Optimal Charging of Plug-in Hybrid Electric Vehicles in Smart Grids
Plug-in hybrid electric vehicles (PHEVs) play an important role in making a greener future. Given a group of PHEVs distributed across a power network equipped with the smart grid technology (e.g. wireless communication devices), the objective of this paper is to study how to schedule the charging of the PHEV batteries. To this end, we assume that each battery must be fully charged by a pre-specified time, and that the charging rate can be time-varying at discrete-time instants. The scheduling problem for the PHEV charging can be augmented into the optimal power flow (OPF) problem to obtain a joint OPF-charging (dynamic) optimization. A solution to this highly nonconvex problem optimizes the network performance by minimizing the generation and charging costs while satisfying the network, physical and inelastic-load constraints. A global optimum to the joint OPF-charging optimization can be found efficiently in polynomial time by solving its convex dual problem whenever the duality gap is zero for the joint OPF-charging problem. It is shown in a recent work that the duality gap is expected to be zero for the classical OPF problem. We build on this result and prove that the duality gap is zero for the joint OPF-charging optimization if it is zero for the classical OPF problem. The results of this work are applied to the IEEE 14 bus system.
© 2011 IEEE. Date of Current Version: 03 October 2011. This research was supported by ONR MURI N00014-08-1-0747 "Scalable, Data-driven, and Provably-correct Analysis of Networks," ARO MURI W911NF-08-1-0233 "Tools for the Analysis and Design of Complex Multi-Scale Networks," the Army's W911NF-09-D-0001 Institute for Collaborative Biotechnology, and NSF NetSE grant CNS-0911041.