Distributed Hierarchical Coordination of Networked Charging Stations Based on Peer-to-Peer Trading and EV Charging Flexibility Quantification
Power systems are facing the challenges of integrating massive electric vehicles (EVs) and lacking operational flexibility. An optimal and efficient coordination strategy is needed to coordinate the operations among EV charging stations (CSs) and the distribution system operator (DSO) and to make fu...
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| Published in: | IEEE transactions on power systems Vol. 37; no. 4; pp. 2961 - 2975 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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New York
IEEE
01.07.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 0885-8950, 1558-0679 |
| Online Access: | Get full text |
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| Abstract | Power systems are facing the challenges of integrating massive electric vehicles (EVs) and lacking operational flexibility. An optimal and efficient coordination strategy is needed to coordinate the operations among EV charging stations (CSs) and the distribution system operator (DSO) and to make full use of the EVs' charging flexibility for improving the operational flexibility of power systems. To this end, this paper proposes a CSs-DSO distributed coordination strategy. The proposed strategy integrates a supply-curve-based quantification method to quantify the EVs' flexibility contribution and a Nash bargaining game-theory-based peer-to-peer (P2P) transactions model for maximizing the profits of entities participating in the coordination. To tackle the CSs-DSO coordination problem that has a bi-level-parallel coupling structure, an analytical target cascading (ATC) and alternating direction method of multipliers (ADMM) jointly-based distributed solution approach is proposed. First, the CSs-DSO bi-level model is decoupled by ATC with tie-line power being the only exchanged information; then, the model is further decomposed for each CS by ADMM for protecting the CSs' privacy and autonomy. The effect of coordination and the computational efficiency of the proposed strategy is verified by numerical simulations on a modified IEEE 33-bus distribution system connecting multiple CSs. |
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| AbstractList | Power systems are facing the challenges of integrating massive electric vehicles (EVs) and lacking operational flexibility. An optimal and efficient coordination strategy is needed to coordinate the operations among EV charging stations (CSs) and the distribution system operator (DSO) and to make full use of the EVs’ charging flexibility for improving the operational flexibility of power systems. To this end, this paper proposes a CSs-DSO distributed coordination strategy. The proposed strategy integrates a supply-curve-based quantification method to quantify the EVs’ flexibility contribution and a Nash bargaining game-theory-based peer-to-peer (P2P) transactions model for maximizing the profits of entities participating in the coordination. To tackle the CSs-DSO coordination problem that has a bi-level-parallel coupling structure, an analytical target cascading (ATC) and alternating direction method of multipliers (ADMM) jointly-based distributed solution approach is proposed. First, the CSs-DSO bi-level model is decoupled by ATC with tie-line power being the only exchanged information; then, the model is further decomposed for each CS by ADMM for protecting the CSs’ privacy and autonomy. The effect of coordination and the computational efficiency of the proposed strategy is verified by numerical simulations on a modified IEEE 33-bus distribution system connecting multiple CSs. |
| Author | Che, Liang Zhang, Jin Wan, Xin Shahidehpour, Mohammad |
| Author_xml | – sequence: 1 givenname: Jin surname: Zhang fullname: Zhang, Jin email: zhangjin1994@hnu.edu.cn organization: College of Electrical and Information Engineering, Hunan University, Changsha, Hunan, China – sequence: 2 givenname: Liang orcidid: 0000-0002-7004-6448 surname: Che fullname: Che, Liang email: lche@hawk.iit.edu organization: College of Electrical and Information Engineering, Hunan University, Changsha, Hunan, China – sequence: 3 givenname: Xin surname: Wan fullname: Wan, Xin email: 409595482@qq.com organization: Dadu River Hydropower Development Co. Ltd, Chengdu, Sichuan, China – sequence: 4 givenname: Mohammad orcidid: 0000-0002-8994-1688 surname: Shahidehpour fullname: Shahidehpour, Mohammad email: ms@iit.edu organization: Robert W. Galvin Center for Electricity Innovation, Illinois Institute of Technology, Chicago, IL, USA |
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| SubjectTerms | Coordination Couplings distributed optimization Distribution system electric vehicle Electric vehicle charging Flexibility game theory Mathematical analysis Mathematical models Optimization peer-to-peer Peer-to-peer computing Privacy Reactive power Security Strategy Topology |
| Title | Distributed Hierarchical Coordination of Networked Charging Stations Based on Peer-to-Peer Trading and EV Charging Flexibility Quantification |
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