Demand response via large scale charging of electric vehicles

The problem of centralized scheduling of large scale charging of electric vehicles (EVs) with demand response options is considered. A stochastic dynamic programming model is introduced in which the EV charging service provider faces stochastic demand, convex non-completion penalties, and random demand response requirements. Formulated as a restless multi-armed bandit problem, the EV charging problem is shown to be indexable, thus low complexity index policies exist. An enhancement of the Whittle's index policy based on spatial interchange according to the less laxity and longer processing time (LLLP) principle is presented. Numerical results illustrate the performance improvement and the capability of handling various operation uncertainties of the proposed index policy.