Title :
Aggregation Model-Based Optimization for Electric Vehicle Charging Strategy
Author :
Jinghong Zheng ; Xiaoyu Wang ; Kun Men ; Chun Zhu ; Shouzhen Zhu
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Abstract :
This paper presents an aggregation charging model for large numbers of electric vehicles (EVs). A genetic algorithm (GA) is employed to obtain the stochastic feature parameters of the aggregation model, and a charging strategy based on the aggregation model is developed to reduce the power fluctuation level caused by EV charging. In addition, an updatable optimization method is proposed to track the variation of the EV charging characteristics. The proposed charging strategy and optimization method are validated by the simulation results.
Keywords :
electric vehicles; genetic algorithms; stochastic processes; EV charging characteristics; GA; aggregation model-based optimization; electric vehicle charging strategy; genetic algorithm; power fluctuation level reduction; stochastic feature parameters; updatable optimization method; Batteries; Lithium; Load modeling; Optimization; Stochastic processes; System-on-chip; Vehicles; Aggregation model; electric vehicle; optimal charging; parameter estimation; stochastic distribution;
Journal_Title :
Smart Grid, IEEE Transactions on
DOI :
10.1109/TSG.2013.2242207
