IEEE Power & Energy Magazine - January/February 2015 - 67

that are capable of determining remedial measures for maintaining system security at minimal cost. to provide system operators
with adequate action recommendations, it is of special significance that these algorithms take into account all available remedial measures as well as all relevant contingencies. In particular,
relatively new technologies with great influence on power flows,
such as hVdc connections operated in parallel to the asynchronous grid and phase-shifting transformers, are considered
along with conventional measures like topology modifications
and redispatch. the new options in transmission grid operation
resulting from the increased controllability of load flow control
devices in contingency situations are optimized as corrective
remedial measures and provide significantly increased flexibility to transmission system operators in stressed grid situations.
uncertainties resulting from error-prone feed-ins of renewable
energy sources, however, can lead to deviations from anticipated
system states. a reasonable way to deal with this issue is to postpone the activation of remedial actions as long as possible and
react only if critical deviations from anticipated system states
actually occur. a short-term optimization algorithm has therefore been developed that takes into account measures available
in the very short term as well as real-time constraints. nevertheless, it is crucial for system security to avoid unmanageable
system situations. to deal with this issue, probabilistic optimization algorithms have also been developed that are capable of
directly incorporating uncertainties into the operational planning
process. In this way, it is possible to make optimal power plant
start-up decisions-decisions that must be made as much as 24
hours before the actual operation (see figure 5).

and safety of network operation, especially in cases of increased
power flows through existing transmission system infrastructure. Sumo's other goal is to optimize the usage of the infrastructure: as mentioned above, higher line rating enables higher
line loading and, combined with the active use of pSts, this
leads to optimal grid employment.
the basic tool used is Dtr or, more specifically in the
case of power lines, dynamic thermal line rating (DtLr).
Dealing with the problem of defining Dtr from the perspective of a power system as a whole is the main novelty
introduced by the Sumo system. for real-time application,

Midscale
Meteorological
Model

Model

Grid

Weather
Measurements

A New Application for Network
Reliability and Safety

. . .

many studies have shown that in most day-to-day power
grid operation situations, weather parameters allow for
dynamically calculated maximum current carrying capaci- figure 8. The weather-gridding process.
ties (CCCs) that are higher than the
traditionally set static ones. In theory, this allows for better utilizaInput Data
DLR Calculation
tion of the existing grid. It should
be noted that in some situations,
Weather Data
Calculation
Ta(t), v (t),
Im1
of IDLR for
dynamically calculated CCCs are
δ (t), S(t)
Section 1
also lower than the static ones;
power grid operations relying on
dynamically calculated CCCs
Calculation
Line Current
min(IDLR1...IDLRn)
of IDLR for
Im2
must take this into account (see the
I(t)
Section 2
comparison of static and dynamic
ratings in figure 6). figure 1
shows results obtained from a test
Calculation
polygon for comparing different
Result
Imn
of IDLR for
dynamic thermal rating (Dtr)
Section n
technologies.
Line Rating
I DLR(t)
the aim of the new system for
assessment of operational limits
(whose Slovenian acronym is
Sumo) is to improve the reliability figure 9. The general principle of dynamically determining line rating.
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