operation mode of the charging station are detailed in (Sedano
et al., 2013). Fig. 1 shows the schema of the distribution grid, which
is designed to be installed in a private community park where each
user has his own space. The design criteria of the control system
were based on simplicity, economy and maintenance easiness.
The grid is fed by a three-phase source of electric power with a
voltage between phases of 400 V. Each charging point is connected
to one single-phase and supplies energy at 230 V and 2.3 kW
(Sedano et al., 2013). So, for a given contracted power, there can
be a maximum number of vehicles charging in a line at the same
time. Also, the consumption in the three lines should not be too
different at any time. Otherwise, the net is imbalanced and there
is current in the neutral point. This causes higher losses than those
of a balanced system and lowers the energy transmission effi-
ciency. Moreover, the Spanish regulations (BOE, 2013) do not allow
the installation of devices that produce large imbalances without
the consentient of the supplier company, which can penalize the
customer for it.
The station is controlled by a distributed system composed of a
master and a number of slaves. Each slave controls two consecutive
charging points in the same line. The master accesses the database
where the vehicles’ data and the charging schedule are stored.
It gathers information about the demanding vehicles from the
slaves, and sends connection/disconnection orders to them. So
the slaves are responsible for activating and deactivating charging
points as well as recording asynchronous events such as a new
vehicle arriving to the system. When entering in the station, the
user parks the vehicle in his own space (as he cannot use the space
of another user) and connects the vehicle to the charging point.
Then, he has to provide the charging time and the time he will take
the vehicle away (due date). From these data, the control system
schedules the charging times of the vehicles. The objective is in
principle that all users can be served by their due dates.
However this is not always possible and in that case what we try
to do is minimize the overall time beyond the due dates for all
users; i.e., the total tardiness. Of course, other objective functions
could be considered instead as, for example, the maximum tardiness
in order to not penalize a particular user in excess with
respect to the remaining ones.
In this paper we consider a simplified model of the operating
mode of the charging station that makes the following assumptions:
the user never takes the vehicle away before the due date
and the battery does not get completely charged before the
charging time provided by the user. These are in fact unrealistic
assumptions, however the model may be adapted by introducing
new asynchronous events if they do not hold.
Each time a new vehicle requires charging, a new schedule
should be build. In principle, the system could try to accommodate
the new vehicle without changing the schedule for the remaining
vehicles in the system. However, this may not be the best option.
So, in order to obtain a new feasible schedule as good as possible,
all vehicles in the system that have not yet started to charge may
be rescheduled, and a new schedule is build with these vehicles
together with the new ones. In this process, the available resources
determined by the contracted power, the imbalance constraints
and the vehicles that are currently charging, must be taken into
account to build the new schedule.
Moreover, in order to avoid the system to collapse if, for example,
many vehicles arrive in a very short period of time, new schedules
are built at regular time intervals. In order to do that, after
every time interval DT (typically 120 s) or larger, a supervisor program
running on the server checks for the events produced in the
last interval. If at least one event was produced then the scheduler