DocumentCode
115754
Title
Electric Vehicles aggregator optimization: a fast and solver-free solution method
Author
Vujanic, Robin ; Esfahani, Peyman Mohajerin ; Goulart, Paul ; Morari, Manfred
Author_Institution
Dept. of Inf. Technol. & Electr. Eng., ETH Zurich, Zurich, Switzerland
fYear
2014
fDate
15-17 Dec. 2014
Firstpage
5027
Lastpage
5032
Abstract
The increased presence of Electric Vehicles (EVs) within electricity distribution systems introduces new challenges to their reliability, since uncoordinated charging of large numbers of EV can result in overload of distribution lines or transformers. In order to manage this difficulty, entities called EV aggregators are introduced whose task is to schedule charging of the EV fleet while ensuring that network constraints are respected. In this paper we propose a solution method for the type of constrained optimization problems such aggregators must solve. Our method is simple to implement and is guaranteed to produce good and feasible solutions, while performing only lightweight centralized computations which do not require the use of additional - and often expensive - constrained optimization solvers. We show that the quality of solutions produced by our method improves as the number of EVs to be controlled is increased. In addition, the computation times remain very short even for large problem instances entailing several thousands EVs.
Keywords
electric vehicles; optimisation; EV aggregator; constrained optimization problem; electric vehicle aggregator; electricity distribution system; solution method; Batteries; Convergence; Couplings; Load modeling; Optimization; Schedules; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location
Los Angeles, CA
Print_ISBN
978-1-4799-7746-8
Type
conf
DOI
10.1109/CDC.2014.7040174
Filename
7040174
Link To Document