Modeling Joint Charging and Parking Choices of Electric Vehicle Drivers

Electric vehicles (EVs) offer significant opportunities to improve sustainability of the road transport sector. But simultaneously, widespread adoption of EVs would create new challenges. For example, spatiotemporal concentration of charging events in high-density residential or commercial areas would place extreme demands on the power network, causing bottlenecks and grid instability. A novel approach to the typical decentralized control methods for EV charging service providers (CSPs) is presented. First, static price signals based on anticipated demand define a set of charging offers, targeted to segments of EV users. Prices are differentiated either only by time or both by time and place and allow comparison and evaluation of both scenarios. A choice-based revenue management method is employed to optimize allocation of generated charging offers, with respect to revenue outcome for the CSP. The charging coordination techniques are demonstrated through simulation. Data come from the London Travel Demand Survey and particularly trips around Westfield, one of Europe's largest urban shopping malls, representing out-of-home charging behavior for short intervals in a high-demand area. Findings suggest that in a first-come, first-served system, locational pricing might create opportunities both for increased revenue and for relocation of charging events to less-congested facilities. In the revenue management system, locational pricing significantly favors total revenue outcome but without discharging vulnerable areas. However, because agents with conflicting interests participate in the process (infrastructure owners, power system operators, EV drivers), opportunity exists for the CSP to adapt constraints according to the priority of its objectives.