Integrated modelling review - Modelling Distributed Energy Resources in Energy Service Networks - page 26

This methodology favours the use of network flow modelling techniques that can
incorporate potent algorithms [147]. Accordingly, the problem is solved by using
a generalised network simplex algorithm which performs a multi-period optimisa-
tion that minimises the overall costs of running the complex energy system, thus
guaranteeing the energy system operates for the benefit of all stakeholders.
An important approach taken in this work is the assumption that since each
energy infrastructure may have varying time scales, repetitive computations need to
be avoided. As a consequence, different time steps are defined for each subsystem,
thus eliminating the stress of redundant simulations [148].
More specifically, the optimisation model showcases the following contribu-
tions [149]:

Provides a reinterpretation of the electric power flow concept in terms of a
generic energy flow for multiple infrastructures;

●

Identifies the least cost flow patterns;

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Obtains the marginal costs for all nodal prices of energy;

●

Determines the extent to which emission restrictions affect the flow patterns;

●

Evaluates how the level of decentralisation of the decision-making processes
affects the economic performance of the whole energy system.

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The regional infrastructure integration research is relevant since it can advise
in key decision-making topics, including strategic planning, economic assessment,
logistics and regulatory policies [150]. In this manner, the modelling framework
achieves a basic understanding of true dynamics between interdependent systems,
undoubtedly serving as a guideline to model integrated energy systems. Still,
the biggest drawback from this approach is the disregard for calculating physical
flow properties; therefore, it omits technical details of the infrastructures - a not-
insignificant knowledge gap.

2.2.3 Modelling of energy hubs
The growing trend of energy companies to offer multiple services ( e.g. natural gas
and power) while having the ability to satisfy end-use services from different energy
infrastructures has motivated researchers to begin modelling multiple energy car-
riers to exploit delivery flexibility - generally under a greenfield approach [151].
This implies that energy systems are revisited without considering the limitations
provided by the current physical constraints, such as land use. Henceforth, this con-
cept has become known in the literature as energy hubs ; they are defined as core
units that function as the interface between DER technologies and integrated energy
interconnectors [152].
Taking the above principles, a generic modelling framework was introduced
solving the steady-state optimisation of energy systems considering multiple energy
vectors [62]. The model thoroughly details the physical properties of energy conver-
sion, storage and transmission of multiple carriers. Supply diversification and storage
grant more degrees of freedom to develop scenarios for the optimal supply of energy
using multi-criteria objectives. Thus, calculating diverse effects that will arise from
coupling different infrastructures through DERs is possible.