Environmental Engineering Reference
In-Depth Information
Chapter 8
Concluding remarks
Further work in the field of distributed energy systems integrated to infrastructures
can take many directions; however, key prominence should be given first to strength-
ening the modelling principles used here in order to enhance the quality and depth
of results an integrated model can offer. For instance, the authors suggest incen-
tivised plug-in hybrid electric vehicle (PHEV) charging via power markets and its
corresponding commercial framework can now be better analysed once an analytical
tools, such as the one presented here are more prominent. Likewise, operational and
design network studies can be developed once PHEV load growth forecasting can be
determined more effectively.
8.1
Summary and contributions
This topic is motivated by the hypothesis that current energy management approaches
of utilities may lead to potential inefficiencies in the near future. This is because immi-
nent deployment of distributed energy resources (DERs) will begin the transformation
of utilities into a smarter grid, and this so-called smart-grid will require coordination
between monitoring systems, distributed generation technologies and other interde-
pendent infrastructures. As a result, a holistic analysis is required to enhance overall
system performance.
In order to address these issues, this text presents a framework for integrated
steady-state modelling and optimisation of energy service networks under the pres-
ence of embedded technologies. This application, referred to as TCOPF, conducts
the necessary steps to calculate both the optimal power flow of natural gas and elec-
trical networks and the optimal dispatch of PHEV and micro-CHP devices. Thus,
the TCOPF tool acts as a coordinating entity that manages cost-effective interactions
between distribution network operators and distributed energy resources.
Conceptually, the modelling of elements in the energy system is represented by
nodes and arcs. This approach explicitly considers the couplings of energy flows
occurring in the infrastructures through DER devices. Overall, the objective of the
optimisation solver is to guarantee the best possible solution for the whole energy
service system by simultaneously calculating the operating values of infrastructures
and embedded devices. Thus, the solver is holistic and unbiased when solving any
objective function proposed, giving no preference to any particular technology or
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