Joint Parking and Power Management for Electric Vehicle Edge Computing: A Bilevel Optimization Approach

Authors

Xumin Huang, School of Automation, Guangdong University of Technology, Guangzhou, China & State Key Laboratory of Internet of Things for Smart City, University of Macau, Macao
Weifeng Zhong, School of Automation, Guangdong University of Technology, Guangzhou, China
Jiangtian Nie, School of Computer Science and Engineering, Nanyang Technological University, Singapore
Jiawen Kang, School of Automation, Guangdong University of Technology, Guangzhou, China
Zehui Xiong, Pillar of Information Systems Technology and Design, Singapore University of Technology and Design, Singapore
Yuan Wu, State Key Laboratory of Internet of Things for Smart City, University of Macau, Macao & Department of Computer and Information Science, University of Macau, Macao
Mohsen Guizani, Mohamed bin Zayed University of Artificial IntelligenceFollow

Document Type

Conference Proceeding

Publication Title

2022 International Wireless Communications and Mobile Computing

Abstract

With the vehicle-to-grid and computing capabilities, a parked electric vehicle (EV) has a dual role, namely being an energy prosumer as well as a computing node for accommodating computation-offloading services. This dual-role feature of EVs yields a new computing paradigm named Electric Vehicle Edge Computing (EVEC). To ease the implementation of EVEC, we propose a fine-grained EV management approach to jointly provide parking guidance for EVs and control their charging/discharging power in parking lots. We formulate a bilevel optimization problem where the top-level problem optimizes the matching between EVs and parking lots from the perspective of computation offloading, and the bottom-level problem optimizes the control of EV charging/discharging power from the view of power networks. We transform the bilevel optimization problem into a single-level form, which is a nonconvex mixed-integer nonlinear programming problem, and we further tackle it by linearization techniques. Finally, we provide numerical results to demonstrate the efficiency and effectiveness of our approach. © 2022 IEEE.

First Page

719

Last Page

724

DOI

10.1109/IWCMC55113.2022.9824253

Publication Date

7-19-2022

Keywords

Bilevel optimization, edge computing, electric vehicle, parking and power management, Air navigation, computation offloading, Electric vehicles, Integer programming, Nonlinear programming

Comments

IR Deposit conditions: non-described

Recommended Citation

X. Huang et al., "Joint Parking and Power Management for Electric Vehicle Edge Computing: A Bilevel Optimization Approach," 2022 International Wireless Communications and Mobile Computing (IWCMC), 2022, pp. 719-724, doi: 10.1109/IWCMC55113.2022.9824253.