Skip to Main Content
A massive amount of energy consumption currently stems from the transportation sector. Therefore, improvements in power usage by commuting vehicles are being studied and becoming an increasingly popular research topic. In particular, there is a growing need to model the envisioned smart infrastructure, including charging stations, some of which might include energy storage devices and swappable, pre-charged batteries. For such new stations, power management is indeed crucial for operation costs, driver convenience, and overall smart grid efficiency. Information technology, communications and vehicle intelligence need to play a crucial role in this process. In this paper, we describe a quantitative model and propose a guiding and control system for the charging of PHEVs in a future smart infrastructure. Specifically, we describe an algorithm that can be used for the joint guidance and power control of smarter electric vehicles in the smart grid. We envision it as part of a larger Smart Guide for the Smart Grid (SGSG) system. Its function is to guide PHEV drivers, directing them to the appropriate charging station, while attempting to achieve an optimization goal at the same time. Our algorithm aims at a joint guiding and power control, in order to heuristically maximize the weighted sum of the average of throughput and energy cost consumption from multiple vehicle charging stations, while satisfying a cost constraint at each station, as well as system stability.