4,638 research outputs found
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
Robust Network Routing under Cascading Failures
We propose a dynamical model for cascading failures in single-commodity
network flows. In the proposed model, the network state consists of flows and
activation status of the links. Network dynamics is determined by a, possibly
state-dependent and adversarial, disturbance process that reduces flow capacity
on the links, and routing policies at the nodes that have access to the network
state, but are oblivious to the presence of disturbance. Under the proposed
dynamics, a link becomes irreversibly inactive either due to overload condition
on itself or on all of its immediate downstream links. The coupling between
link activation and flow dynamics implies that links to become inactive
successively are not necessarily adjacent to each other, and hence the pattern
of cascading failure under our model is qualitatively different than standard
cascade models. The magnitude of a disturbance process is defined as the sum of
cumulative capacity reductions across time and links of the network, and the
margin of resilience of the network is defined as the infimum over the
magnitude of all disturbance processes under which the links at the origin node
become inactive. We propose an algorithm to compute an upper bound on the
margin of resilience for the setting where the routing policy only has access
to information about the local state of the network. For the limiting case when
the routing policies update their action as fast as network dynamics, we
identify sufficient conditions on network parameters under which the upper
bound is tight under an appropriate routing policy. Our analysis relies on
making connections between network parameters and monotonicity in network state
evolution under proposed dynamics
Evolution of Threats in the Global Risk Network
With a steadily growing population and rapid advancements in technology, the
global economy is increasing in size and complexity. This growth exacerbates
global vulnerabilities and may lead to unforeseen consequences such as global
pandemics fueled by air travel, cyberspace attacks, and cascading failures
caused by the weakest link in a supply chain. Hence, a quantitative
understanding of the mechanisms driving global network vulnerabilities is
urgently needed. Developing methods for efficiently monitoring evolution of the
global economy is essential to such understanding. Each year the World Economic
Forum publishes an authoritative report on the state of the global economy and
identifies risks that are likely to be active, impactful or contagious. Using a
Cascading Alternating Renewal Process approach to model the dynamics of the
global risk network, we are able to answer critical questions regarding the
evolution of this network. To fully trace the evolution of the network we
analyze the asymptotic state of risks (risk levels which would be reached in
the long term if the risks were left unabated) given a snapshot in time, this
elucidates the various challenges faced by the world community at each point in
time. We also investigate the influence exerted by each risk on others. Results
presented here are obtained through either quantitative analysis or
computational simulations.Comment: 27 pages, 15 figure
Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems
The first-ever Ukraine cyberattack on power grid has proven its devastation
by hacking into their critical cyber assets. With administrative privileges
accessing substation networks/local control centers, one intelligent way of
coordinated cyberattacks is to execute a series of disruptive switching
executions on multiple substations using compromised supervisory control and
data acquisition (SCADA) systems. These actions can cause significant impacts
to an interconnected power grid. Unlike the previous power blackouts, such
high-impact initiating events can aggravate operating conditions, initiating
instability that may lead to system-wide cascading failure. A systemic
evaluation of "nightmare" scenarios is highly desirable for asset owners to
manage and prioritize the maintenance and investment in protecting their
cyberinfrastructure. This survey paper is a conceptual expansion of real-time
monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework
that emphasizes on the resulting impacts, both on steady-state and dynamic
aspects of power system stability. Hypothetically, we associate the
combinatorial analyses of steady state on substations/components outages and
dynamics of the sequential switching orders as part of the permutation. The
expanded framework includes (1) critical/noncritical combination verification,
(2) cascade confirmation, and (3) combination re-evaluation. This paper ends
with a discussion of the open issues for metrics and future design pertaining
the impact quantification of cyber-related contingencies
From degree-correlated to payoff-correlated activity for an optimal resolution of social dilemmas
An active participation of players in evolutionary games depends on several
factors, ranging from personal stakes to the properties of the interaction
network. Diverse activity patterns thus have to be taken into account when
studying the evolution of cooperation in social dilemmas. Here we study the
weak prisoner's dilemma game, where the activity of each player is determined
in a probabilistic manner either by its degree or by its payoff. While
degree-correlated activity introduces cascading failures of cooperation that
are particularly severe on scale-free networks with frequently inactive hubs,
payoff-correlated activity provides a more nuanced activity profile, which
ultimately hinders systemic breakdowns of cooperation. To determine optimal
conditions for the evolution of cooperation, we introduce an exponential decay
to payoff-correlated activity that determines how fast the activity of a player
returns to its default state. We show that there exists an intermediate decay
rate, at which the resolution of the social dilemma is optimal. This can be
explained by the emerging activity patterns of players, where the inactivity of
hubs is compensated effectively by the increased activity of average-degree
players, who through their collective influence in the network sustain a higher
level of cooperation. The sudden drops in the fraction of cooperators observed
with degree-correlated activity therefore vanish, and so does the need for the
lengthy spatiotemporal reorganization of compact cooperative clusters. The
absence of such asymmetric dynamic instabilities thus leads to an optimal
resolution of social dilemmas, especially when the conditions for the evolution
of cooperation are strongly adverse.Comment: 8 two-column pages, 6 figures; accepted for publication in Physical
Review
Optimizing protections against cascades in network systems: A modified binary differential evolution algorithm
International audienceThis paper addresses the optimization of protection strategies in critical infrastructures within a complex network systems perspective. The focus is on cascading failures triggered by the intentional removal of a single network component. Three different protection strategies are proposed that minimize the consequences of cascading failures on the entire system, on predetermined areas or on both scales of protective intervention in a multi-objective optimization framework. We optimize the three protection strategies by devising a modified binary differential evolution scheme that overcomes the combinatorial complexity of this optimization problem. We exemplify our methodology with reference to the topology of an electricity infrastructure, i.e. the 380 kV Italian power transmission network. We only focus on the structure of this network as a test case for the suggested protection strategies, with no further reference on its physical and electrical properties
A failure management prototype: DR/Rx
This failure management prototype performs failure diagnosis and recovery management of hierarchical, distributed systems. The prototype, which evolved from a series of previous prototypes following a spiral model for development, focuses on two functions: (1) the diagnostic reasoner (DR) performs integrated failure diagnosis in distributed systems; and (2) the recovery expert (Rx) develops plans to recover from the failure. Issues related to expert system prototype design and the previous history of this prototype are discussed. The architecture of the current prototype is described in terms of the knowledge representation and functionality of its components
- …