Applications of Digital Twin System in a Smart City System with Multi-Energy

Qiang Lu, Huaiguang Jiang, Sisi Chen, Yi Gu, Tianlu Gao, Jun Zhang

Research output: Contribution to conferencePaper

6 Scopus Citations

Abstract

With the increasing number of electric vehicles (EV), the smart transportation system is becoming more closely related to the smart energy system in a smart city. However, because of the high complexity, dynamics, and large-scale of these two systems, it is challenging to study their operation problems systematically, especially in severe conditions, e.g., the 2021 winter Texas power traffic crisis. With artificial intelligence, federated learning, edge computing, and automatic control, a digital twin based smart city is proposed in this paper and it focuses on two applications: smart transportation and smart energy grid. Both systems are presented in a structured design manner with several components in the digital twin system, which also contains many real-implementations of different scenarios. The proposed digital twin of a smart city provides a potential clue for the problems mentioned above.
Original languageAmerican English
Pages58-61
Number of pages4
DOIs
StatePublished - 2021
Event2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI) - Beijing, China
Duration: 15 Jul 202115 Aug 2021

Conference

Conference2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI)
CityBeijing, China
Period15/07/2115/08/21

NREL Publication Number

  • NREL/CP-5D00-81258

Keywords

  • artificial intelligence
  • digital twin
  • edge computing
  • federated learning
  • smart energy system
  • smart grid
  • smart transportation system

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