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 language | American English |
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Pages | 58-61 |
Number of pages | 4 |
DOIs | |
State | Published - 2021 |
Event | 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI) - Beijing, China Duration: 15 Jul 2021 → 15 Aug 2021 |
Conference
Conference | 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI) |
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City | Beijing, China |
Period | 15/07/21 → 15/08/21 |
NREL Publication Number
- NREL/CP-5D00-81258
Keywords
- artificial intelligence
- digital twin
- edge computing
- federated learning
- smart energy system
- smart grid
- smart transportation system