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