Hierarchical Distributed Control Strategy for Electric Vehicle Mobile Energy Storage Clusters

Mei Wu, Yu-Qing Bao, Gang Chen, Jinlong Zhang, Beibei Wang and Weixing Qian
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Mei Wu: NARI School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing 210023, China
Yu-Qing Bao: NARI School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing 210023, China
Gang Chen: State Grid Suqian Power Supply Company, Suqian 223800, China
Jinlong Zhang: NARI School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing 210023, China
Beibei Wang: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Weixing Qian: NARI School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing 210023, China

Energies, 2019, vol. 12, issue 7, 1-14

Abstract: The stability problem of the power system becomes increasingly important for the penetration of renewable energy resources (RESs). The inclusion of electric vehicles (EVs) in a power system can not only promote the consumption of RESs, but also provide energy for the power grid if necessary. As a mobile energy storage unit (MESU), EVs should pay more attention to the service life of their batteries during operation. A hierarchical distributed control strategy was proposed in this paper for mobile energy storage clusters (MESCs) considering the life loss of each EV’s battery. This strategy was divided into a two-layer control structure. Firstly, numerous EVs were divided into different clusters according to their regional relationships. The lower layer adopted a distributed collaborative control approach for allocating energy among EVs in the cluster. Under this condition, an aggregate EVs response model was established and the characteristic of the MESC was analyzed. Secondly, the upper layer applied the multi-agent consensus algorithm to achieve the optimal allocation among different clusters. Therefore, the control strategy realized the two-way communication of energy between EVs and the power grid, and ensured the optimal economical dispatch for the mobile energy storage system (MESS). Finally, the simulation of testing examples verified the effectiveness of the proposed strategy.

Keywords: mobile energy storage system (MESS); multi-agent; consensus algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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