Zoom Link: https://hku.zoom.us/j/91849018634?pwd=YgyqXnIIfUsd8YGU2YNaSa5aj3uWou.1
Meeting ID: 918 4901 8634
Password: 038419
Abstract
The dynamic wireless charging (DWC) system based on wireless charging lanes (WCLs) is an important component of smart cities, allowing electric vehicles (EVs) to charge while moving. It is necessary to establish a user-oriented real-time DWC navigation system to achieve the joint optimization of EV routing and charging. However, the modeling characteristics of DWC and the risk preferences of EV owners towards congested WCLs are completely different from those in traditional wired charging. Furthermore, optimal EV charging navigation is always challenging without prior knowledge of uncertainty in electricity prices and traffic conditions. This work first proposes a novel dynamic charging routing model for individual EVs to minimize travel and charging costs, and reformulates it as a two-step optimization problem to facilitate feature extraction. Then, mirror-symmetrical Dijkstra’s algorithm (MSDA) is proposed to solve the reformulated model in linear time and extract advanced features from the stochastic information. By feeding the system state containing extracted features into the deep Q network (DQN) in an event-triggered manner, the near-optimal charging navigation strategy is finally obtained. The proposed MSDA-DQN approach not only efficiently extracts low-dimensional interpretable input features, but also adaptively learns the unknown dynamics of system uncertainty. Numerical results based on simulated and real-world data validate the proposed approach.
Speaker
Miss Chaoran Si
Department of Electrical and Electronic Engineering
The University of Hong Kong
Biography of the Speaker
Chaoran Si received her bachelor degree from Tianjin University in 2018 and her master degree from Zhejiang University in 2021, both in electrical engineering. She is currently working toward the Ph.D. degree in electrical and electronic engineering in the Department of Electrical and Electronic Engineering at the University of Hong Kong. Her current research interests include power-transportation systems, wireless charging of electric vehicles, and deep reinforcement learning.
Organiser
Prof. Yunhe Hou
Department of Electrical and Electronic Engineering, The University of Hong Kong
All are welcome!