Power Grids as Complex Networks: Resilience and Reliability Analysis

Abstract

Power grids are cyber-physical systems and can be modelled as network systems where individual units (generators, busbars and loads) are interconnected through physical and cyber links. Network components (nodes/edges) may undergo intentional and/or random failures. In catastrophic cases, a failure initiating from a small set of these components can quickly propagate through the whole network, leading to a cascade of failures that might force a deep whole-grid blackout. Often network components have different vitality and protecting some is more critical than others. This manuscript aims to provide a focused overview of modelling power grids as complex networks and their resilience and reliability analysis. We also perform a critical review of vitality metrics and their precision in power grid resilience analysis. The review is accompanied by some simulations on benchmark and real power grids to show the applicability of these concepts in studying resilience.

Discovering Important Nodes of Complex Networks Based on Laplacian Spectra

“…So, we are interested in knowing what is the vertex u that results in the maximum increment ∆ i = µ i − µ i . But, when ∆ i = 0 (which usually happens in the case when the multiplicity of µ i is one), we observe that the sum of the two terms mui λ−µi and mu,i+1 λ−µi+1 in (10), where m ui + m u,i+1 ≤ 1, gives rise to a greater ∆ i (µ i closer to µ i+1 ) when m ui is large, as we claimed. Of course, this is an approximation suggested by the simpler case of having only two terms, where the function ξ(λ) = mui λ−µi + 1−mui λ−µi+1 has a zero at µ i = µ i +m ui (µ i+1 −µ i ).…”

“…A similar approach can be applied as a failure or attack tolerant mechanism for dynamical networks [23]. For example, identifying and protecting central nodes can improve resilience and reliability of power systems [10]. Node centrality can also be defined based on the Laplacian energy E L (G), which is sum of the squared eigenvalues of the Laplacian matrix L of the graph G [29].…”

Enhancing Loadability of Transmission Lines Using Static Synchronous Series Compensator Devices: A Case Study of the Syrian Network

“…The continual growth in demand for electric power necessitates the significant expansion of existing electrical networks [2]. Critical issues, such as the overload of transmission lines, which are highly undesirable and detrimental to power reliability, can result from insufficient interconnection and management of electrical networks [3]. Resorting to the construction of new transmission lines to address these problems is economically unviable.…”

Partial‐nodes‐based state estimation for state‐saturated complex networks with random mixed couplings under dynamic event‐triggered protocol

“…With the developments of the network era, the complex networks (CNs) have been widely used in various fields, such as power grids, 1 disease spread, 2 biological networks, 3 neural networks 4 and social networks 5 . It is worthwhile to mention that the CNs are composed of numerous nodes and edges with massive scales 6‐9 .…”