Electric Vehicles Aggregator Optimization: a Fast and Solver-Free Solution Method

R. Vujanic, P. Mohajerin Esfahani, P. J. Goulart and M. Morari

in IEEE Conference on Decision and Control, Los Angeles, CA, USA, pp. 5027-5032, December 2014.
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@inproceedings{VEGM:2014,
  author = {R. Vujanic and P. Mohajerin Esfahani and P. J. Goulart and M. Morari},
  title = {Electric Vehicles Aggregator Optimization: a Fast and Solver-Free Solution Method},
  booktitle = {IEEE Conference on Decision and Control},
  year = {2014},
  pages = {5027-5032},
  url = {http://dx.doi.org/10.1109/CDC.2014.7040174},
  doi = {10.1109/CDC.2014.7040174}
}

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 guaran- teed 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.