electric vehicles (EVs) on the road brings both opportunities and challenges to the power system. For the EV charging stations (EVCSs), it is often difficult to conduct effective operations due to the incomplete information in EVs' departure times and the opacity of their preference information. To tackle this challenge, we seek to design the optimal deadline differentiated dynamic price menu that offers multiple choice-pairs of deadlines and charging prices. We prove that such price menus can incentivize EVs to truthfully reveal their departure time. We then analyze the properties of the optimal price menu with complete EV information, i.e., social optimality and first-degree price discrimination. For the incomplete information case, we first design a systematic method to estimate the utility and demand information for a large population of EVs based on EV behavior data. Then, we employ mixed-integer quadratic programming for the efficient optimal price menu design. The numerical study based on field data in California verifies the remarkable performance of our designed price menu.