Title:  Probabilistic Analysis and Control Methods for Electric Vehicle Charging

Committee: 

Dr. Coogan, Advisor

Dr. Wardi, Chair

Dr. Grubert

Abstract: The objective of the proposed research is to study the electric vehicle (EV) charging ecosystem that is comprised of various entities such as charging facility operators, customers, and utility providers. As widespread adoption of EVs continues to proliferate, there is a growing need for intelligent ways to manage the interactions amongst the EV charging ecosystem stakeholders. EV charging is subject to many random processes that affect the ways the participants in the ecosystem behave; hence, it is often advantageous to frame the problem from a probabilistic perspective. While there are many approaches to addressing the EV charging ecosystem problems, we focus primarily on pricing-based planning methods. We present preliminary work that constructs two operational pricing models for resource-constrained EV charging facilities. In addition, we formulate and derive probabilistic guarantees on the charging facility resource limits. These results are illustrated via numerical studies. Lastly, we outline research paths that build upon the proposed work.