Mobility-Centric Modeling and Scalable Optimization on Demand Flexibility in Electric Vehicle Charging

Abstract

Electric vehicles (EVs) promise substantial demand flexibility for the power system. That flexibility is rooted in mobility: where vehicles travel, where they stay, and how much energy they need for future trips. This talk develops mobility-aware flexibility, which allows charging to shift across a vehicle’s week-long itinerary as long as its mobility needs remain feasible. At the system level, I study how millions of EVs can be coordinated when both distribution-feeder headroom and shared public charging ports are scarce, and how the two infrastructures should be co-expanded. Despite the resulting metropolitan-scale, nonconvex problem, I develop iterated price response algorithm, structure-exploiting per-vehicle solvers, and primal-dual certificates that make near-optimal coordination tractable for 1.84 million EVs, 1,303 feeders, and 17,300 existing public charging ports. In the modeled 30% EV-adoption scenario for the San Francisco Bay Area, coordinated mobility-aware charging reduces estimated feeder and charger expansion costs from $15.3 billion to $114 million; once unidirectional charging is fully coordinated, bidirectional charging adds only about 5% further savings.

The research views EV charging management as a large-scale, tightly coupled complex system and asks what flexibility is actually realizable and actionable. I will close by discussing my recent thoughts on some emerging directions of sustainable infrastructure systems.