Title :
Electric vehicle charging scheduling under local renewable energy and stochastic grid power price
Author :
Tian Zhang ; Wei Chen ; Zhu Han ; Zhigang Cao
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Normal Univ., Jinan, China
Abstract :
In the paper, we consider delay-optimal charging scheduling of the electric vehicles (EVs) at a renewable energy aided charging station with multiple charge points. The uncertainty of the EV arrival, the intermittence of the renewable energy, and the variation of the grid power price are taken into account. In each period, the station determines the number of charging EVs during this period. Meanwhile, it also chooses the amount of renewables used for charging (the rest amount of energy will be purchased from the grid). The goal is to minimize the mean waiting time of EVs under the long-term constraint on the cost. We formulate a stochastic optimization problem, in which the charging EV number sequence and the allocated renewable energy sequence compose the two-dimensional optimization variable vector sequence, to investigate this scheduling problem. We derive the formal solution of the problem. Specifically, we prove that the optimal variable vector can be successively obtained: the optimal number of charging EVs is the solution of a reduced stochastic optimization problem and the greedy renewable energy allocation is optimal for given number of charging EVs. Finally, based on theoretical analysis, we propose two strategies for the problem and we investigate the proposed strategies numerically.
Keywords :
battery powered vehicles; greedy algorithms; hybrid electric vehicles; power grids; scheduling; secondary cells; stochastic programming; EV delay-optimal charging scheduling; greedy renewable energy allocation; local renewable energy sequence allocation; optimal variable vector; plug-in hybrid electric vehicle; rechargeable battery pack; renewable energy aided charging station; stochastic grid power price; stochastic optimization problem; Batteries; Charging stations; Optimization; Renewable energy sources; Resource management; Smart grids; Stochastic processes;
Conference_Titel :
Smart Grid Communications (SmartGridComm), 2014 IEEE International Conference on
Conference_Location :
Venice
DOI :
10.1109/SmartGridComm.2014.7007712