IEEE Power & Energy Magazine - July/August 2015 - 68
In this article, we demonstrate that effects of transmission
arrangements on consumer bills are significant, when a large
amount of RES is expected to connect.
Modeling Approach
We have applied our DTIM that has been enhanced to
facilitate optimal transmission network investment decision-making process under different levels of coordination
in integrating offshore wind generation and different levels
of EU market integration. Furthermore, the capability of
dealing with uncertainty in future generation deployment
has been included in the model. Within a holistic optimization process, DTIM balances costs of multiple transmission investment propositions against the associated costs of
system operation such as cost of congestion/constraints, cost
of wind curtailments, cost of network losses, and reliability
across multiyear time horizons. The DTIM explicitly optimizes offshore grid topology, and for this purpose we have
identified a large number of candidate corridors to be potentially constructed (and shown in Figure 9) and have used
advanced optimization techniques to identify network sections that should be built. All network asset investments are
structured on the basis of fixed and variable costs, enabling
the model to explicitly consider the effects of economies of
scale and hence to more accurately capture the fundamental differences between incremental and strategic network
investment philosophies. Uncertainty in offshore generation deployment in terms of time, location, and amount is
considered explicitly in this study through a min-max regret
approach. This is an important contribution given that all
existing North Seas grid studies have been based on deterministic analysis frameworks and have not explicitly considered the time dimension associated with offshore wind
deployment decisions.
The study considered four offshore wind development scenarios covering the period 2015-2040. We have
adopted a scenario tree approach, where a consistent set
of possible future developments is compiled and analyzed
to identify optimal investment commitments that would
lead to optimally robust performance across all envisaged
futures (considering that investment decision in the first
stage is made before uncertainty is resolved). The amount
of offshore wind generation across the different scenarios
and time scales considered in this study is presented in
Figure 10.
Key Findings
68
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2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
Baseload Power Price (£/MWh)
From Figure 11, we observe that, in the case of large-scale
deployment of offshore generation resources, coordination
through offshore hubs could deliver significant economic
benefits when compared to incremental point-to-point connections. As expected, benefits will depend on the scenario,
i.e., the amount of offshore wind generation deployed. For
a large penetration of offshore wind, savings in network
investment from coordinating connection of offshore wind
clusters are about €40 billion, while for small-scale deployment, benefits are about €8 billion. This is significant given
160
that the total asset value of the
present onshore, offshore, and
140
interconnection infrawstructure
120
associated with the regions of
the North Seas countries is esti100
mated to be below €60 billion.
Assessing the benefits of
80
establishing an offshore grid
60
through developing offshoreto-offshore links, and the inter40
action between offshore grid
Locational
Uniform
and interconnection, is one of
20
the key objectives of this study.
0
We observe that the benefits of
connecting offshore clusters via
a grid would be relatively modest in the energy neutral case
figure 6. The impact on power prices of uniform charging versus status quo
(a small increase in network
(£ nominal).
july/august 2015
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