Improved fault-tolerant PMU placement using algebraic connectivity of graphs

Due to perpetual and innovative technological advancements, the need for reliable and stable power generation and transmission has been increasing dramatically over the years. Smart grids use advanced technologies to provide self-monitoring, self-checking and self-healing power networks, including smart metering devices capable of providing accurate measurements of the network’s power components. Among the most important metering devices in this context are “Phasor Measurement Units (PMUs)â€. PMUs are metering devices that provide synchronized measurements of voltage, current and phase angle differences using signals from the GPS satellites. However, due to the high cost of such advanced metering devices, studies were performed to determine the minimum number of PMUs required and their strategic placements in the power networks to provide full system observability. In this thesis, we consider fault-tolerant PMU placement aiming to minimize the number of PMUs while maintaining system observability under various contingencies. Conventionally, the optimal number of PMUs in a system is determined based on the system’s connectivity matrix under no contingency. This thesis considers fault- tolerant PMU placement under single and double branch failures. We propose algebraic connectivity, or Fiedler value, to identify the worst- case branch failures in terms of connectivity degradation. The proposed PMU placement accounts for this worst-case and covers a large percentage of other single and double branch failures. Furthermore, we propose the usage of Fiedler vector to provide a PMU placement that would ensure that the system remains fully observable during system partitioning into separate sub-systems. The resulting placements are compared with those obtained without considering connectivity degradation or system partitioning in terms of the percentages of observable systems during any single and double branch failures. The proposed PMU placements have increased percentages of fully observable systems in the event of any single or double branch failures compared to non—contingency based placement, with a reasonable increase in number of PMUs, and for some placement approaches no increase in PMUs is needed for providing a higher percentage of fully observable systems

Improved fault-tolerant PMU placement using algebraic connectivity of graphs

Due to perpetual and innovative technological advancements, the need for reliable and stable power generation and transmission has been increasing dramatically over the years. Smart grids use advanced technologies to provide self-monitoring, self-checking and self-healing power networks, including smart metering devices capable of providing accurate measurements of the network\u27s power components. Among the most important metering devices in this context are Phasor Measurement Units (PMUs) . PMUs are metering devices that provide synchronized measurements of voltage, current and phase angle differences using signals from the GPS satellites. However, due to the high cost of such advanced metering devices, studies were performed to determine the minimum number of PMUs required and their strategic placements in the power networks to provide full system observability. In this thesis, we consider fault-tolerant PMU placement aiming to minimize the number of PMUs while maintaining system observability under various contingencies. Conventionally, the optimal number of PMUs in a system is determined based on the system\u27s connectivity matrix under no contingency. This thesis considers fault- tolerant PMU placement under single and double branch failures. We propose algebraic connectivity, or Fiedler value, to identify the worst- case branch failures in terms of connectivity degradation. The proposed PMU placement accounts for this worst-case and covers a large percentage of other single and double branch failures. Furthermore, we propose the usage of Fiedler vector to provide a PMU placement that would ensure that the system remains fully observable during system partitioning into separate sub-systems. The resulting placements are compared with those obtained without considering connectivity degradation or system partitioning in terms of the percentages of observable systems during any single and double branch failures. The proposed PMU placements have increased percentages of fully observable systems in the event of any single or double branch failures compared to non—contingency based placement, with a reasonable increase in number of PMUs, and for some placement approaches no increase in PMUs is needed for providing a higher percentage of fully observable systems

Node dynamics on graphs: dynamical heterogeneity in consensus, synchronisation and final value approximation for complex networks

Here we consider a range of Laplacian-based dynamics on graphs such as dynamical invariance and coarse-graining, and node-specific properties such as convergence, observability and consensus-value prediction. Firstly, using the intrinsic relationship between the external equitable partition (EEP) and the spectral properties of the graph Laplacian, we characterise convergence and observability properties of consensus dynamics on networks. In particular, we establish the relationship between the original consensus dynamics and the associated consensus of the quotient graph under varied initial conditions. We show that the EEP with respect to a node can reveal nodes in the graph with increased rate of asymptotic convergence to the consensus value as characterised by the second smallest eigenvalue of the quotient Laplacian. Secondly, we extend this characterisation of the relationship between the EEP and Laplacian based dynamics to study the synchronisation of coupled oscillator dynamics on networks. We show that the existence of a non-trivial EEP describes partial synchronisation dynamics for nodes within cells of the partition. Considering linearised stability analysis, the existence of a nontrivial EEP with respect to an individual node can imply an increased rate of asymptotic convergence to the synchronisation manifold, or a decreased rate of de-synchronisation, analogous to the linear consensus case. We show that high degree 'hub' nodes in large complex networks such as Erdős-Rényi, scale free and entangled graphs are more likely to exhibit such dynamical heterogeneity under both linear consensus and non-linear coupled oscillator dynamics. Finally, we consider a separate but related problem concerning the ability of a node to compute the final value for discrete consensus dynamics given only a finite number of its own state values. We develop an algorithm to compute an approximation to the consensus value by individual nodes that is ϵ close to the true consensus value, and show that in most cases this is possible for substantially less steps than required for true convergence of the system dynamics. Again considering a variety of complex networks we show that, on average, high degree nodes, and nodes belonging to graphs with fast asymptotic convergence, approximate the consensus value employing fewer steps.Open Acces

Random graphs with correlation structure.

In this thesis we consider models of random graphs where, unlike in the classical models G (n, p) the probability of an edge arising can be correlated with that of other edges arising. Attention focuses on graphs whose vertices are each assigned a colour (type) at random and where edges between differently coloured vertices subsequently arise with different probabilities (so-called RRC graphs), especially the special case with two colours. Various properties of these graphs are considered, often by comparing and contrasting them with the classical model with the same probability of each particular edge existing. Topics examined include the probabilities of trees and cycles, how the joint probability of two subgraphs compares with the product of their probabilities, the number of edges in the graph (including large deviations results), connectedness, connectivity, the number and order of complete graphs and cliques, and tournaments with correlation structure