Discount-based pricing and capacity planning for EV charging under stochastic demand

P. Pandit, S. Coogan
American Control Conference, 2018


The increasing market penetration of electric vehicles (EVs) poses new business avenues for existing facilities such as parking lots, gas stations, and other EV charging aggregators. There remain several open problems for these players in the EV power supply chain, such as pricing, scheduling the charging, and capacity planning, with limited theoretical understanding about their optimality. In this paper we consider an EV charging aggregator that provides energy to randomly arriving users with a user specified charging deadline, and we assume the aggregator has a total power budget which must be satisfied with high probability at each time instant.

We look at a class of parameterized static pricing functions that incentivize EV users to provide the aggregators with longer deadlines, to avoid having to charge each EV at the peak kW rate. Under this pricing, we derive non-asymptotic concentration bounds on the required power capacity under stochastic arrival of users using a queuing theoretic approach.