IEEE Power & Energy Magazine - September/October 2021 - 62

power system that meets reliability standards. The capacity
outlook is essentially solving an objective function, with the
objective being to reliably (defined by Australia's reliability
standards) meet the electricity demand for the NEM for the
next 25 years while minimizing cost, subject to several constraints,
such as the physical limitations of the existing generation
and transmission plant and carbon budgets.
A suite of models is then used to explore the optimization
problem through varying periods. This approach either
focuses on the entire outlook period or an enhanced representation
of the system at an intertemporal level. By taking this
approach, we can explore a range of operational characteristics
for each of the generation, storage, and demand response
solutions for the respective scenarios.
In practice, a capacity outlook model is a two-stage approach.
The first stage considers electricity and gas interdependencies
with a long-time horizon but has a coarse representation of time.
The second stage is a more granular model that provides chronological
and detailed representations of the long-term electricity
system by solving in multiple steps. Because this stage performs
a more complex optimization over a shorter horizon, it relies on
the foresight provided by the first-stage model.
To successfully run these models, we need to provide a
capacity outlook model of several fixed parameters, such as
electricity demand, new generator costs, or policy requirements.
We also need to supply several " candidate options "
for new generation and large transmission interconnection,
which can be selected by the capacity outlook to meet the
objective while addressing constraints.
Scenario Demand
and Energy
Forecasts
Scenario Drivers
(Policy, Emissions,
and so on)
Candidate REZ
and Generation
Parameters
Specifically, the capacity outlook contains parameters
for all 35 REZs, as described previously, which ensures that
the capacity outlook model is rich in detail when making
decisions on REZ transmission and generation development.
This ascertains that diversity among REZs is considered,
which can reduce the need for higher cost generation, such
as open-cycle gas turbines, to provide firming.
We generally found that new large interconnector candidates
that increase the transfer capacity among the major
load centers often have synergies with REZ network developments.
That is, a new interconnector between the major
cities often traverses or passes near multiple candidate
REZs. We, therefore, include the additional network capacity
provided to a REZ by interconnector expansion options
in the capacity outlook model.
Finally, the outputs of the capacity outlook model are
a set of generator, storage, and network investment decisions.
Those decisions reflect the interdependencies between
the gas and electricity systems to determine optimal thermal
generation investments; retirements; and transmission
expansion, gas field, and pipeline investment plans over the
longest time horizon (25 years or beyond).
To complete the capacity outlook, the allocation of generation
investments to specific locations in the network (typically
a specific network connection point in the REZ) needs to
occur (usually based on spare network capacity). We must do
this because the capacity outlook model presents a simplified
picture of the network topology, whereas the next stage of the
model uses a far more detailed representation of that topology.
Potential
Transmission
Projects
Generation and Transmission Expansion Model
Gas
Supply
Model
Generation
Expansion
Transmission
Expansion
Power
System
Analysis
Short-Term Time-Sequential Model
Dispatch Outcomes
figure 5. An overview of AEMO's modeling framework. (Source: AEMO; used with permission.)
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IEEE Power & Energy Magazine - September/October 2021

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