This project aims to develop and implement intelligent techniques to manage the charging and discharging of electric vehicle (EV) batteries and design EV management framework using state of the art artificial intelligence algorithms for addressing major challenges that arise in the deployment and management of EVs in residential and commercial levels. The key focus of this project is to develop new tools to optimize the infrastructure and maximize the benefits for businesses and consumers with distributed energy resources including EVs and photovoltaic systems. The outcomes of this project will be to produce new applied research utilizing AI in EV management and V2G resource optimization and, thus contribute in creating new jobs and reduce greenhouse gas emissions
This PhD will explore different AI-based techniques which will be implemented not only to predict optimal solutions but also to estimate uncertainty in EV usages and charging while combining with methods in Human Interpretable Machine Learning to ensure EV owners and businesses can have confidence in the models. The outcomes of this project will be to produce new applied research utilizing AI in EV management and V2G resource optimization. The results will be verified using a real time simulator (OPAL RT) and power systems equipment available at Tech-Lab UTS. The unique and competitive ideas developed and verified using real-time simulator will be published in reputed journals and conferences.