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

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Modern Power System Dynamic Performance Improvement through Big Data Analysis

Higher penetration of Renewable Energy (RE) is causing generation uncertainty and reduction of system inertia for the modern power system. This phenomenon brings more challenges on the power system dynamic behavior, especially the frequency oscillation and excursion, voltage and transient stability problems. This dissertation work extracts the most useful information from the power system features and improves the system dynamic behavior by big data analysis through three aspects: inertia distribution estimation, actuator placement, and operational studies.First of all, a pioneer work for finding the physical location of COI in the system and creating accurate and useful inertia distribution map is presented. Theoretical proof and dynamic simulation validation have been provided to support the proposed method for inertia distribution estimation based on measurement PMU data. Estimation results are obtained for a radial system, a meshed system, IEEE 39 bus-test system, the Chilean system, and a real utility system in the US. Then, this work provided two control actuator placement strategy using measurement data samples and machine learning algorithms. The first strategy is for the system with single oscillation mode. Control actuators should be placed at the bus that are far away from the COI bus. This rule increased damping ratio of eamples systems up to 14\% and hugely reduced the computational complexity from the simulation results of the Chilean system. The second rule is created for system with multiple dynamic problems. General and effective guidance for planners is obtained for IEEE 39-bus system and IEEE 118-bus system using machine learning algorithms by finding the relationship between system most significant features and system dynamic performance. Lastly, it studied the real-time voltage security assessment and key link identification in cascading failure analysis. A proposed deep-learning framework has Achieved the highest accuracy and lower computational time for real-time security analysis. In addition, key links are identified through distance matrix calculation and probability tree generation using 400,000 data samples from the Western Electricity Coordinating Council (WECC) system

Analysis of new control applications

This document reports the results of the activities performed during the first year of the CRUTIAL project, within the Work Package 1 "Identification and description of Control System Scenarios". It represents the outcome of the analysis of new control applications in the Power System and the identification of critical control system scenarios to be explored by the CRUTIAL project

Enhancing Grid Reliability With Phasor Measurement Units

Over the last decades, great efforts and investments have been made to increase the integration level of renewable energy resources in power grids. The New York State has set the goal to achieve 70% renewable generations by 2030, and realize carbon neutrality by 2040 eventually. However, the increased level of uncertainty brought about by renewables makes it more challenging to maintain stable and robust power grid operation. In addition to renewable energy resources, the ever-increasing number of electric vehicles and active loads have further increased the uncertainties in power systems. All these factors challenge the way the power grids are operated, and thus ask for new solutions to maintain stable and reliable grids. To meet the emerging requirements, advanced metering infrastructures are being integrated into power grids that transform traditional grids into \u27\u27 smart grids . One example is the widely deployed phasor measurement units (PMUs), which enable generating time-synchronized measurements with high sampling frequency, and pave a new path to realize real-time monitoring and control in power grids. However,the massive data generated by PMUs raises the questions of how to efficiently utilize the obtained measurements to understand and control the present system. Additionally, to meet the communication requirements between the advanced meters, the connectivity of the cyber layer has become more sophisticated, and thus is exposed to more cyber-attacks than before. Therefore, to enhance the grid reliability with PMUs, robust and efficient grid monitoring and control methods are required. This dissertation focuses on three important aspects of improving grid reliability with PMUs: (1) power system event detection; (2) impact assessment regarding both steady-state and transient stability; and (3) impact mitigation. In this dissertation, a comprehensive introduction of PMUs in the wide-area monitoring system, and comparisons with the existing supervisory control and data acquisition (SCADA) systems are presented first. Next, a data-driven event detection method is developed for efficient event detection with PMU measurements. A text mining approach is utilized to extract event oscillation patterns and determine event types. To ensure the integrity of the received data, the developed detection method is further designed to identify the fake events, and thus is robust against cyber-threat. Once a real event is detected, it is critical to promptly understand the consequences of the event in both steady and dynamic states. Sometimes, a single system event, e.g., a transmission line fault, may cause subsequent failures that lead to a cascading failure in the grid. In the worst case, these failures can result in large-scale blackouts. To assess the risk of an event in steady state, a probabilistic cascading failure model is developed. With the real-time phasor measurements, the failure probability of each system component at a specific operating condition can be predicted. In terms of the dynamic state, a failure of a system component may cause generators to lose synchronism, which will damage the power plant and lead to a blackout. To predict the transient stability after an event, a predictive online transient stability assessment (TSA) tool is developed in this dissertation. With only one sample of the PMU voltage measurements, the status of the transient stability can be predicted within cycles. In addition to the impact detection and assessment, it is also critical to identify proper mitigations to alleviate the failures. In this dissertation, a data-driven model predictive control strategy is developed. As a parameter-based system model is vulnerable to topology errors, a data-driven model is developed to mimic the grid behavior. Rather than utilizing the system parameters to construct the grid model, the data-driven model only leverages the received phasor measurements to determine proper corrective actions. Furthermore, to be robust against cyber-attacks, a check-point protocol, where past stored trustworthy data can be used to amend the attacked data, is utilized. The overall objective of this dissertation is to efficiently utilize advanced PMUs to detect, assess, and mitigate system failure, and help improve grid reliability

Adaptive Three-Stage Controlled Islanding to Prevent Imminent Wide-area Blackouts

Power blackouts are a recurring problem worldwide, and research in this area continues to focus on developing improved methods for their prediction and prevention. Controlled islanding has been proposed as a last resort action to save the network before imminent blackouts when the usual means fail in an unexpected manner. Successful controlled islanding has to deal with three important issues that are involved in the implementation of islanding: when to island, where to island and what to do after islanding is implemented in each island. This thesis presents a framework that combines all three issues to achieve successful islanding based on wide area measurement systems (WAMS). In addition, this thesis focuses on the question of when to island. This question is critical to the success of the three-stage controlled islanding scheme because the possible issues of false dismissal and false alarm have to be handled. In false dismissal, islanding is triggered too late. However, the potentially unstable system is still allowed to operate, and this unstable system, which could have survived, may cause uncontrolled cascading blackouts. In false alarm, islanding is triggered too early, and an originally stable system is forced to split into islands, resulting in unnecessary disruption and economic loss. Thus, the early recognition and identification of “the point of no return” before blackout is inevitable. The single machine equivalent (SIME) method is adopted online to predict transient stability during cascading outages that would shortly lead to blackouts, giving support in decisions about when to island in terms of transient instability. SIME also evaluates dynamic stability after islanding and ensures that the selected island candidates are stable before action is taken. Moreover, in this thesis, the power flow tracing-based method provides all possible islanding cutsets, and SIME helps to identify the one that has the best transient stability and minimal power flow disruption. If no possible island cut set exists, corrective actions through tripping critical generators or load shedding are undertaken in each island. The IEEE 10-generator, 39-busbar power system and 16-generator 68-busbar system are used to demonstrate the entire framework of the controlled islanding scheme. The performance of each methodology involved in each stage is then presented

HVDC links between North Africa and Europe: Impacts and benefits on the dynamic performance of the European system

This document is the Accepted Manuscript version of the following article: Mokhtar Benasla, Tayeb Allaoui, Mostefa Brahami, Mouloud Denai, and Vijay K. Sood, ‘HVDC links between North Africa and Europe: Impacts and benefits on the dynamic performance of the European system’, Renewable and Sustainable Energy Reviews, November 2017. Under embargo. Embargo end date: 20 November 2018. The published version is available online at doi: DOI: https://doi.org/10.1016/j.rser.2017.10.075. Published by Elsevier Ltd. This manuscript version is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.In the last decade, there have been several initiatives for the deployment of cross-Mediterranean HVDC (High Voltage Direct Current) links to enable the transmission of electrical power from renewable energy sources between North Africa and Europe. These initiatives were mainly driven by the potential economic, environmental and technical benefits of these HVDC interconnections. In previous studies on these projects, some technical aspects of critical importance have not been addressed or studied in sufficient detail. One of these key aspects relates to the impact and possible benefit of these HVDC links on the dynamic performance of the European system which is the major focus of this paper. Several issues relating to the dynamic performance of the system are addressed here. Based on the experience gained from existing AC/DC projects around the world, this paper shows that the HVDC links between North Africa and Europe can greatly improve the dynamic performance of the European system especially in the southern regions. In addition, some challenges on the operation and control of these HVDC links are highlighted and solutions to overcome these challenges are proposed. This review paper, therefore, serves as a preliminary study for further detailed investigation of specific impacts or benefits of these interconnections on the overall performance of the European system.Peer reviewe