  Plug-in electric vehicles (PEVs) are considered as flexible loads since their
charging schedules can be shifted over the course of a day without impacting
drivers mobility. This property can be exploited to reduce charging costs and
adverse network impacts. The increasing number of PEVs makes the use of
distributed charging coordinating strategies preferable to centralized ones. In
this paper, we propose an agent-based method which enables a fully distributed
solution of the PEVs Coordinated Charging (PEV-CC) problem. This problem aims
at coordinating the charging schedules of a fleet of PEVs to minimize costs of
serving demand subject to individual PEV constraints originating from battery
limitations and charging infrastructure characteristics. In our proposed
approach, each PEVs charging station is considered as an agent that is equipped
with communication and computation capabilities. Our multiagent approach is an
iterative procedure which finds a distributed solution for the first order
optimality conditions of the underlying optimization problem through local
computations and limited information exchange with neighboring agents. In
particular, the updates for each agent incorporate local information such as
the Lagrange multipliers, as well as enforcing the local PEVs constraints as
local innovation terms. Finally, the performance of our proposed algorithm is
evaluated on a fleet of 100 PEVs as a test case, and the results are compared
with the centralized solution of the PEV-CC problem.
