Identification of Cascading Failure Propagation Under Extreme Weather Conditions

As a fundamental infrastructure, power systems play a vital role in modern society, but it can be damaged by different adverse events e.g. natural, accidental, and malicious, of which the adverse natural events, especially extreme weathers, with huge destructive force can bring tremendous damages and economic losses. The high exposure and comprehensive geographical coverage of the power system make it highly vulnerable to extreme weathers, resulting in equipment damage which leads to cascading failures and blackouts. Traditional methods only focus on modeling and analysing the reliability of the power system under extreme weathers, without focusing on the propagation of the cascades. In this thesis, innovative methods of studying the cascading failure were proposed, and further extend to collectively consider the impact of extreme weathers on the transmission networks. The proposed models were further validated by applying them to a study system (IEEE-30 bus system) and a real system (Italian transmission network). A so called normal failure model based on probabilistic graphs was proposed to describe how a cascading failure propagates under a contingency analysis. This model employed Monte Carlo simulation to consider most of the possible operating conditions to establish directed probabilistic graphs to identify the cascading propa-gation by tripping all branches one by one under each operating condition. Obviously, the results of the model can clearly and legibly show the main cascading path of a given network without considering the initial operating condition and the triggering contingency. Further, an index based on branch vulnerability was designed to select the triggering event to increase the effectiveness of the failure in the simulation. Furthermore, by integrating a probabilistic model of extreme weather impact into the normal failure model, the extreme weather model was proposed based on failure networks, which maps a physical electricity network into a graph in the cascading propagation dimensions. Based on the generated failure networks, a new method based on clustering techniques was proposed to fast track the cascading failure path from any initial contingencies without recalculating the cascading failure in the physical network. The high similarity of the simulation results on the IEEE 30 bus system from the two proposed models indicates the validity of the models. Further, to demonstrate the extreme weather model, we selected a winter storm, which could happen in Northwest of Italy as an example. The data of snowfall on the Alps was collected and modeled by probability density function and probability mass function. By applying the proposed extreme weather model, the propagation paths can be predicted. The values of the study provide two powerful tools which can 1) clearly present the inherent characteristic of any one given network, i.e. main propagation paths exist regardless of the initial network and failure condition; 2) fast and reasonably predict the cascading paths in a network under extreme weather conditions

Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems

The first-ever Ukraine cyberattack on power grid has proven its devastation by hacking into their critical cyber assets. With administrative privileges accessing substation networks/local control centers, one intelligent way of coordinated cyberattacks is to execute a series of disruptive switching executions on multiple substations using compromised supervisory control and data acquisition (SCADA) systems. These actions can cause significant impacts to an interconnected power grid. Unlike the previous power blackouts, such high-impact initiating events can aggravate operating conditions, initiating instability that may lead to system-wide cascading failure. A systemic evaluation of "nightmare" scenarios is highly desirable for asset owners to manage and prioritize the maintenance and investment in protecting their cyberinfrastructure. This survey paper is a conceptual expansion of real-time monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework that emphasizes on the resulting impacts, both on steady-state and dynamic aspects of power system stability. Hypothetically, we associate the combinatorial analyses of steady state on substations/components outages and dynamics of the sequential switching orders as part of the permutation. The expanded framework includes (1) critical/noncritical combination verification, (2) cascade confirmation, and (3) combination re-evaluation. This paper ends with a discussion of the open issues for metrics and future design pertaining the impact quantification of cyber-related contingencies

MATCASC: A tool to analyse cascading line outages in power grids

Blackouts in power grids typically result from cascading failures. The key importance of the electric power grid to society encourages further research into sustaining power system reliability and developing new methods to manage the risks of cascading blackouts. Adequate software tools are required to better analyze, understand, and assess the consequences of the cascading failures. This paper presents MATCASC, an open source MATLAB based tool to analyse cascading failures in power grids. Cascading effects due to line overload outages are considered. The applicability of the MATCASC tool is demonstrated by assessing the robustness of IEEE test systems and real-world power grids with respect to cascading failures

Application of reliability-based robustness assessment of steel moment resisting frame structures under post-mainshock cascading events

This paper proposes a reliability-based framework for quantifying structural robustness considering the occurrence of a major earthquake (mainshock) and subsequent cascading hazard events, such as aftershocks that are triggered by the mainshock. These events can significantly increase the probability of failure of buildings, especially for structures that are damaged during the mainshock. The application of the proposed framework is exemplified through three numerical case studies. The case studies correspond to three SAC steel moment frame buildings of three, nine, and 20 stories, which were designed to pre-Northridge codes and standards. Two-dimensional nonlinear finite-element models of the buildings are developed with the Open System for Earthquake Engineering Simulation framework (OpenSees), using a finite length plastic hinge beam model and a bilinear constitutive law with deterioration, and are subjected to multiple mainshock-aftershock seismic sequences. For the three buildings analyzed herein, it is shown that the structural reliability under a single seismic event can be significantly different from that under a sequence of seismic events. The reliability based robustness indicator shows that the structural robustness is influenced by the extent to which a structure can distribute damage

Stochastic Model for Power Grid Dynamics

We introduce a stochastic model that describes the quasi-static dynamics of an electric transmission network under perturbations introduced by random load fluctuations, random removing of system components from service, random repair times for the failed components, and random response times to implement optimal system corrections for removing line overloads in a damaged or stressed transmission network. We use a linear approximation to the network flow equations and apply linear programming techniques that optimize the dispatching of generators and loads in order to eliminate the network overloads associated with a damaged system. We also provide a simple model for the operator's response to various contingency events that is not always optimal due to either failure of the state estimation system or due to the incorrect subjective assessment of the severity associated with these events. This further allows us to use a game theoretic framework for casting the optimization of the operator's response into the choice of the optimal strategy which minimizes the operating cost. We use a simple strategy space which is the degree of tolerance to line overloads and which is an automatic control (optimization) parameter that can be adjusted to trade off automatic load shed without propagating cascades versus reduced load shed and an increased risk of propagating cascades. The tolerance parameter is chosen to describes a smooth transition from a risk averse to a risk taken strategy...Comment: framework for a system-level analysis of the power grid from the viewpoint of complex network

Spatial and performance optimality in power distribution networks

(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.Complex network theory has been widely used in vulnerability analysis of power networks, especially for power transmission ones. With the development of the smart grid concept, power distribution networks are becoming increasingly relevant. In this paper, we model power distribution systems as spatial networks. Topological and spatial properties of 14 European power distribution networks are analyzed, together with the relationship between geographical constraints and performance optimization, taking into account economic and vulnerability issues. Supported by empirical reliability data, our results suggest that power distribution networks are influenced by spatial constraints which clearly affect their overall performance.Peer ReviewedPostprint (author's final draft