6,780 research outputs found
Optimal adaptive control of cascading power grid failures
We present theoretical results and experiments with parallel algorithms for
computing an adaptive, online control with the objective of attenuating a power
grid cascading failure.Comment: 2 figure
Mitigating Cascading Failures in Interdependent Power Grids and Communication Networks
In this paper, we study the interdependency between the power grid and the
communication network used to control the grid. A communication node depends on
the power grid in order to receive power for operation, and a power node
depends on the communication network in order to receive control signals for
safe operation. We demonstrate that these dependencies can lead to cascading
failures, and it is essential to consider the power flow equations for studying
the behavior of such interdependent networks. We propose a two-phase control
policy to mitigate the cascade of failures. In the first phase, our control
policy finds the non-avoidable failures that occur due to physical
disconnection. In the second phase, our algorithm redistributes the power so
that all the connected communication nodes have enough power for operation and
no power lines overload. We perform a sensitivity analysis to evaluate the
performance of our control policy, and show that our control policy achieves
close to optimal yield for many scenarios. This analysis can help design robust
interdependent grids and associated control policies.Comment: 6 pages, 9 figures, submitte
Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependency
Increased coupling between critical infrastructure networks, such as power
and communication systems, will have important implications for the reliability
and security of these systems. To understand the effects of power-communication
coupling, several have studied interdependent network models and reported that
increased coupling can increase system vulnerability. However, these results
come from models that have substantially different mechanisms of cascading,
relative to those found in actual power and communication networks. This paper
reports on two sets of experiments that compare the network vulnerability
implications resulting from simple topological models and models that more
accurately capture the dynamics of cascading in power systems. First, we
compare a simple model of topological contagion to a model of cascading in
power systems and find that the power grid shows a much higher level of
vulnerability, relative to the contagion model. Second, we compare a model of
topological cascades in coupled networks to three different physics-based
models of power grids coupled to communication networks. Again, the more
accurate models suggest very different conclusions. In all but the most extreme
case, the physics-based power grid models indicate that increased
power-communication coupling decreases vulnerability. This is opposite from
what one would conclude from the coupled topological model, in which zero
coupling is optimal. Finally, an extreme case in which communication failures
immediately cause grid failures, suggests that if systems are poorly designed,
increased coupling can be harmful. Together these results suggest design
strategies for reducing the risk of cascades in interdependent infrastructure
systems
Less is More: Real-time Failure Localization in Power Systems
Cascading failures in power systems exhibit non-local propagation patterns
which make the analysis and mitigation of failures difficult. In this work, we
propose a distributed control framework inspired by the recently proposed
concepts of unified controller and network tree-partition that offers strong
guarantees in both the mitigation and localization of cascading failures in
power systems. In this framework, the transmission network is partitioned into
several control areas which are connected in a tree structure, and the unified
controller is adopted by generators or controllable loads for fast timescale
disturbance response. After an initial failure, the proposed strategy always
prevents successive failures from happening, and regulates the system to the
desired steady state where the impact of initial failures are localized as much
as possible. For extreme failures that cannot be localized, the proposed
framework has a configurable design, that progressively involves and
coordinates more control areas for failure mitigation and, as a last resort,
imposes minimal load shedding. We compare the proposed control framework with
Automatic Generation Control (AGC) on the IEEE 118-bus test system. Simulation
results show that our novel framework greatly improves the system robustness in
terms of the N-1 security standard, and localizes the impact of initial
failures in majority of the load profiles that are examined. Moreover, the
proposed framework incurs significantly less load loss, if any, compared to
AGC, in all of our case studies
Stochastic Model for Power Grid Dynamics
We introduce a stochastic model that describes the quasi-static dynamics of
an electric transmission network under perturbations introduced by random load
fluctuations, random removing of system components from service, random repair
times for the failed components, and random response times to implement optimal
system corrections for removing line overloads in a damaged or stressed
transmission network. We use a linear approximation to the network flow
equations and apply linear programming techniques that optimize the dispatching
of generators and loads in order to eliminate the network overloads associated
with a damaged system. We also provide a simple model for the operator's
response to various contingency events that is not always optimal due to either
failure of the state estimation system or due to the incorrect subjective
assessment of the severity associated with these events. This further allows us
to use a game theoretic framework for casting the optimization of the
operator's response into the choice of the optimal strategy which minimizes the
operating cost. We use a simple strategy space which is the degree of tolerance
to line overloads and which is an automatic control (optimization) parameter
that can be adjusted to trade off automatic load shed without propagating
cascades versus reduced load shed and an increased risk of propagating
cascades. The tolerance parameter is chosen to describes a smooth transition
from a risk averse to a risk taken strategy...Comment: framework for a system-level analysis of the power grid from the
viewpoint of complex network
Statistical Classification of Cascading Failures in Power Grids
We introduce a new microscopic model of the outages in transmission power
grids. This model accounts for the automatic response of the grid to load
fluctuations that take place on the scale of minutes, when the optimum power
flow adjustments and load shedding controls are unavailable. We describe
extreme events, initiated by load fluctuations, which cause cascading failures
of loads, generators and lines. Our model is quasi-static in the causal,
discrete time and sequential resolution of individual failures. The model, in
its simplest realization based on the Directed Current description of the power
flow problem, is tested on three standard IEEE systems consisting of 30, 39 and
118 buses. Our statistical analysis suggests a straightforward classification
of cascading and islanding phases in terms of the ratios between average number
of removed loads, generators and links. The analysis also demonstrates
sensitivity to variations in line capacities. Future research challenges in
modeling and control of cascading outages over real-world power networks are
discussed.Comment: 8 pages, 8 figure
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