  This paper investigates a decentralized optimization methodology to
coordinate Electric Vehicles (EV) charging in order to contribute to the
voltage control on a residential electrical distribution feeder. This aims to
maintain the voltage level in function of the EV's power injection using the
sensitivity matrix approach. The decentralized optimization is tested with two
different methods, respectively global and local, when EV take into account
their impact on all the nodes of the network or only on a local neighborhood of
their connection point. EV can also update their decisions asynchronously or
synchronously. While only the global approach with asynchronous update is
theoretically proven to converge, using results from game theory, simulations
show the potential of other algorithms for which fewer iterations or fewer
informations are necessary. Finally, using Monte Carlo simulations over a wide
range of EV localization configurations, the first analysis have also shown a
promising performance in comparison with uncoordinated charging or with a
"voltage droop charging control" recently proposed in the literature.
