Title :
Resident electric vehicles charging optimization strategy in the smart grid
Author :
Ruiqin, Duan ; Zhongjing, Ma
Author_Institution :
School of Automation, Beijing Institute of Technology, and the National Key Laboratory of Complex System Intelligent Control and Decision, Beijing 100081, China
Abstract :
Considering the stochastic nature of electric vehicles (EVs) charging activities, this paper is dedicated to schedule the resident EVs charging load in the smart grid. Three important factors of the EV charging process are taken into account and studied, including the characteristics of EV battery, the start time of EV charging and the initial state-of-charging (SOC) of EV battery. We present a resident EVs charging optimization scheduling strategy to minimize the variation of total power load in the specified time period. And then we propose an approximate evaluation method for the corresponding optimization problem. The simulation results illustrate that the proposed EVs charging scheduling strategy will reduce the total power load curve difference of peak and valley, and the proposed method is very promising to improve the daily load profile of power system.
Keywords :
Batteries; Load modeling; Optimization; Power grids; Probability distribution; Stochastic processes; System-on-chip; Electric vehicle; Optimization scheduling; Probability model; Smart grid;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7261072