DocumentCode :
1465493
Title :
A Methodology for Optimization of Power Systems Demand Due to Electric Vehicle Charging Load
Author :
Peng Zhang ; Kejun Qian ; Chengke Zhou ; Stewart, Brian G. ; Hepburn, Donald M.
Author_Institution :
Sch. of Eng. & Built Environ., Glasgow Caledonian Univ., Glasgow, UK
Volume :
27
Issue :
3
fYear :
2012
Firstpage :
1628
Lastpage :
1636
Abstract :
This paper presents a methodology of optimizing power systems demand due to electric vehicle (EV) charging load. Following a brief introduction to the charging characteristics of EV batteries, a statistical model is presented for predicting the EV charging load. The optimization problem is then described, and the solution is provided based on the model. An example study is carried out with error and sensitivity analysis to validate the proposed method. Four scenarios of various combinations of EV penetration levels and charging modes are considered in the study. A series of numerical solutions to the optimization problem in these scenarios are obtained by serial quadratic programming. The results show that EV charging load has significant potential to improve the daily load profile of power systems if the charging loads are optimally distributed. It is demonstrated that flattened load profiles may be achieved at all EV penetration levels if the EVs are charged through a fast charging mode. In addition, the implementation of the proposed optimization is discussed with analyses on the impact of travel pattern and the willingness of customers.
Keywords :
battery powered vehicles; power systems; quadratic programming; sensitivity analysis; EV battery; EV charging load prediction; daily load profile improvement; electric vehicle charging load prediction; load profile; numerical solution; optimization methodology; power system demand; sensitivity analysis; serial quadratic programming; statistical model; Batteries; Companies; Optimization; Power demand; System-on-a-chip; Vehicles; Electric vehicle (EV); load modeling; power demand; quadratic programming;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2012.2186595
Filename :
6165683
Link To Document :
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