Environmental Engineering Reference
In-Depth Information
Based on the combination of different flows that satisfy the power needs in node
k
,
the non-PHEV load can be classified as the conventional electricity demands in an
urban area (
e.g.
residential and/or commercial), this term can be expressed as:
W
phev
k
W
chp
k
Gk
P
phev
Gk
P
chp
P
urban
Dk
P
total
Dk
=
−
·
−
·
(4.47)
The values of injections
P
phev
Gk
and
P
chp
Gk
for each time interval will be determined
by the TCOPF tool according to its objective function and set of constraints.
Subsequently, the total electric power load end-users' need in node
k
can be
satisfied by coordinating all possible power sources, and it is stated as:
W
phev
k
W
chp
k
Gk
P
phev
Gk
P
chp
P
total
Dk
P
urban
Dk
=
+
·
+
·
(4.48)
Equation (4.48) guarantees that the total electrical power obtained from the
grid and distributed resources at predefined efficiencies will entirely satisfy the load
demand in node
k
at each time interval.
4.4.3 Electrochemical energy storage management equations
As mentioned before, the two types of battery technologies most applied when desig-
ning electric vehicles are lithium-based and nickel-based. However, the scope of this
work does not cover battery circuit models and instead solely focuses on schedul-
ing G2V and V2G power injections. Hence, the storage management equations
presented here apply for any battery technology.
Under present battery capacities and travel surveys, the battery system is likely
to incur in at least one deep discharge cycle every one or two days, resulting in a
couple thousands of discharge cycles in the lifetime of the battery [119]. Because of
these circumstances, the range of batteries and their SOC need to be appropriately
modelled for power system studies. Electrical engineering literature suggests that the
modelling of batteries does not distance itself much from hydro power plant schedul-
ing [121]. There has been significant work in organising fuel deliveries and water
resources in order to optimise electric energy production [211]. The hydrothermal
coordination problem is aimed at solving thermal unit commitments and economic
load dispatch simultaneously with the hydro schedules [212]. By adopting hydrother-
mal principles, batteries can be modelled using a similar approach, thus giving the
TCOPF tool flexibility to evaluate different energy management strategies for fleets
of PHEVs.
In this text, electrochemical energy storage modelling is approached by applying
a piece-wise time optimisation. This optimisation approach is somewhat analogous
to the TES modelling applied for CHP technology in section 4.3.
For simplicity sake, the batteries of a PHEV fleet within a particular node are
modelled as a single concentrated battery. This implies that the nodal electrochemical
capacity is an aggregated quantity which is equal to the sum of all individual batter-
ies. Additionally, the charging and discharging constraints of the PHEVs need to be
satisfied at each time interval, while the global constraints for these variables must be
met for the entire period being analysed.
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