Synchrophasor Measurements Research Articles

Controlled islanding of transmission system using synchrophasor measurements

The authors propose a smart transmission system islanding scheme during an out-of-step (OOS) condition using PMU data. An OOS condition leads to the formation of electrical centers on a few transmission lines. The distance relays on the lines misinterpret it as a bolted three-phase fault and trip leading to an uncontrolled system separation. The load-rich islands can blackout due to massive generation-load imbalance. Recent research has shown that the evolution of electrical centers can be tracked by PMUs and hence, distance relays on these lines can be temporarily blocked from operation. The authors now propose an adaptive islanding scheme wherein (i) the islands contain coherent generators and (ii) overall load shed is minimised. In other words, the authors propose a simple and efficient method for determining the optimal cutset using PMU data. The method does not require explicit coherency determination of generators and can be implemented within the time interval of two PMU frames (40 ms in India). Simulation results on the 16-generator system and the Indian power system demonstrate the efficacy of the proposed method.

Line Impedance Estimation Based on Synchrophasor Measurements for Power Distribution Systems

Effective monitoring and management applications on modern distribution networks (DNs) require a sound network model and the knowledge of line parameters. Network line impedances are used, among other things, for state estimation and protection relay setting. Phasor measurement units (PMUs) give synchronized voltage and current phasor measurements, referred to a common time reference (coordinated universal time). All synchrophasor measurements can thus be temporally aligned and coordinated across the network. This feature, along with high accuracy and reporting rates, could make PMUs useful for the evaluation of network parameters. However, instrument transformer behavior strongly affects the parameter estimation accuracy. In this paper, a new PMU-based iterative line parameter estimation algorithm for DNs, which includes in the estimation model systematic measurement errors, is presented. This method exploits the simultaneous measurements given by PMUs on different nodes and branches of the network. A complete analysis of uncertainty sources is also performed, allowing the evaluation of estimation uncertainty. Issues related to operating conditions, topology, and measurement uncertainty are thoroughly discussed and referenced to a realistic model of a DN to show how a full network estimator is possible.

Electromechanical Mode Estimation in the Presence of Periodic Forced Oscillations

Electromechanical modes are inherent to any interconnected power systems which provide a measure of the small-signal stability margin of the system. A number of algorithms have been developed for the estimation of these modes using synchrophasor measurements. However, most of these algorithms are not designed to operate in the presence of forced oscillations (FO). These FOs are results of periodic rogue input driving the system. When FOs are present, estimates of system modes can be biased depending on the frequency and the amplitude of the FOs. To tackle this problem, a new algorithm is proposed in this paper to estimate system modes in the presence of FOs. In the proposed method, the over-determined modified Yule–Walker method which is used to estimate autoregressive coefficients of an autoregressive moving average (ARMA) signal model is extended to an ARMA with exogenous input (ARMAX) model that incorporates the presence of FOs. Two versions of the proposed method are included in this paper based on the requirement of the information of the duration of FOs in the signal. Results obtained by implementing the proposed algorithm on simulated data and real-world data validate the effectiveness of both versions of the proposed method.

Detection of Periodic Forced Oscillations in Power Systems Using Multitaper Approach

An algorithm based on Thomson's multitaper spectral estimation and harmonic analysis techniques is proposed for the detection and frequency estimation of periodic forced oscillations in a power system. Unlike traditional periodogram-based techniques, the method does not rely on true ambient noise spectrum of the system, and can operate continuously in an online environment without requiring any system knowledge except synchrophasor measurements. It compares a test statistic derived from only measurements against a threshold, and the threshold is established from general expressions of the test statistic's distribution and the probability of false alarm. Performance of the detector is explicitly expressed using probability of detection expression, and evaluated using simulation studies. Results upon application of this algorithm to field measured synchrophasor data suggest usability of the technique for forced oscillation detection in practical monitoring of the power system.

PMU Multilevel End-to-End Testing to Assess Synchrophasor Measurements During Faults

This paper introduces a framework for comprehensive testing and evaluation of the phasor measurement units (PMUs) and synchrophasor systems under normal power system operating conditions, as well as during disturbances such as faults. The evaluation is suggested to be accomplished using three different testing approaches, namely, type testing, application testing, and end-to-end testing, for each of which, systematic characterization of the hardware and software modules is presented in detail. Through the proposed approach of PMU testing in a controlled environment and detailed analysis of different estimation techniques used in PMU algorithms, one can gain insights on which estimation technique is most accurate for a certain end-use application. This hypothesis has been validated through series of realistic test scenarios on a 23-bus system running on an Opal Real Time simulator using the hardware-in-the-loop interface. In addition, the impact of synchrophasor estimation errors and their propagation from the PMU toward the end-use applications has been quantified for a fault location algorithm that uses only PMU measurements.

A Priority-Based Multistage PMU Installation Approach for Direct Observability of All Network Buses

The highly precise synchrophasor measurements obtained from the phasor measurement unit (PMU) are important for an effective implementation of a wide-area monitoring, protection, control, and self-healing (WAMPCAS) power system. The overall performance of the WAMPCAS power system can be improved if the PMUs are installed at all the buses in a transmission network. However, the multistage PMU installation is obligatory as PMU installation at all network buses is a matter of large-scale investment. Priority should be given to the important buses during the initial and intermediate stages to obtain relatively better observability. The optimal PMU installation (OPI) should be determined at the preliminary stage to measure the voltage phasors of all buses with the least number of PMUs. To evaluate the OPI problem, an improved binary shuffled frog leaping algorithm (IBSFLA) was proposed for the IEEE 118-bus test system. To enhance the overall performance of the IBSFLA and to obtain possible multiple optimal solutions (MOSs), an improved initialization and similarity-checking assessment were developed. A bus-observability maximization was mathematically modeled to select the best solution from MOSs, and the efficacy of the proposed algorithm was verified by comparing its performance with other algorithms.

A Prediction Algorithm to Enhance Grid Resilience Toward Cyber Attacks in WAMCS Applications

Monitoring and control of electrical power grids are highly reliant on the accuracy of the digital measurements. These digital measurements reflect the precision of the installed sensors, which are vulnerable to the injection of unknown parameters in the form of device malfunction and cyberattacks. This may question the operational security and reliability of many cyberphysical infrastructure such as smart grid. To resolve this issue, a multisensor temporal prediction based wide-area control scheme is proposed in this paper. The feasibility of the designed scheme is verified in an advanced synchrophasor measurements based wide-area monitoring and control system (WAMCS). This WAMCS adopts a flexible ac transmission system device (the primary controller) for controlling the smart grid's voltage profile. The algorithm is validated in a real-time environment with an innovative software-in-the-loop testing setup. The performance of the proposed technique in the presence of false-data-injection attacks shows promising results.

Detection of Periodic Forced Oscillations in Power Systems Incorporating Harmonic Information

This paper derives an improved version of a periodogram detector for detecting forced oscillations (FOs) in power systems using synchrophasor measurements. FOs are usually periodic in nature and are often accompanied with multiple harmonic components. This harmonic information of FOs is incorporated into the proposed periodogram detector, which significantly improves its detection performance for a given probability of a false alarm. The original periodogram detector carries out detection of each component of FOs separately, even though they are related through their harmonics. In the proposed periodogram detector, the detection algorithm is re-derived by incorporating harmonic information such that the detector now looks for a combination of harmonic components of FOs for detection. This derivation shows a significant improvement in the detection performance of the proposed periodogram detector as compared to the original one. This is also illustrated by the results obtained by implementing the proposed periodogram detector on the simulated and real-world PMU measurements.

Robust Online Estimation of Power System Center of Inertia Frequency

The real-time center of inertia frequency plays an important role in power system stability analysis and control. This letter proposes a robust approach to identify power system center of inertia frequency with consideration of system uncertainties and synchrophasor measurement quality. A model decoupling strategy is first presented by taking measured generator active power as the swing equation input, whereas remaining the bus frequency as output. This allows deriving the linear discrete-time state-space form, which will be used by the robust Kalman filter for generator rotor speed, angle, and inertia estimation. The robust Kalman filter is mandatory as the measured frequency can change abruptly due to impulsive noise or system sudden changes. Simulations carried out on the IEEE 39-bus system validate the effectiveness and robustness of the proposed approach in the presence of various sources of uncertainties.

SA102GENETIC AND CLINICAL ANALYSES OF PSYCHOSIS SPECTRUM IN A LARGE MULTI-ETHNIC YOUTH COHORT (N>8,000) REVEAL SIGNIFICANT LINK WITH ADHD

The power system at present is a complex network that accommodates several applications with diverse requirements. For the stable operation of this network the wide area synchrophasor measurement system (WASMS) has been instituted. The WASMS consists of several measuring devices called the phasor measurement units (PMUs), for collecting the information pertaining to the subtleties of the power grid, which is in the form of time-synchronized phasors measured at various spatial locations in the power system. The synchronization in the time domain is achieved by using the global positioning system timing signals. These synchronized phasors are communicated to the phasor data concentrator where the data is analyzed for detection and control of the power system abnormalities. Reliable performance of the WASMS is quintessential for effective monitoring and subsequent decision-making. Risk assessment of this system prior to its actual deployment would help the power system engineers in the design of fault-tolerant monitoring system. Risk quantifies the severity of failure, and uncertainties in the system parameters pose a major impediment for the accurate determination of the system’s risk. Therefore uncertainty analysis has to be included in the risk assessment framework for obtaining a better estimate. The aim of this book chapter is to present a Monte Carlo simulation (MCS)–based uncertainty analysis and risk assessment of the WASMS. MCS can model simultaneous component failures and is widely used for estimating the failure rates of complex systems. It can also model complex interconnections that are neither series nor parallel. MCS models are presented for the PMU and its communication system. With the uncertainty analysis included in the risk assessment, the WASMS is optimally designed such that the risk is minimized without compromising the system’s observability. Case study results of an Indian power system are presented to elucidate the proposed approach.

Wind Power Monitoring and Control Based on Synchrophasor Measurement Data Mining

More and more countries and utilities are trying to develop smart grid projects to make transformation of their power infrastructure towards future grids with increased share of renewable energy production and near zero emissions. The intermittent nature of solar and wind power can in general cause large problems for power system control. Parallel to this process, the aging of existing infrastructure also imposes requirements to utility budgets in the form of a need for large capital investments in reconstruction or maintenance of key equipment. Synchrophasor and other synchronized measurement technologies are setting themselves as one of the solutions for larger wind power integration. With that aim, in this paper one possible solution for wind power control through data mining algorithms used on a large quantity of data gathered from phasor measurement units (PMU) is described. Developed model and algorithm are tested on an IEEE 14 bus test system as well as on real measurements made on wind power plants currently in operation. One such wind power plant is connected to the distribution grid and the other one to the transmission grid. Results are analyzed and compared.

Cyber-Physical System Analysis of Communication Networks Utilising Synchrophasors in a Smart Grid

The electrical grid is often hailed as one of the 20th century's greatest technical achievements. While it is undeniably a feat of engineering, it is in dire need of updating to keep up with things like two-way dynamic energy management, load balancing, enhanced metering, the incorporation of renewable energy sources, protection and control, etc. The term "Smart Grid" (SG) is used to describe this updated electrical network. Rapid progress in communication technology has made it possible to create the envisioned SG. The SG may be seen as a Cyber Physical System (CPS), with the physical system being the infrastructure of the power grid and the cyber system being the communication and computing technologies, sensors, actuators, etc. A Smart Grid Cyber Physical System (SGCPS) is a CPS-based conceptualization of an SG. CPS technology is expanding rapidly, which has allowed the SG's capabilities to grow even further. In SGCPS in particular, the SG's security and management are tweaked to improve consistency of functioning. With synchrophasor measurement, SG has gained traction from a safety and regulation perspective. The sinusoidal voltage and current of electrical buses in the smart grid may be measured using a time-synchronized phasor measurement called synchrophasor measurement. High-speed sensors, known as Phasor Measurement Units (PMUs), collect the synchrophasor information. The Phasor Data Concentrator (PDC) at the command centre receives the synchrophasor information. Synchrophasor data is sent from PMUs to PDCs through a communication network known as the Synchrophasor Communication Network (SCN), which serves as the backbone of the synchrophasor applications.

Inertia Estimation of Wind Power Plants Based on the Swing Equation and Phasor Measurement Units

High penetration of wind power plants may have an adverse impact on power systems’ stability by reducing the inertia, and problems like frequency stability could appear due to total inertia in the system being reduced, making the power system more vulnerable to disturbances. However, most recent grid codes include an emulation inertia requirement for wind power plants, because modern wind turbines are capable of providing virtual inertia through power electronic converter controls to improve frequency stability issues. Because of this, it is necessary that the inertia estimation analyze and quantify the impact of the inertia reduction in power systems. In this paper, an implementation of a methodology for the inertia estimation of wind power plants is presented. It is evaluated through synchrophasor measurements obtained from a Real-Time Digital Simulator (RTDS) implementation, using industrial Phasor Measurement Units (PMUs). This methodology is based on the swing equation. Furthermore, a comparison of the results obtained between two professional tools RSCAD and DIgSILENT PowerFactory is performed, in order to evaluate the accuracy and the robustness of the methodology. This methodology is applied for the inertia estimation of an equivalent of the southeast zone of the Mexican power system, where there is a large-scale penetration of wind power plants. The results demonstrate that this methodology can be applied in real power systems using PMUs.

Modelless Data Quality Improvement of Streaming Synchrophasor Measurements by Exploiting the Low-Rank Hankel Structure

This paper presents a new framework to improve the quality of streaming synchrophasor measurements with the existence of missing data and bad data. The method exploits the low-rank property of the Hankel structure to identify and correct bad data, as well as to estimate and fill in the missing data. The method is advantageous compared to existing methods in the literature that only estimate missing data by leveraging the low-rank property of the synchrophasor data observation matrix. The proposed algorithm can efficiently differentiate event data from bad data, even in the existence of simultaneous and consecutive bad data. The algorithm has been verified through numerical experiments on recorded synchrophasor datasets.

Data-Driven Estimation of Frequency Response From Ambient Synchrophasor Measurements

With the wide deployment of synchrophasor technology, measurement-based dynamic modeling and studies have been becoming increasingly useful for real-time grid operations. This paper considers the problem of estimating the power system frequency response from ambient synchrophasor measurements. Specifically, we develop the analytical conditions for establishing the equivalence between the cross correlation of ambient generator speed data and the system frequency response between any two locations. Our conditions, relying on uniformly damped and equally excited oscillation modes, extend earlier work on electromechanical wave propagation modeling to nonhomogeneous power networks. Numerical results suggest that the validity of the cross correlation approach would hold for more realistic conditions such as nonuniform damping and high-order generator model. Its practical value is further corroborated by real-data results, which closely match with the actual propagation time of electromechanical waves recorded during the 2008 Florida blackout in the Eastern Interconnection system.

An Extended Kalman Filter Approach for Accurate Instantaneous Dynamic Phasor Estimation

This paper proposes the application of a non-linear Extended Kalman Filter (EKF) for accurate instantaneous dynamic phasor estimation. An EKF-based algorithm is proposed to better adapt to the dynamic measurement requirements and to provide real-time tracking of the fundamental harmonic components and power system frequencies. This method is evaluated using dynamic compliance tests defined in the IEEE C37.118.1-2011 synchrophasor measurement standard, providing promising results in phasor and frequency estimation, compliant with the accuracy required in the case of off-nominal frequency, amplitude and phase angle modulations, frequency ramps, and step changes in magnitude and phase angle. An important additional feature of the method is its capability for real-time detection of transient disturbances in voltage or current waveforms using the residual of the filter, which enables flagging of the estimation for suitable processing.

Decentralized Load Shedding Method Based on Voltage Stability Margin Index Using Synchrophasor Measurement Technology

This study develops an analytical method for assessing the voltage stability margins of a decentralized load shedding scheme; it then examines the challenges related to the existing load shedding scheme. It also presents a practical application for implementing the proposed method, based on the synchrophasor measurement technology in modern power grid operations. By applying the concept of a continuously-computed voltage stability margin index to the configuration of the Thévenin equivalent system, the maximum transfer power could be used as an index to monitor the voltage instability phenomenon and thus determine the required load shedding amount. Thus, the calculated voltage stability margin might be a useful index for system operators in the critical decision-making process of load shedding. Dynamic simulations are performed on real Korean power systems as case studies. Simulation results, when comparing the existing and proposed methods, showed that there was a considerable reduction in the amount of load shedding in the voltage instability scenario. This indicates that the synchrophasor measurement technology has a considerable effect on the proposed load shedding method. The simulation results have validated the performance of the proposed method.

Automated Failure Diagnosis in Transmission Network Protection System Using Synchrophasors

In this paper, a multihypothesis-based centralized Failure Diagnosis in Protection System (FDProSys) tool using phasor measurement units (PMU) data has been proposed to systematically and automatically detect malfunctions or failures in protective devices. The proposed diagnostic algorithm and FDProSys tool employs synchrophasor measurements to select a section of the network called ProNet, with possible device malfunction. Multiple hypotheses have been generated automatically based on node incidence matrices and multihypothesis theory. The malfunction of the protective devices in the presence of fault and relay operation is identified by comparing the five-digit message of the real event with multiple hypotheses. Trustworthiness of PMU data caused by common failures, such as communication outage and GPS problems, has also been considered by the proposed algorithm using the PMU status flag. The developed tool FDProSys can also work with supervisory control and data acquisition data assisted by manual analysis with less accuracy and is robust enough to several PMU/relay failures. Simulation results using the IEEE 14-bus, IEEE 57-bus, and IEEE 300-bus systems demonstrate the accuracy of the developed algorithm.

Improved synchrophasor measurement to capture sub/super‐synchronous dynamics in power systems with renewable generation

The existing phasor-measurement unit (PMU) and wide-area measurement system (WAMS) based on the fundamental synchrophasors are insufficient to accurately capture the dynamics of sub/super-synchronous resonance or oscillation (SSR/SSO). To address this issue, this study proposes a new method for the simultaneous and precise measurement of the fundamental and multiple sub/super-synchronous harmonic phasors. It improves the classic discrete Fourier transform (DFT)-based method by adding adaptive frequency detection, modal filtration and phasor correction and compensation. Thus, in the context of SSR/SSO, the phasors of both fundamental and interharmonic components can be precisely obtained at local PMUs and the control/data centre of WAMS. The basic procedures and the prototype implementation of the method have been elaborated, and the performance has been examined with simulation signals as well as the field data recorded from an actual SSO incident. The results have verified its high precision, noise immunity and fast response.

Fault test analysis in transmission lines throughout interfering synchrophasor signals

Abstract The distribution of power supplies be obliged to offer reliable, superior-quality in power. To obtain good power quality the transmission line faults identification should be more precise, consistence and complete rectification is required. The faults in the transmission and distribution lines influence the power quality. The major faults in transmission lines such as line to ground fault, line-to-line fault and three-phase faults. This paper proposes a unique organized interrelated structure for fault-location and classification technique for transmission lines through an experimental set-up similar to transmission and distribution for good power quality. The proposed method utilizes synchrophasor measurements during the disturbances from the transmission lines and compares with ideal condition signals for fault location and classification. From the results, the synchrophasor measurements identify faults in the initial stage. The phasor measurement results are modelled through regression modelling for precise measurement. Various faults are modelled for the earlier detection in the transmission lines.