3,246 research outputs found
A model for cascading failures in complex networks
Large but rare cascades triggered by small initial shocks are present in most
of the infrastructure networks. Here we present a simple model for cascading
failures based on the dynamical redistribution of the flow on the network. We
show that the breakdown of a single node is sufficient to collapse the
efficiency of the entire system if the node is among the ones with largest
load. This is particularly important for real-world networks with an highly
hetereogeneous distribution of loads as the Internet and electrical power
grids.Comment: 4 pages, 4 figure
Resilience of power grids and other supply networks: structural stability, cascading failures and optimal topologies
The consequences of the climate crisis are already present and can be expected to become more severe in the future. To mitigate long-term consequences, a major part of the world's countries has committed to limit the temperature rise via the Paris Agreement in the year 2015. To achieve this goal, the energy production needs to decarbonise, which results in fundamental changes in many societal aspects. In particular, the electrical power production is shifting from fossil fuels to renewable energy sources to limit greenhouse gas emissions.
The electrical power transmission grid plays a crucial role in this transformation. Notably, the storage and long-distance transport of electrical power becomes increasingly important, since variable renewable energy sources (VRES) are subjected to external factors such as weather conditions and their power production is therefore regionally and temporally diverse. As a result, the transmission grid experiences higher loadings and bottlenecks appear. In a highly-loaded grid, a single transmission line or generator outage can trigger overloads on other components via flow rerouting. These may in turn trigger additional rerouting and overloads, until, finally, parts of the grid become disconnected. Such cascading failures can result in large-scale power blackouts, which bear enormous risks, as almost all infrastructures and economic activities depend on a reliable supply of electric power. Thus, it is essential to understand how networks react to local failures, how flow is rerouted after failures and how cascades emerge and spread in different power transmission grids to ensure a stable power grid operation.
In this thesis, I examine how the network topology shapes the resilience of power grids and other supply networks. First, I analyse how flow is rerouted after the failure of a single or a few links and derive mathematically rigorous results on the decay of flow changes with different network-based distance measures. Furthermore, I demonstrate that the impact of single link failures follows a universal statistics throughout different topologies and introduce a stochastic model for cascading failures that incorporates crucial aspects of flow redistribution. Based on this improved understanding of link failures, I propose network modifications that attenuate or completely suppress the impact of link failures in parts of the network and thereby significantly reduce the risk of cascading failures. In a next step, I compare the topological characteristics of different kinds of supply networks to analyse how the trade-off between efficiency and resilience determines the structure of optimal supply networks. Finally, I examine what shapes the risk of incurring large scale cascading failures in a realistic power system model to assess the effects of the energy transition in Europe
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
Network hierarchy evolution and system vulnerability in power grids
(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The seldom addressed network hierarchy property and its relationship with vulnerability analysis for power transmission grids from a complex-systems point of view are given in this paper. We analyze and compare the evolution of network hierarchy for the dynamic vulnerability evaluation of four different power transmission grids of real cases. Several meaningful results suggest that the vulnerability of power grids can be assessed by means of a network hierarchy evolution analysis. First, the network hierarchy evolution may be used as a novel measurement to quantify the robustness of power grids. Second, an antipyramidal structure appears in the most robust network when quantifying cascading failures by the proposed hierarchy metric. Furthermore, the analysis results are also validated and proved by empirical reliability data. We show that our proposed hierarchy evolution analysis methodology could be used to assess the vulnerability of power grids or even other networks from a complex-systems point of view.Peer ReviewedPostprint (author's final draft
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