Survey on synchrophasor data quality and cybersecurity challenges, and evaluation of their interdependencies

Synchrophasor devices guarantee situation awareness for real-time monitoring and operational visibility of smart grid. With their widespread implementation, significant challenges have emerged, especially in communication, data quality and cybersecurity. The existing literature treats these challenges as separate problems, when in reality, they have a complex interplay. This paper conducts a comprehensive review of quality and cybersecurity challenges for synchrophasors, and identifies the interdependencies between them. It also summarizes different methods used to evaluate the dependency and surveys how quality checking methods can be used to detect potential cyberattacks. This paper serves as a starting point for researchers entering the fields of synchrophasor data analytics and security

Integrity and attack-resilience of GPS-based positioning and timing: a Bayesian and measurement fusion approach

Robust Position, Velocity, and Timing (PVT) are essential for the safe operations of critical infrastructure sectors, such as transportation systems and power grids. Different transportation systems, both human-operated and autonomous vehicles, navigate using accurate position and velocity information. On the other hand, precise timing is crucial for various economic activities worldwide, such as banking, stock markets, and the power grid. GPS serves as a backbone for many state-of-the-art applications related to these crucial infrastructures. GPS provides sub-microsecond accurate timing and meter level of accurate positioning. It has global coverage and is free for all users. The GPS positioning and timing service has some limitations. The positioning accuracy degrades in urban environments due to tall structures that block and reflect satellite signals. Degraded positioning is not safe for the operation of autonomously driving vehicles. Furthermore, GPS signals are susceptible to external attacks due to their low signal power and unencrypted signal structures. Researchers have shown that GPS Spoofing Attacks (GSAs) are feasible, and GSA for timing is able to alter timing without modifying the positioning solution. Such attacks create unsafe operating conditions for the modern power grid, which will use GPS timing for monitoring the wide-area network. The contribution of this work is to develop algorithms to mitigate the above limitations. We develop Bayesian algorithms that utilize multiple sensors and receivers. For improving positioning, first, we design an adaptive filter based on Bayesian algorithms to augment GPS with the additional vision sensor. Second, we develop an integrity monitoring algorithm for Direct Positioning (DP), which is an advanced GPS receiver architecture that directly works on the position domain and is robust to signal blockage and multipath effects. To monitor integrity, we estimate vertical protection levels using a Bayesian approach. We further generate GPS datasets simulating open, semi-urban, and urban environments for validating DP with multiple receivers. For mitigating GSAs for timing, we design static and dynamic state estimators for the power grid. The static state estimator utilizes measurement residuals to correct power grid states. In the dynamic state estimator, we fuse GPS and power grid measurements to provide resiliency against GSAs. We create a virtual power grid testbed and generate datasets for a power grid network under different GSAs. These are the first datasets that contain both power grid and GPS measurements under GSAs, and we make them openly available. Our estimators are validated on various power grid networks and on the generated datasets

Synchrophasors: Multilevel Assessment and Data Quality Improvement for Enhanced System Reliability

. This study presents a comprehensive framework for testing and evaluation of Phasor Measurement Units (PMUs) and synchrophasor systems under normal power system operating conditions, as well as during disturbances such as faults and transients. The proposed framework suggests a performance assessment to be conducted in three steps: (a) type testing: conducted in the synchrophasor calibration laboratory according to accepted industrial standards; (b) application testing: conducted to evaluate the performance of the PMUs under faults, transients, and other disturbances in power systems; (c) end-to-end system testing: conducted to assess the risk and quantify the impact of measurement errors on the applications of interest. The suggested calibration toolset (type testing) enables performance characterization of different design alternatives in a standalone PMU (e.g., length of phasor estimation windows, filtering windows, reporting rates, etc.). In conjunction with the standard performance requirements, this work defines new metrics for PMU performance evaluations under any static and dynamic conditions that may unfold in the grid. The new metrics offer a more realistic understanding of the overall PMU performance and help users choose the appropriate device/settings for the target applications. Furthermore, the proposed probabilistic techniques quantify the PMU accuracy to various test performance thresholds specified by corresponding IEEE standards, rather than having only the pass/fail test outcome, as well as the probability of specific failures to meet the standard requirements defined in terms of the phasor, frequency, and rate of change of frequency accuracy. Application testing analysis encompasses PMU performance evaluation under faults and other prevailing conditions, and offers a realistic assessment of the PMU measurement errors in real-world field scenarios and reveals additional performance characteristics that are crucial for the overall application evaluation. End-to-end system tests quantify the impact of synchrophasor estimation errors and their propagation from the PMU towards the end-use applications and evaluate the associated risk. In this work, extensive experimental results demonstrate the advantages of the proposed framework and its applicability is verified through two synchrophasor applications, namely: Fault Location and Modal Analysis. Finally, a data-driven technique (Principal Component Pursuit) is proposed for the correction and completion of the synchrophasor data blocks, and its application and effectiveness is validated in modal analyzes

False Data Injection Attacks in Smart Grids: State of the Art and Way Forward

In the recent years cyberattacks to smart grids are becoming more frequent Among the many malicious activities that can be launched against smart grids False Data Injection FDI attacks have raised significant concerns from both academia and industry FDI attacks can affect the internal state estimation processcritical for smart grid monitoring and controlthus being able to bypass conventional Bad Data Detection BDD methods Hence prompt detection and precise localization of FDI attacks is becomming of paramount importance to ensure smart grids security and safety Several papers recently started to study and analyze this topic from different perspectives and address existing challenges Datadriven techniques and mathematical modelings are the major ingredients of the proposed approaches The primary objective of this work is to provide a systematic review and insights into FDI attacks joint detection and localization approaches considering that other surveys mainly concentrated on the detection aspects without detailed coverage of localization aspects For this purpose we select and inspect more than forty major research contributions while conducting a detailed analysis of their methodology and objectives in relation to the FDI attacks detection and localization We provide our key findings of the identified papers according to different criteria such as employed FDI attacks localization techniques utilized evaluation scenarios investigated FDI attack types application scenarios adopted methodologies and the use of additional data Finally we discuss open issues and future research direction

Synchrophasors: Multilevel Assessment and Data Quality Improvement for Enhanced System Reliability

. This study presents a comprehensive framework for testing and evaluation of Phasor Measurement Units (PMUs) and synchrophasor systems under normal power system operating conditions, as well as during disturbances such as faults and transients. The proposed framework suggests a performance assessment to be conducted in three steps: (a) type testing: conducted in the synchrophasor calibration laboratory according to accepted industrial standards; (b) application testing: conducted to evaluate the performance of the PMUs under faults, transients, and other disturbances in power systems; (c) end-to-end system testing: conducted to assess the risk and quantify the impact of measurement errors on the applications of interest. The suggested calibration toolset (type testing) enables performance characterization of different design alternatives in a standalone PMU (e.g., length of phasor estimation windows, filtering windows, reporting rates, etc.). In conjunction with the standard performance requirements, this work defines new metrics for PMU performance evaluations under any static and dynamic conditions that may unfold in the grid. The new metrics offer a more realistic understanding of the overall PMU performance and help users choose the appropriate device/settings for the target applications. Furthermore, the proposed probabilistic techniques quantify the PMU accuracy to various test performance thresholds specified by corresponding IEEE standards, rather than having only the pass/fail test outcome, as well as the probability of specific failures to meet the standard requirements defined in terms of the phasor, frequency, and rate of change of frequency accuracy. Application testing analysis encompasses PMU performance evaluation under faults and other prevailing conditions, and offers a realistic assessment of the PMU measurement errors in real-world field scenarios and reveals additional performance characteristics that are crucial for the overall application evaluation. End-to-end system tests quantify the impact of synchrophasor estimation errors and their propagation from the PMU towards the end-use applications and evaluate the associated risk. In this work, extensive experimental results demonstrate the advantages of the proposed framework and its applicability is verified through two synchrophasor applications, namely: Fault Location and Modal Analysis. Finally, a data-driven technique (Principal Component Pursuit) is proposed for the correction and completion of the synchrophasor data blocks, and its application and effectiveness is validated in modal analyzes

Development and application of synchronized wide-area power grid measurement

Phasor measurement units (PMUs) provide an innovative technology for real-time monitoring of the operational state of entire power systems and significantly improve power grid dynamic observability. This dissertation focuses on development and application of synchronized power grid measurements. The contributions of this dissertation are as followed:First, a novel method for successive approximation register analog to digital converter control in PMUs is developed to compensate for the sampling time error caused by the division remainder between the desirable sampling rate and the oscillator frequency. A variable sampling interval control method is presented by interlacing two integers under a proposed criterion. The frequency of the onboard oscillator is monitored in using the PPS from GPS.Second, the prevalence of GPS signal loss (GSL) on PMUs is first investigated using real PMU data. The correlation between GSL and time, spatial location, solar activity are explored via comprehensive statistical analysis. Furthermore, the impact of GSL on phasor measurement accuracy has been studied via experiments. Several potential solutions to mitigate the impact of GSL on PMUs are discussed and compared.Third, PMU integrated the novel sensors are presented. First, two innovative designs for non-contact PMUs presented. Compared with conventional synchrophasors, non-contact PMUs are more flexible and have lower costs. Moreover, to address nonlinear issues in conventional CT and PT, an optical sensor is used for signal acquisition in PMU. This is the first time the utilization of an optical sensor in PMUs has ever been reported.Fourth, the development of power grid phasor measurement function on an Android based mobile device is developed. The proposed device has the advantages of flexibility, easy installation, lower cost, data visualization and built-in communication channels, compared with conventional PMUs.Fifth, an identification method combining a wavelet-based signature extraction and artificial neural network based machine learning, is presented to identify the location of unsourced measurements. Experiments at multiple geographic scales are performed to validate the effectiveness of the proposed method using ambient frequency measurements. Identification accuracy is presented and the factors that affect identification performance are discussed

Proactive defense strategies against net load redistribution attacks in cyber-physical smart grids

Doctor of PhilosophyDepartment of Electrical and Computer EngineeringHongyu WuRecent advances in the cyber-physical smart grid (CPSG) have enabled a broad range of new devices based on information and communication technology (ICT). An open network environment in CPSG provides frequent interaction between information and physical components. However, this interaction also exposes the ICT-enabled devices to a growing threat of cyberattacks. Such threats have been alerted by recent cybersecurity incidents, and the security issues have strongly restricted the development of CPSG. Among various CPS cybersecurity incidents, cyber data attacks invade the cyber layer to destroy data integrity. Through elaborately eavesdropping on the transferred measurement data, the attacks can mislead the state estimation (SE) while keeping stealthy to conventional bad data detection (BDD). Due to the SE being the critical function of CPSG control, the cyber data attacks may cause massive economic loss, power system instability, or even cascading failures. Therefore, this dissertation focuses on the detection of stealthy data integrity attacks. This dissertation first performs a thorough review of the state-of-the-art cyber-physical security of the smart grid. By focusing on the physical layer of the CPSG, this work provides an abstracted and unified state-space model in which cyber-physical attack and defense models can be effectively generalized. The existing cyber-physical attacks are categorized in terms of their target components. In addition, this work discusses several operational and informational defense approaches that present the current state-of-the-art in the field, including moving target defense (MTD), watermarking, and data-driven strategies. The challenges and future opportunities associated with the smart grid cyber-physical security is also discussed. Further, a real-time digital simulator, namely Typhoon HIL, is utilized to visualize the random MTD against false data injection (FDI) attacks. Given the review section as a background, a hidden, coordinated net load redistribution attack (NLRA) in an AC distribution system is proposed. The attacker's goal is to create violations in nodal voltage magnitude estimation. An attacker can implement the NLRA strategy by using the local information of an attack region and power flow enhanced deep learning (PFEDL) state estimators. The NLRA is modeled as an attacker's modified AC optimal power flow problem to maximize the attack impact. Case study results indicate the PFEDL-based SE can provide the attacker with accurate system states in a low observable distribution system where conventional lease square-based SE cannot converge. The stealthiness of the hidden NLRA is validated in multiple attack cases. The influence of NLRA on the distribution system is assessed, and the impact of attack regions, attack timing, and attack area size are also revealed. Next, this dissertation highlights that current MTD strategies myopically perturb the reactance of D-FACTS lines without considering the system voltage stability. Voltage instability induced by MTDs is illustrated in a three-bus system and two more complicated systems with real-world load profiles. Further, a novel MTD framework that explicitly considers system voltage stability using continuation power flow and voltage stability indices is proposed to avoid MTD-induced voltage instability. In addition, this dissertation mathematically derives the sensitivity matrix of voltage stability index to line impedance, on which an optimization problem for maximizing voltage stability index is formulated. This framework is tested on the IEEE 14-bus and the IEEE 118-bus transmission systems, in which sophisticated attackers launch NLRAs. The simulation results show the effectiveness of the proposed framework in circumventing voltage instability while maintaining the detection effectiveness of MTD. Case studies are conducted with and without the proposed framework under different MTD planning and operational methods. The impacts of the proposed two methods on attack detection effectiveness and system economic metrics are also revealed. Finally, this dissertation proposes utilizing smart inverters to implement a novel meter encoding scheme in distribution systems. The proposed meter encoding scheme is a software-based active detection method, which neither requires additional hardware devices nor causes system instability, compared with MTD and watermarking. By elaborately constructing the encoding vector, the proposed smart-inverter-based meter encoding can mislead the attacker's SE while being hidden from alert attackers. In addition, by utilizing the topology of radial distribution systems, the proposed encoding scheme encodes fewer meters than current schemes when protecting the same number of buses, which decreases the encoding cost. Simulation results from the IEEE 69-bus distribution system demonstrate that the proposed meter encoding scheme can mislead the attacker's state estimation on all the downstream buses of an encoded bus without arousing the attacker's suspicion. FDI attacks constructed based on the misled estimated states are highly possible to trigger the defender's BDD alarm

Detection and Mitigation of Cyber Attacks on Time Synchronization Protocols for the Smart Grid

The current electric grid is considered as one of the greatest engineering achievements of the twentieth century. It has been successful in delivering power to consumers for decades. Nevertheless, the electric grid has recently experienced several blackouts that raised several concerns related to its availability and reliability. The aspiration to provide reliable and efficient energy, and contribute to environment protection through the increasing utilization of renewable energies are driving the need to deploy the grid of the future, the smart grid. It is expected that this grid will be self-healing from power disturbance events, operating resiliently against physical and cyber attack, operating efficiently, and enabling new products and services. All these call for a grid with more Information and Communication Technologies (ICT). As such, power grids are increasingly absorbing ICT technologies to provide efficient, secure and reliable two-way communication to better manage, operate, maintain and control electric grid components. On the other hand, the successful deployment of the smart grid is predicated on the ability to secure its operations. Such a requirement is of paramount importance especially in the presence of recent cyber security incidents. Furthermore, those incidents are subject to an augment with the increasing integration of ICT technologies and the vulnerabilities they introduce to the grid. The exploitation of these vulnerabilities might lead to attacks that can, for instance, mask the system observability and initiate cascading failures resulting in undesirable and severe consequences. In this thesis, we explore the security aspects of a key enabling technology in the smart grid, accurate time synchronization. Time synchronization is an immense requirement across the domains of the grid, from generation to transmission, distribution, and consumer premises. We focus on the substation, a basic block of the smart grid system, along with its recommended time synchronization mechanism - the Precision Time Protocol (PTP) - in order to address threats associated with PTP, and propose practical and efficient detection, prevention, mitigation techniques and methodologies that will harden and enhance the security and usability of PTP in a substation. In this respect, we start this thesis with a security assessment of PTP that identifies PTP security concerns, and then address those concerns in the subsequent chapters. We tackle the following main threats associated with PTP: 1) PTP vulnerability to fake timestamp injection through a compromised component 2) PTP vulnerability to the delay attack and 3) The lack of a mechanism that secures the PTP network. Next, and as a direct consequence of the importance of time synchronization in the smart grid, we consider the wide area system to demonstrate the vulnerability of relative data alignment in Phasor Data Concentrators to time synchronization attacks. These problems will be extensively studied throughout this thesis, followed by discussions that highlight open research directions worth further investigations

Data Analytics and Wide-Area Visualization Associated with Power Systems Using Phasor Measurements

As power system research becomes more data-driven, this study presents a framework for the analysis and visualization of phasor measurement unit (PMU) data obtained from large, interconnected systems. The proposed framework has been implemented in three steps: (a) large-scale, synthetic PMU data generation: conducted to generate research-based measurements with the inclusion of features associated with industry-grade PMU data; (b) error and event detection: conducted to assess risk levels and data accuracy of phasor measurements, and furthermore search for system events or disturbances; (c) oscillation mode visualization: conducted to present wide-area, modal information associated with large-scale power grids. To address the challenges due to real data confidentiality, the creation of realistic, synthetic PMU measurements is proposed for research use. First, data error propagation models are generated after a study of some of the issues associated with the unique time-synchronization feature of PMUs. An analysis of some of the features of real PMU data is performed to extract some of the statistics associated with data errors. Afterwards, an approach which leverages on existing, large-scale, synthetic networks to model the constantly-changing dynamics often observed in real measurements is used to generate an initial synthetic dataset. Further inclusion of PMU-related data anomalies ensures the production of realistic, synthetic measurements fit for research purposes. An application of different techniques based on a moving-window approach is suggested for use in the detection of events in real and synthetic PMU measurements. These fast methods rely on smaller time-windows to assess fewer measurement samples for events, classify disturbances into global or local events, and detect unreliable measurement sources. For large-scale power grids with complex dynamics, a distributed error analysis is proposed for the isolation of local dynamics prior any reliability assessment of PMU-obtained measurements. Finally, fundamental system dynamics which are inherent in complex, interconnected power systems are made apparent through a wide-area visualization of large-scale, electric grid oscillation modes. The approach ensures a holistic interpretation of modal information given that large amounts of modal data are often generated in these complex systems irrespective of the technique that is used

Towards secure & robust PNT for automated systems

This dissertation makes four contributions in support of secure and robust position, navigation, and timing (PNT) for automated systems. The first two relate to PNT security while the latter two address robust positioning for automated ground vehicles. The first contribution is a fundamental theory for provably-secure clock synchronization between two agents in a distributed automated system. All one-way synchronization protocols, such as those based on the Global Positioning System (GPS) and other Global Navigation Satellite Systems (GNSS), are shown to be vulnerable to man-in-the-middle delay attacks. This contribution is the first to identify the necessary and sufficient conditions for provably secure clock synchronization. The second contribution, also related to PNT security, is a three-year study of the world-wide GPS interference landscape based on data from a dual-frequency GNSS receiver operating continuously on the International Space Station (ISS). This work is the first publicly-reported space-based survey of GNSS interference, and unveils previously-unreported GNSS interference activity. The third contribution is a novel ground vehicle positioning technique that is robust to GNSS signal blockage, poor lighting conditions, and adverse weather events such as heavy rain and dense fog. The technique relies on sensors that are commonly available on automated vehicles and are insensitive to lighting and inclement weather: automotive radar, low-cost inertial measurement units (IMUs), and GNSS. Remarkably, it is shown that, given a prior radar map, the proposed technique operating on data from off-the-shelf all-weather automotive sensors can maintain sub-50-cm horizontal position accuracy during 60 min of GNSS-denied driving in downtown Austin, TX. This dissertation’s final contribution is an analysis and demonstration of the feasibility of crowd-sourced digital mapping for automated vehicles. Localization techniques, such as the one described in the previous contribution, rely on such digital maps for accuracy and robustness. A key enabler for large-scale up-to-date maps is enlisting the help of the very consumer vehicles that need the map to build and update it. A method for fusing multi-session vision data into a unified digital map is developed. The asymptotic limit of such a map’s globally-referenced position accuracy is explored for the case in which the mapping agents rely on low-cost GNSS receivers performing standard code-phase-based navigation. Experimental validation along a semi-urban route shows that low-cost consumer vehicles incrementally tighten the accuracy of the jointly-optimized digital map over time enough to support sub-lane-level positioning in a global frame of reference.Electrical and Computer Engineerin