A Topological Investigation of Phase Transitions of Cascading Failures in Power Grids

Cascading failures are one of the main reasons for blackouts in electric power transmission grids. The economic cost of such failures is in the order of tens of billion dollars annually. The loading level of power system is a key aspect to determine the amount of the damage caused by cascading failures. Existing studies show that the blackout size exhibits phase transitions as the loading level increases. This paper investigates the impact of the topology of a power grid on phase transitions in its robustness. Three spectral graph metrics are considered: spectral radius, effective graph resistance and algebraic connectivity. Experimental results from a model of cascading failures in power grids on the IEEE power systems demonstrate the applicability of these metrics to design/optimize a power grid topology for an enhanced phase transition behavior of the system

Structural Vulnerability Analysis of Electric Power Distribution Grids

Power grid outages cause huge economical and societal costs. Disruptions in the power distribution grid are responsible for a significant fraction of electric power unavailability to customers. The impact of extreme weather conditions, continuously increasing demand, and the over-ageing of assets in the grid, deteriorates the safety of electric power delivery in the near future. It is this dependence on electric power that necessitates further research in the power distribution grid security assessment. Thus measures to analyze the robustness characteristics and to identify vulnerabilities as they exist in the grid are of utmost importance. This research investigates exactly those concepts- the vulnerability and robustness of power distribution grids from a topological point of view, and proposes a metric to quantify them with respect to assets in a distribution grid. Real-world data is used to demonstrate the applicability of the proposed metric as a tool to assess the criticality of assets in a distribution grid

Interdepedency modeling of cyber-physical systems using a weighted complex network approach

This paper introduces a three-dimensional weighted Complex Network Theory (CNT) model to study the dependency and interdependency of cyber-physical systems (CPS) and to identify the most critical and vulnerable components within the coupled network. Based on CNT, the electric power buses within power system and communication routers and multiplexers within communication network are modelled as nodes, while the power lines and communication channels are modelled as edges. The intrinsic properties of electric power system (e.g. power flow) and the communication network (e.g. gross bitrate) are assigned as weights to each edge. A novel CNT-derived index, Vulnerability-weighted Node Degree (VWND), has been developed and applied to assess the dependency/importance of each physical/cyber node to its own and to the other system and such to help identify potentially weak areas of the system. The approach is illustrated on a 14-bus synthetic power distribution network with supporting Information and Communication Technologies (ICT)

Alternative method for the identification of critical nodes leading to voltage instability in a power system

Abstract: Introduction of new operation enhancement technologies plus increasing application of power electronics coupled with the continuous increase in load demand has increased the risk of power networks to voltage instability and susceptibility to voltage collapse. This frequent occurrence of voltage collapse in modern power system has been a growing concern to power system utilities. This paper proposes alternative techniques for the identification of critical nodes that are liable to voltage instability in a power system. The first method is based on the critical mode corresponding to the smallest eigenvalues, while the second technique is based on the centrality measure to identify the influential node of the networks. The eigenvector centrality measure is formulated from the response matrices of both the load and generator nodes of the networks. The effectiveness of the suggested approaches is tested using the IEEE 30 bus and the Southern Indian 10 bus power networks. The results are compared to the techniques based on the traditional power flow. The whole procedure of the results involved in the identification of critical nodes through the proposed methods is totally non-iterative and thereby save time and require less computational burden

Critical Infrastructures: Enhancing Preparedness & Resilience for the Security of Citizens and Services Supply Continuity: Proceedings of the 52nd ESReDA Seminar Hosted by the Lithuanian Energy Institute & Vytautas Magnus University

Critical Infrastructures Preparedness and Resilience is a major societal security issue in modern society. Critical Infrastructures (CIs) provide vital services to modern societies. Some CIs’ disruptions may endanger the security of the citizen, the safety of the strategic assets and even the governance continuity. The European Safety, Reliability and Data Association (ESReDA) as one of the most active EU networks in the field has initiated a project group on the “Critical Infrastructure/Modelling, Simulation and Analysis – Data”. The main focus of the project group is to report on the state of progress in MS&A of the CIs preparedness & resilience with a specific focus on the corresponding data availability and relevance. In order to report on the most recent developments in the field of the CIs preparedness & resilience MS&A and the availability of the relevant data, ESReDA held its 52nd Seminar on the following thematic: “Critical Infrastructures: Enhancing Preparedness & Resilience for the security of citizens and services supply continuity”. The 52nd ESReDA Seminar was a very successful event, which attracted about 50 participants from industry, authorities, operators, research centres, academia and consultancy companies.JRC.G.10-Knowledge for Nuclear Security and Safet

Structural vulnerability assessment of electric power grids

Cascading failures are the typical reasons of blackouts in power grids. The grid topology plays an important role in determining the dynamics of cascading failures in power grids. Measures for vulnerability analysis are crucial to assure a higher level of robustness of power grids. Metrics from Complex Networks are widely used to investigate the grid vulnerability. Yet, these purely topological metrics fail to capture the real behaviour of power grids. This paper proposes a metric, the effective graph resistance, as a vulnerability measure to determine the critical components in a power grid. Differently than the existing purely topological measures, the effective graph resistance accounts for the electrical properties of power grids such as power flow allocation according to Kirchoff laws. To demonstrate the applicability of the effective graph resistance, a quantitative vulnerability assessment of the IEEE 118 buses power system is performed. The simulation results verify the effectiveness of the effective graph resistance to identify the critical transmission lines in a power grid. © 2014 IEEE