scispace - formally typeset
Open AccessJournal ArticleDOI

Emergence of Scale-Free Blackout Sizes in Power Grids

Reads0
Chats0
TLDR
A new mathematical framework combining the physics of power flow with rare event analysis for heavy-tailed distributions is presented, and is validated using various synthetic networks and the German transmission grid.
Abstract
We model power grids as graphs with heavy-tailed sinks, which represent demand from cities, and study cascading failures on such graphs. Our analysis links the scale-free nature of blackout sizes to the scale-free nature of city sizes, contrasting previous studies suggesting that this nature is governed by self-organized criticality. Our results are based on a new mathematical framework combining the physics of power flow with rare event analysis for heavy-tailed distributions, and are validated using various synthetic networks and the German transmission grid.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Collective nonlinear dynamics and self-organization in decentralized power grids

TL;DR: In this paper , the authors show that mathematically modeling grids as coupled nonlinear dynamical systems and networks, and utilizing concepts from statistical physics and graph theory provide a comprehensive framework to understand and control their collective behavior as a system of many interacting units.
Journal ArticleDOI

Topological theory of resilience and failure spreading in flow networks

TL;DR: This work uses a spanning tree formulation of link failures in linear flow networks to analyse topological structures that prevent failures spreading and identifies three strategies based on the network topology that allow to reduce the impact of single link failures.
Journal ArticleDOI

A Cascading Failure Model Considering Operation Characteristics of the Communication Layer

TL;DR: In this paper, a cascading failure model of a cyber physical power system (CPPS) that considers the operation characteristics of the communication layer, especially the influence of transmission delay and connectivity on stability control is introduced.
Posted Content

Power-grid stability predictions using transferable machine learning

TL;DR: In this paper, three machine learning algorithms (random forest, support vector machine, and artificial neural network) were used to predict the synchronization stability of power-grid nodes when they are trained with the heterogeneous input-power distribution than the homogeneous one.
References
More filters
Journal ArticleDOI

Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Journal ArticleDOI

Emergence of Scaling in Random Networks

TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Journal ArticleDOI

Power-Law Distributions in Empirical Data

TL;DR: This work proposes a principled statistical framework for discerning and quantifying power-law behavior in empirical data by combining maximum-likelihood fitting methods with goodness-of-fit tests based on the Kolmogorov-Smirnov (KS) statistic and likelihood ratios.
Journal ArticleDOI

MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education

TL;DR: The details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture, are presented, which are used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits.
Journal ArticleDOI

Epidemic Spreading in Scale-Free Networks

TL;DR: A dynamical model for the spreading of infections on scale-free networks is defined, finding the absence of an epidemic threshold and its associated critical behavior and this new epidemiological framework rationalizes data of computer viruses and could help in the understanding of other spreading phenomena on communication and social networks.
Related Papers (5)