Optimizing Electric Vehicle Charging Through Determinization

We propose a determinization based approach to optimize the charging policies of an electric vehicle (EV) operating in a vehicle-to-grid (V2G) setting. By planning when to charge or discharge electricity from the vehicle, the long-term cost of operating the EV can be minimized, while being consistent with the owner’s preferences. For an EV operating under price uncertainty caused by the dynamic pricing of electricity, this problem needs to be solved on-the-fly. Therefore, we model this problem as a Stochastic Shortest Path (SSP) problem and employ a determinization technique to solve it. Since it is hard to predict a priori the performance of a determinization method on a given problem, we introduce the notion of Lossless Determinization (LLD) that produces optimal action selection via determinization and present an approach that achieves lossless determinization by adjusting the cost of actions to account for the ignored outcomes. We also present Approximate Lossless Determinization (ALLD)—an effective method for approximating the cost of actions based on state features. We evaluate the performance of ALLD and demonstrate its effectiveness on a range of settings for the electric vehicle charging problem.