Title :
A decentralized optimization method to track electric vehicle aggregator´s optimal charging plan
Author :
Zhengshuo Li ; Qinglai Guo ; Hongbin Sun ; Shujun Xin
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Abstract :
Many papers focus on electric vehicle (EV) aggregators´ participating in the operation of transmission grid, but the practical interaction of EVs and power grid is implemented through charging every single EV. Therefore, it´s necessary to make hundreds or thousands of EVs optimally charge to track an aggregator´s optimal charging plan assigned by the power grid. In this paper, this tracking problem is formulated firstly and then a decentralized optimization method is proposed to solve this problem of which the size is usually too large to solve efficiently in a centralized way. The optimality of the method is proved under certain conditions. Case study for a simple scenario and numerical tests with various EV numbers show that the proposed method is not only optimal but also scalable.
Keywords :
battery powered vehicles; optimisation; power grids; power system planning; secondary cells; decentralized optimization method; electric vehicle aggregator optimal charging plan; optimal charging plan tracking; tracking problem; aggregator; decentralized optimization; electric vehicle; tracking problem;
Conference_Titel :
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location :
National Harbor, MD
DOI :
10.1109/PESGM.2014.6939181