![](bg6.png)
• E
w,h
: it measures the amount of wasted energy, in
Wh/year, at hour h, with h = 0, 1, 2, .., 23, in each
year. It is computed as:
E
w,h
=
1
Y
Y ·365·24
∑
t=0
t%24=h
E
(t)
w
(7)
where, as above, E
(t)
w
is the wasted energy at time
t, computed as in (3) and Y is the number of con-
sidered years.
5 SIMULATION RESULTS
In this section, we discuss the results of the simu-
lations, using the metrics presented above. Besides
the impact of the total installed RES capacity C
tot
on
these metrics, we also investigate the impact of its dis-
tribution between the PV panel capacity, S, and the
wind turbine capacity, W . In particular, we consider
C
tot
equal to 1 kW, 4 kW and 5 kW and we vary its
distribution among the solar and wind energy gen-
erator systems. The results are compared with our
benchmark, i.e., the scenario in which no RES is used
and the electricity needed for the BS supply is totally
taken from the grid. This means that E
b
is equal to
the annual BS energy consumption, which is, accord-
ing to our simulations, 5.1 MWh for San Siro BS and
5.6 MWh for the Train Station BS; E
w
is 0 MWh.
In Fig. 4, E
w
and E
b
, in blue and orange, respectively,
are plotted, for the Train Station BS, on the left, and
the San Siro BS, on the right. Each row of the fig-
ure considers different total RES installed capacity:
1 kW, in Figs. 4a, 4b, 4 kW in Figs. 4c, 4d and 5 kW
in Figs. 4e, 4f. On the left of each plot, only the so-
lar capacity is used, while moving towards right, so-
lar capacity diminishes by 0.5 kW and the capacity
of the wind turbine grows of 0.5 kW at each step,
i.e., at each group of bars. From Fig. 4, we first no-
tice that E
b
and E
w
significantly vary with different
C
tot
. Indeed, the energy bought from the grid, E
b
, de-
creases if the total capacity grows, from a maximum
of 5.56 MWh, when C
tot
is 1 kW, to a minimum of
0.93 MWh, when the capacity of RES is 5 kW. Sim-
ilarly, when the C
tot
becomes larger, the waisted en-
ergy, E
w
, rises, from 0 MWh, when C
tot
is 1 kW, to a
maximum of 4.97 MWh with C
tot
equals to 5 kW.
Results in Fig. 4 reveal that E
b
and E
w
are also af-
fected by the different distributions of these capacities
between the wind and solar systems. Indeed, given a
fixed total capacity C
tot
, if the portion of wind capac-
ity grows, E
b
decreases but E
w
increases. When C
tot
is
1 kW, the reduction of the E
b
is 17% and 18% with re-
spect to the chosen benchmark, in San Siro and Train
Station areas, respectively, if the capacity is totally
used as PV panel capacity. Meanwhile, E
b
reaches its
minimum value, dropping up to 34%, if all the capac-
ity is employed for the wind turbines. The situation is
different when C
tot
is larger. Indeed, when it is 4 kW,
for each considered BS, the minimum E
b
is reached
when the wind and the solar capacities are, respec-
tively, 3 kW and 1 kW. In this scenario, E
b
drops by
74% and 76%, for the BS in the Train Station and San
Siro areas, respectively. In this case, the annual E
w
is
1.43 MWh/year and 1.22 MWh/year, respectively.
Each curve in Fig. 5b represents E
w,h
, with
h = 1,2,...,24, i.e., the total amount of energy which
is wasted during a year at each hour of the day, for
the Train Station BS, for different W and S combina-
tions, given C
tot
equal to 4 kW. Values of E
w,h
close
to 0 MWh are given before 7.00 a.m. and after 7.00
p.m., for values of W lower than 1.5 kW, which im-
plies S larger than 2.5 kW (see light green, orange and
blue curves in Fig. 5b). This is because the PV panel
is not producing in these hours and the small capac-
ity of the wind turbine does not exceed in production
for the BS supply. Between 7.00 a.m. and 7.00 p.m.,
the PV panel produces energy because of the sun’s
presence. In this period of the day, the case with W
and S equal to 1.0 kW and 3.0 kW, respectively, pro-
vides the lowest E
w,h
, among the scenarios with W
and S, respectively, lower than 1.5 kW and larger than
2.5 kW. Quite the opposite occurs for E
b
,h, , with
h = 1,2,...,24, whose behaviour is plotted in Fig. 5a,
for different combinations of W and S, when C
tot
is
equal to 4 kW, for the Train Station BS. For values
of W larger than 2.5 kW and, consequently, S lower
than 1.5 kW, E
b,h
is no larger than 0.08 MWh, before
8.00 a.m. and after 6.00 p.m., as denoted by the pink,
grey and dark green curves in Fig. 5a. In the same
time interval, if W is lower than 2.5 kW and S larger
than 1.5 kW, E
b,h
increases up to z MWh. Between
8.00 a.m. and 6.00 p.m., because of the limited con-
tribution from the PV panel when its capacity is not
larger than 0.5 kW, E
b
,h grows up to 0.1 MWh, mak-
ing the scenario with solar and wind capacities equal
to 3.0 kW and 1.0 kW the best in terms of E
b
.
Nevertheless, as can be seen in Fig. 4c, if the tur-
bine has capacity 2.5 kW and the PV panel 1.5 kW,
the E
b
drops by 73% and 75% with respect to the
benchmark scenario, respectively, resulting therefore
slightly larger than the previous case, where, as men-
tioned, up to 74% and 76% of reduction is achieved.
Nevertheless, this reduces E
w
by 16% and 14%. Sim-
ilarly, when C
tot
is 5 kW, the hybrid solution, with
4 kW of wind capacity and 1 kW of solar one provides
the lowest amount of E
b
, as can be noticed in Figs. 4e
and 4f. It results no larger than 1.1 MWh/year, re-
SMARTGREENS 2021 - 10th International Conference on Smart Cities and Green ICT Systems
136