Internet-Inspired Autonomous Electric Vehicle Charging

Electric vehicles (EVs) are transforming the modern transportation and energy systems. With a growing EV market, the mass penetration of EVs into the utility grid will result in detrimental effects due to coincidence between utility peak power loading and EV charging. This impact will include increased peak loading and voltage drops that will call for over-investments in the network resulting in an overall high cost for the society. Therefore, advanced and practical interaction methods between vehicles, charging stations, and the utility grid need to be developed. Internet-inspired EV charge control offers a new paradigm-shift for EV charge control studies. This project aims to build a new autonomous and fair EV charge control technique that can penetrate into practice at large scales. The significance of the proposed idea lies in the effort to bring together a cyber-physical system that utilizes the prior art in end-to-end internet network congestion control with decentralized autonomous EV charging. The effort is inter-disciplinary and brings together ideas from computer science as well as power engineering to support mass integration of EVs into the conventional electric energy system. The proposed idea can impact the way all grid-connected power electronics systems are controlled. The algorithms developed in this work can be used to accelerate the integration of low-carbon energy sources such as solar photovoltaic systems.

The proposed research develops a new family of EV charging algorithms by adopting some of the well-deployed end-to-end congestion control techniques in the Internet. The research objectives include (i) investigating distribution grid congestion through extensive data collection from field, modeling, and simulations to understand and extract the impacts of EV charging on voltage and frequency signatures at the end-nodes, (ii) design of entirely decentralized and localized EV charging algorithms that work autonomously, (iii) investigation of adaptive and increase and decrease of EV charging rate according to the power flow congestion on the distribution network to attain proportional or max-min fair charging of EVs in a neighborhood, and (iv) exploration of hybrid charging architectures where more than one EV measurements can be utilized. The cyber-physical system that will be developed with this project will help the researchers understand and resolve issues relating to large scale electric vehicle integration.