Paper Info
Title
Optimization based AIMD saturated algorithms for public charging of electric vehicles
Abstract
The Additive Increase Multiplicative Decrease (AIMD) algorithm is an interesting approach in congestion control of communication networks, as it maintains the good features of a distributed strategy, without sacrificing the network stability and robustness. Recent applications of these algorithms also concern other industrial fields such as Electric Vehicles (EVs) based transportation systems, for which the introduction of an optimal charging policy is an important challenge for power systems operation. Moreover, saturation constraints on the resource allocated to each vehicle need to be taken into account in order to avoid peak power requirements and grid overloads. Optimization based AIMD algorithms with saturation constraints are proposed in this paper for public charging of EVs. Specifically, a new AIMD approach is presented in order to capture the main advantages of optimal algorithms which minimize either the sum of charging times or the operation time of each vehicle, giving rise to a mixed AIMD strategy. Simulation results illustrate the performance of the proposal, even in comparison to the corresponding centralized optimal solutions.
Year
DOI
Venue
2019
10.1016/j.ejcon.2018.12.009
European Journal of Control
Keywords
Field
DocType
AIMD,Distributed control,Electric vehicles,Optimal scheduling,Distributed management
Saturation (chemistry),Telecommunications network,Control theory,Electric power system,Algorithm,Robustness (computer science),Network congestion,Grid,Mathematics,Additive increase/multiplicative decrease
Journal
Volume
ISSN
Citations 
47
0947-3580
1
PageRank 
References 
Authors
0.35
10
4
Name
Order
Citations
PageRank
Saqib Nisar Shah110.35
Gian Paolo Incremona2709.40
Paolo Bolzern330430.90
Patrizio Colaneri495090.11