424 research outputs found

    Event detection and localization in distribution grids with phasor measurement units

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    The recent introduction of synchrophasor technology into power distribution systems has given impetus to various monitoring, diagnostic, and control applications, such as system identification and event detection, which are crucial for restoring service, preventing outages, and managing equipment health. Drawing on the existing framework for inferring topology and admittances of a power network from voltage and current phasor measurements, this paper proposes an online algorithm for event detection and localization in unbalanced three-phase distribution systems. Using a convex relaxation and a matrix partitioning technique, the proposed algorithm is capable of identifying topology changes and attributing them to specific categories of events. The performance of this algorithm is evaluated on a standard test distribution feeder with synthesized loads, and it is shown that a tripped line can be detected and localized in an accurate and timely fashion, highlighting its potential for real-world applications

    On Identification of Distribution Grids

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    Large-scale integration of distributed energy resources into distribution feeders necessitates careful control of their operation through power flow analysis. While the knowledge of the distribution system model is crucial for this analysis, it is often unavailable or outdated. The recent introduction of synchrophasor technology in low-voltage distribution grids has created ample opportunity to learn this model from high-precision, time-synchronized measurements of voltage and current phasors at various locations. This paper focuses on joint estimation of admittance parameters and topology of a polyphase distribution network from the available telemetry data via the lasso, a method for regression shrinkage and selection. We propose tractable convex programs capable of tackling the low-rank structure of the distribution system and develop an online algorithm for early detection and localization of critical events that induce a change in the admittance matrix. The efficacy of these techniques is corroborated through power flow studies on four three-phase radial distribution systems serving real and synthetic household demands

    Security Analysis of Interdependent Critical Infrastructures: Power, Cyber and Gas

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    abstract: Our daily life is becoming more and more reliant on services provided by the infrastructures power, gas , communication networks. Ensuring the security of these infrastructures is of utmost importance. This task becomes ever more challenging as the inter-dependence among these infrastructures grows and a security breach in one infrastructure can spill over to the others. The implication is that the security practices/ analysis recommended for these infrastructures should be done in coordination. This thesis, focusing on the power grid, explores strategies to secure the system that look into the coupling of the power grid to the cyber infrastructure, used to manage and control it, and to the gas grid, that supplies an increasing amount of reserves to overcome contingencies. The first part (Part I) of the thesis, including chapters 2 through 4, focuses on the coupling of the power and the cyber infrastructure that is used for its control and operations. The goal is to detect malicious attacks gaining information about the operation of the power grid to later attack the system. In chapter 2, we propose a hierarchical architecture that correlates the analysis of high resolution Micro-Phasor Measurement Unit (microPMU) data and traffic analysis on the Supervisory Control and Data Acquisition (SCADA) packets, to infer the security status of the grid and detect the presence of possible intruders. An essential part of this architecture is tied to the analysis on the microPMU data. In chapter 3 we establish a set of anomaly detection rules on microPMU data that flag "abnormal behavior". A placement strategy of microPMU sensors is also proposed to maximize the sensitivity in detecting anomalies. In chapter 4, we focus on developing rules that can localize the source of an events using microPMU to further check whether a cyber attack is causing the anomaly, by correlating SCADA traffic with the microPMU data analysis results. The thread that unies the data analysis in this chapter is the fact that decision are made without fully estimating the state of the system; on the contrary, decisions are made using a set of physical measurements that falls short by orders of magnitude to meet the needs for observability. More specifically, in the first part of this chapter (sections 4.1- 4.2), using microPMU data in the substation, methodologies for online identification of the source Thevenin parameters are presented. This methodology is used to identify reconnaissance activity on the normally-open switches in the substation, initiated by attackers to gauge its controllability over the cyber network. The applications of this methodology in monitoring the voltage stability of the grid is also discussed. In the second part of this chapter (sections 4.3-4.5), we investigate the localization of faults. Since the number of PMU sensors available to carry out the inference is insufficient to ensure observability, the problem can be viewed as that of under-sampling a "graph signal"; the analysis leads to a PMU placement strategy that can achieve the highest resolution in localizing the fault, for a given number of sensors. In both cases, the results of the analysis are leveraged in the detection of cyber-physical attacks, where microPMU data and relevant SCADA network traffic information are compared to determine if a network breach has affected the integrity of the system information and/or operations. In second part of this thesis (Part II), the security analysis considers the adequacy and reliability of schedules for the gas and power network. The motivation for scheduling jointly supply in gas and power networks is motivated by the increasing reliance of power grids on natural gas generators (and, indirectly, on gas pipelines) as providing critical reserves. Chapter 5 focuses on unveiling the challenges and providing solution to this problem.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201
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