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
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;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7040174