Per aspera ad astra. How electric vehicles (EVs) got to where they are today could be explained
with that one phrase. This place, where they are today, is synonymous with technology,
innovation and luxury in the motoring world, which, for the same reasons, is still out of reach
for many. On the one hand, this technology is largely dependent on the electric power system,
and on the other, the state of the system largely depends on the number and distribution of
vehicles. Therefore, the stability and reliability of the energy system is extremely important, both
for EVs and for all other consumers.
For this purpose, the thesis will discuss different EV charging and discharging strategies in order
to gain insight into the impact of EVs on the state of the grid. At the beginning, we will look at
the operation of the network in the case of uncontrolled charging. This will be followed by a
look at the benefits brought to us by smart (controlled) charging.
We will conclude the overview of different charging strategies by using the Vehicle-to-Grid
(V2G) concept, which represents a step further compared to smart charging. For this purpose,
the simulations will be carried out in the Matlab environment, with the indirect use of OpenDSS.
Based on statistical data such as profiles, duration and length of trips, we will determine the load
diagram of the EV. The simulations will be performed on a representative sample of the low-
voltage network, but the results obtained in this way can later be generalized to a wider area.
The network consists of 97 consumers and is powered by a distribution transformer with
21/0.42 kV ratio. We will perform several simulations for different charging strategies and based
on this, we will evaluate the impact of EVs on the power system and how the V2G concept
helps to relieve the grid.
As a result of the thesis, we expect a set of different results that clearly show what happens in
the network for different charging strategies. In the case of uncontrolled charging, when
consumers simply connect to the grid and charge EVs whenever they want, we expect additional
load on the transformer. If we generalize the result to a wider area, it would mean that the entire
network is overloaded, which in the extreme case, can lead to its outage. On the other hand, in
the case of controlled charging, we will follow the concept of smart charging, which means that
we will "encourage" consumers to charge EVs exclusively at night, when the network is free of
load. At that point we expect the day and afternoon peaks to remain at the same height, until
the rest of the chart increases accordingly. Above all, we keep in mind the part which represents
energy needs from 10 p.m. to 6 a.m.
The last example will refer to the application of the V2G concept. At that time, we expect
somewhat even consumption during the day, which is achieved by flattening. In other words,
the vehicles will be charging at times when the network conditions are favorable, which means
that the consumption diagram for those parts of the day will increase. On the other hand, during
peak times, vehicles will discharge and return energy back to the grid. In this case, the grid sees
EVs as additional sources rather than consumers. As a result, the morning and evening peaks
will decrease to a certain extent and in this way, the network will be relieved. With this, we
achieve that the consumption diagram is somewhat constant during the day, while the actual
need for energy varies considerably.
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