251 research outputs found
Cascading Power Outages Propagate Locally in an Influence Graph that is not the Actual Grid Topology
In a cascading power transmission outage, component outages propagate
non-locally, after one component outages, the next failure may be very distant,
both topologically and geographically. As a result, simple models of
topological contagion do not accurately represent the propagation of cascades
in power systems. However, cascading power outages do follow patterns, some of
which are useful in understanding and reducing blackout risk. This paper
describes a method by which the data from many cascading failure simulations
can be transformed into a graph-based model of influences that provides
actionable information about the many ways that cascades propagate in a
particular system. The resulting "influence graph" model is Markovian, in that
component outage probabilities depend only on the outages that occurred in the
prior generation. To validate the model we compare the distribution of cascade
sizes resulting from contingencies in a branch test case to
cascade sizes in the influence graph. The two distributions are remarkably
similar. In addition, we derive an equation with which one can quickly identify
modifications to the proposed system that will substantially reduce cascade
propagation. With this equation one can quickly identify critical components
that can be improved to substantially reduce the risk of large cascading
blackouts.Comment: Accepted for publication at the IEEE Transactions on Power System
Failure Localization in Power Systems via Tree Partitions
Cascading failures in power systems propagate non-locally, making the control
and mitigation of outages extremely hard. In this work, we use the emerging
concept of the tree partition of transmission networks to provide an analytical
characterization of line failure localizability in transmission systems. Our
results rigorously establish the well perceived intuition in power community
that failures cannot cross bridges, and reveal a finer-grained concept that
encodes more precise information on failure propagations within tree-partition
regions. Specifically, when a non-bridge line is tripped, the impact of this
failure only propagates within well-defined components, which we refer to as
cells, of the tree partition defined by the bridges. In contrast, when a bridge
line is tripped, the impact of this failure propagates globally across the
network, affecting the power flow on all remaining transmission lines. This
characterization suggests that it is possible to improve the system robustness
by temporarily switching off certain transmission lines, so as to create more,
smaller components in the tree partition; thus spatially localizing line
failures and making the grid less vulnerable to large-scale outages. We
illustrate this approach using the IEEE 118-bus test system and demonstrate
that switching off a negligible portion of transmission lines allows the impact
of line failures to be significantly more localized without substantial changes
in line congestion
Dual theory of transmission line outages
A new graph dual formalism is presented for the analysis of line outages in
electricity networks. The dual formalism is based on a consideration of the
flows around closed cycles in the network. After some exposition of the theory
is presented, a new formula for the computation of Line Outage Distribution
Factors (LODFs) is derived, which is not only computationally faster than
existing methods, but also generalizes easily for multiple line outages and
arbitrary changes to line series reactance. In addition, the dual formalism
provides new physical insight for how the effects of line outages propagate
through the network. For example, in a planar network a single line outage can
be shown to induce monotonically decreasing flow changes, which are
mathematically equivalent to an electrostatic dipole field.Comment: 8 pages, 3 figures, 1 table; Accepted at IEEE Transactions on Power
System
Failure Localization in Power Systems via Tree Partitions
Cascading failures in power systems propagate non-locally, making the control and mitigation of outages extremely hard. In this work, we use the emerging concept of the tree partition of transmission networks to provide an analytical characterization of line failure localizability in transmission systems. Our results rigorously establish the well perceived intuition in power community that failures cannot cross bridges, and reveal a finer-grained concept that encodes more precise information on failure propagations within tree-partition regions. Specifically, when a non-bridge line is tripped, the impact of this failure only propagates within well-defined components, which we refer to as cells, of the tree partition defined by the bridges. In contrast, when a bridge line is tripped, the impact of this failure propagates globally across the network, affecting the power flow on all remaining transmission lines. This characterization suggests that it is possible to improve the system robustness by temporarily switching off certain transmission lines, so as to create more, smaller components in the tree partition; thus spatially localizing line failures and making the grid less vulnerable to large-scale outages. We illustrate this approach using the IEEE 118-bus test system and demonstrate that switching off a negligible portion of transmission lines allows the impact of line failures to be significantly more localized without substantial changes in line congestion
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