Distributed Dynamic Tariff for Congestion Management in Distribution Networks Considering Temporal-Spatial Coordination of Electric Vehicles

A distributed dynamic tariff (DDT) method was proposed in this study for congestion management in distribution networks considering the temporal-spatial coordination of electric vehicles (EVs). First, a quadratic DT-based congestion management model was formulated considering the full travel route a...

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Bibliographic Details
Published in:IEEE transactions on transportation electrification 2024-09, Vol.10 (3), p.7358-7373
Main Authors: Shen, Feifan, Lin, Siyao, Wei, Juan, Huang, Sheng, Wu, Qiuwei, Shen, Yangwu, Zhu, Lipeng, Wang, Pengda, Wang, Bozhong
Format: Article
Language:English
Subjects:
Congestion
Congestion management
Coordination
distributed optimization
Distribution networks
dynamic tariff (DT)
electric vehicle (EV)
Electric vehicle charging
Electric vehicles
Indexes
Information management
Optimization
Partial discharges
Power system dynamics
Spatial distribution
Tariffs
Transportation
Transportation networks
Travel time
Vehicle dynamics
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Summary:A distributed dynamic tariff (DDT) method was proposed in this study for congestion management in distribution networks considering the temporal-spatial coordination of electric vehicles (EVs). First, a quadratic DT-based congestion management model was formulated considering the full travel route as well as the charging and discharging (C&D) behavior of EVs in the transportation network (TN). Second, a distributed congestion management framework based on the asynchronous distributed alternating direction method of multipliers (AD-ADMM) was introduced. Using the proposed framework, DDTs were iteratively optimized between the distribution system operator (DSO) and aggregators to achieve optimal EV routing in the TN and congestion management in the distribution network. Finally, case studies were conducted on two test systems, and the numerical results showed that the proposed DDT method can optimize the temporal-spatial distribution of EVs in the TN, minimize the travel time and C&D costs of EVs in each aggregator, and effectively avoid congestion in the distribution network. Moreover, the optimization efficiency and privacy information protection of aggregators in the DT-based congestion management method could be improved.
ISSN:2332-7782
2577-4212
2332-7782
DOI:10.1109/TTE.2023.3332892