Data-Driven Planning of Electric Vehicle Charging Infrastructure: A Case Study of Sydney, Australia

With the increase of vehicle travelling range and the decrease of vehicle expense, Electric Vehicles (EVs) are gaining popularity as a new transport option which offers a great opportunity for creating a smart city in terms of transportation electrification. However, the existing research of EV char...

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Veröffentlicht in:IEEE transactions on smart grid Jg. 12; H. 4; S. 3289 - 3304
Hauptverfasser: Li, Chaojie, Dong, Zhaoyang, Chen, Guo, Zhou, Bo, Zhang, Jingqi, Yu, Xinghuo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 01.07.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Australia
Business competition
Case studies
charging infrastructure planning
Coders
Cournot competition
Data models
Economic analysis
Electric vehicle charging
Electric vehicles
Electrification
Encoders-Decoders
Game theory
Games
Global optimization
Infrastructure
multi-relation graph
Planning
Public transportation
Resource allocation
Roads
Sensors
Strategy
Sydney New South Wales Australia
Australia
ISSN:1949-3053, 1949-3061
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Zusammenfassung:With the increase of vehicle travelling range and the decrease of vehicle expense, Electric Vehicles (EVs) are gaining popularity as a new transport option which offers a great opportunity for creating a smart city in terms of transportation electrification. However, the existing research of EV charger planning primarily concentrates on the optimal location seeking from a perspective of global optimization. To achieve a competitive strategy in future, a market-based mechanism is proposed for the problem of EV charger planning with a case study of Sydney where a predict-then-optimise diagram is introduced to predict the EV charging demand by a multi-relation graph convolutional network (GCN)-based encoder-decoder deep architecture and optimise the competitive resource allocation strategy for the charger planning through a Cournot competition game model. A new parallel computational algorithm is proposed to seek the Cournot competition equilibrium with the convergence analysis. Furthermore, the optimal EV charger sizing problem is considered to obtain each service provider's EV charger number at each zone of the city. Experiments are implemented by using the Sydney public transportation dataset and the corresponding key economic indicators. The results show the effectiveness of our proposed approach which can fill the gap between data and the optimal EV charging infrastructure planning.
Bibliographie:ObjectType-Case Study-2
SourceType-Scholarly Journals-1
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ObjectType-Feature-4
ObjectType-Report-1
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ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2021.3054763