IEEE Power & Energy Magazine - January/February 2015 - 47
✔✔ Passive transmission technologies: high-voltage ac
existing system. The assessment of the transmission technologies
required a thorough knowledge of the developments expected by
2050, which was provided by the relevant supporting task.
(HVac) and high-voltage dc (HVdc) cables, both submarine and underground; HVac and HVdc overhead
lines; high-temperature conductors; combined HVac/
HVdc transmission solutions; gas-insulated lines; and
superconductors
✔✔ Active transmission technologies: converters for
HVdc, both current-source converters and voltagesource converters; flexible ac transmission systems,
both shunt and series; phase-shifting transformers and
transformers with tap changers; protection and control
at both the substation and system levels.
Grid Architecture:
The Technology Assessment
All computational and simulation tasks need input data related
to the relevant technologies. To meet this need, a portfolio
of technologies (for generation, storage, transmission, and
demand) has been selected according to the impact of each on
transmission networks with regard to planning issues for 2050.
For the generation, storage, and transmission technologies, this
portfolio has been constructed based on the views of experts.
For demand-side technologies, a specific methodology has
been proposed that examines the criticality of the future demandside technology changes that will affect the transmission system
as of 2050. For each end use, this criticality has been assessed by
considering three different effects-volume, energy efficiency,
and controllability-that modify the load curve, both in terms of
energy and power (the load profile). The volume effect represents
typical consumption for a given end use. The energy efficiency
improvement effect measures any change in the typical energy
consumed by end use. The load controllability potential measures
the ability of a remote operator to control part of the load of a
given end use. The proposed approach has been designed in two
successive steps: first, end uses were selected based on the assessment of their criticality; then, for each of the retained end uses,
technologies-the factors driving the criticality-were identified.
As a consequence, the database is organized per technology, as follows:
✔✔ Generation and storage technologies: hydropower;
PV; concentrated solar power; wind power; geothermal;
gas turbines; hard coal and lignite, with or without CCS;
nuclear power; biomass and biogas; pumped hydro; compressed air energy storage; and electrochemical storage
✔✔ Demand-side technologies: electric vehicles; heat
pumps; and lighting, e.g., light-emitting diodes (LEDs)
and organic LEDs
Data Uncertainties and Contextualization
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Apart from the data-gathering process, two major difficulties have been addressed: uncertainty and contextualization.
✔✔ Uncertainty refers to the intervals of confidence of the
values for given variables. For example, the value of a
given variable in the year 2050 cannot be determined
with certitude, i.e., if one considers, for instance, a
value of 2,100 MW to be the maximum power for
a VSC station in 2050, the value should really be
expressed as 2,100 MW ± 10% or 2,080-2,265 MW
(meaning it may vary within a min-max interval). The
increasing uncertainty over time constituted a major
difficulty when assessing numerical values for several
data types, such as costs or technical performances.
✔✔ Contextualization refers to the different values that
could be taken by a variable depending on which
e-Highway2050 scenario is being looked at. For
example, in the 100% RES scenario (S4), in 2050 one
can expect that the installation costs of a VSC substation will be significantly different from those in a scenario in which renewables reach a lower penetration
level and thermal electricity generation is roughly at
the same level it is today. In the latter scenario, one
would expect that the installation costs of a VSC station would be higher than in the former.
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figure 13. Iterative development until constraints were resolved.
january/february 2015
ieee power & energy magazine
47
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