A Decentralized Power Allocation Strategy for the EV Charging Network

nowadays, developing electric vehicles (EVs) is an important measure to reduce the greenhouse effect of the traditional transportation system. While the number of EVs growing rapidly, how to charge EVs efficiently attracts researchers’ attention. Different from the traditional centralized charging power allocation, which is operated by a centralized control computer collecting all information and sending the commands to EVs, in this paper the decentralized power allocation strategy for EV charging network is proposed. Moreover, the centralized algorithm requires a high quality communication network, which cannot handle disturbances in communication like delays or packet losses. Therefore, the consensus algorithm is applied here to realize the efficiency and robust power allocation of the EV charging network in a decentralized fashion. The effectiveness of the proposed strategy has been fully investigated in three different cases.

[1]  Jian-Xin Xu,et al.  Consensus Based Approach for Economic Dispatch Problem in a Smart Grid , 2013, IEEE Transactions on Power Systems.

[2]  Luc Moreau,et al.  Stability of multiagent systems with time-dependent communication links , 2005, IEEE Transactions on Automatic Control.

[3]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[4]  Mo-Yuen Chow,et al.  Convergence Analysis of the Incremental Cost Consensus Algorithm Under Different Communication Network Topologies in a Smart Grid , 2012, IEEE Transactions on Power Systems.

[5]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[6]  Wei Ren,et al.  Information consensus in multivehicle cooperative control , 2007, IEEE Control Systems.

[7]  G. Hug,et al.  Distributed robust economic dispatch in power systems: A consensus + innovations approach , 2012, 2012 IEEE Power and Energy Society General Meeting.

[8]  Mo-Yuen Chow,et al.  Incremental cost consensus algorithm in a smart grid environment , 2011, 2011 IEEE Power and Energy Society General Meeting.