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Joint Parking and Power Management for Electric Vehicle Edge Computing: A Bilevel Optimization Approach
2022 International Wireless Communications and Mobile Computing
  • 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 Intelligence
Document Type
Conference Proceeding
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.

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
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Citation Information
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.