Real-Time Distributed Control for Smart Electric Vehicle Chargers: From a Static to a Dynamic Study

At high penetrations, uncontrolled electric vehicle (EV) charging has the potential to cause line and transformer congestion in the distribution network. Instead of upgrading components to higher nameplate ratings, we investigate the use of real-time control to limit EV load to the available capacity in the network. Inspired by rate control algorithms in computer networks such as TCP, we design a measurement-based, real-time, distributed, stable, efficient, and fair charging algorithm using the dual-decomposition approach. We show through extensive numerical simulations and power flow analysis on a test distribution network that this algorithm operates successfully in both static and dynamic settings, despite changes in home loads and the number of connected EVs. We find that our algorithm rapidly converges from large disturbances to a stable operating point. We show that in a test setting, for an acceptable level of overload, only 70 EVs could be fully charged without control, whereas up to around 700 EVs can be fully charged using our control algorithm. This compares well with the maximum supportable population of approximately 900 EVs. Our work also provides engineering guidelines for choosing the control parameters and setpoints in a distribution network.