Environmental Engineering Reference
In-Depth Information
Table 7.1
Techno-economical case study parameters
Electric network
Number of nodes
=
4
topology
Number of branches
=
3
V
1
=
1
∠
0
◦
Electric slack node
Admittances
Y
12
=
Y
23
=
Y
34
=
205
.
29
−
j
38
.
17
Electric nodes,
α
=
1, 2, 3, 4
0
.
94
≤
V
α
≤
1
.
06
0
.
95
≤|
t
|
1
≤
1
.
05
Tap-changer
P
phev
D
,
max
=
3
.
12 kW
el
PHEV capacity per unit
EVSOC
store
max
=
24 kW
el
Battery capacity per unit
P
F
=
10
P
G
1
+
0
.
10
P
G
1
DNO operation scenarios 1 and 2
Carbon price scenarios 1 and 2
£12
/
tonne
Weekday spot price scenario 1 and 2
£72
.
71
/
MWh
Weekend spot price scenario 1 and 2
£64
.
70
/
MWh
P
F
=
20
P
G
1
+
0
.
20
P
G
1
DNO operation scenario 3
Carbon price scenario 3
£60
/
tonne
Weekday spot price scenario 3
£86
.
67
/
MWh
Weekend spot price scenario 3
£68
.
30
/
MWh
Table 7.2
Distances travelled per day and battery status at end of day
Day of the
Average
Minimum
Maximum
Battery SOC (%)
week
(miles)
(miles)
(miles)
Thursday
24.83
6.33
61.73
74.64
Friday
31.78
7.50
73.16
67.56
Saturday
23.55
3.41
66.46
75.96
end of the period (
i.e.
6 a.m.) if no charging takes place. As the table details, there
is a substantial difference between agents due to the stochastic patterns in vehicle
use. This means some agents barely use their battery capacity, while others have
more travelling requirements. On average, vehicles are used more on Friday as agents
combine work and leisure activities throughout the day.
Table 7.3 gives ABM results that are useful for energy stakeholders to deter-
mine PHEV load flexibility, including total amount of energy consumed by batteries
as well as their plug-in factor (
i.e.
percentage of vehicles connected to grid). The plug-
in factor is highly dependent on the time of day, varying from about 30% when the
majority of vehicles are on the road up to 100% during most of the night - because all
agents are vehicles owned by residential users. The total amount of energy used over
the day is the energy that has to be supplied by the network, while the plug-in fac-
tor gives one of the constraints for when it might be possible for PHEVs to charge.
Since vehicles are used most on Friday, the energy consumed this day is greater and
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