Wide Area Measurement Research Articles

Transient Stability Assessment Based on Gated Graph Neural Network With Imbalanced Data in Internet of Energy

Transient stability assessment (TSA) plays an important role to ensure the safe operation of the power system in Internet of Energy (IoE). Many time-domain simulation (TDS)-based and transient energy function (TEF)-based methods have been proposed to assess the transient stability of the power system. With the wide area measurement system (WAMS) and the phasor measure units (PMUs) applied to observe the real-time data, methods of TSA based on the machine learning and data-driven are continuously studied. These kinds of methods can only assess the transient stability of the power system when subjected to large disturbances. However, these kinds of methods cannot infer the type of event which leads to the collapse of the power system. In this article, the gated graph neural network (GGNN) is applied to assess the power system transient stability and infer the type of event leading the instability of the power system. First, conditional generative adversarial network (CGAN) is applied to generate unstable samples making the training data more balanced. With the balanced data graph-structured and used to train the GGNN-based TSA model, the GGNN-based TSA model achieves better performances. Finally, the real-time data is input into the trained TSA model and the transient stability of the power system is assessed. When the power system is considered unstable, the proposed TSA model can also infer the type of event leading the instability of the power system, classifying the unstable state to the corresponding event. Simulations performed on the New England 39-bus system verify the effectiveness of the proposed method.

Cyber–physical testbed for Wide Area Measurement System employing IEC 61850 and IEEE C37.118 based communication

Wide Area Measurement Systems (WAMS) are well known for enhancing situational awareness of the grid using IEEE C37.118 phasors from Phasor Measurement Units (PMUs). Recently introduced IEC 61850-90-5 Routable Sample Values (R-SV) have proven promising to communicate timestamped synchrophasors to the control center, fulfilling the purpose. In wide area protection and control schemes, the communication of synchrophasors to the control center is also followed by sending back a supervisory decision signal (based on synchrophasor data) to the physical devices in the field. Development of WAMS testbeds for implementation and assessment of such schemes have often been addressed only from IEEE C37.118 PMU phasors’ perspective alone. This paper presents a comprehensive cyber–physical WAMS testbed capable of real-time communication of synchrophasors using both IEEE C37.118 PMU phasors and IEC 61850-90-5 R-SV. It also facilitates status and feedback signal communication between the control center and substations using IEC 61850-90-5 Routable GOOSE (R-GOOSE). The developed testbed integrates a real-time digital simulator (RTDS), industry-standard hardware devices such as PMUs, Phasor Data Concentrator (PDC), IEDs, Global Positioning System (GPS) synchronization clock, network components, and software components such as IEC 61850 emulator tools. It can be used for end-to-end implementation of a myriad of wide area monitoring protection and control (WAMPAC) applications. It can further facilitate vulnerability analysis of WAMS components, analyze the impact of cyber-attacks on critical applications, and then test and validate various security solutions for cyber resiliency of WAMPAC applications.

A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree.

The insulation state of high-voltage cables in coal mines directly influences the reliability of power supply in coal mines and the level of safe production. In this paper, the degradation mechanism of cable insulation is analyzed, and an online monitoring technology of cable insulation in coal mines based on decision tree is proposed, the technical principle of the judgment method of cable degradation based on decision tree is studied, the feasibility of this technology is verified through simulation, the existing online monitoring solutions for cable insulation are analyzed, and a wide-area synchronous measurement and monitoring system for cable insulation is designed. This technology has been applied in Chinese coal mine enterprises in China and achieved a good effect.

Malicious data injection attacks risk mitigation strategy of cyber–physical power system based on hybrid measurements attack detection and risk propagation

Malicious data injection attacks (MDIAs) can tamper with the measurements of the supervisory control and data acquisition (SCADA) system and wide area measurement system (WAMS), which seriously affect the state estimation of cyber–physical power system (CPPS). The existing researches mostly focus on SCADA system, ignoring the vulnerability of phasor measurement unit (PMU) in WAMS, and not considering that MDIA can propagate through the communication network of CPPS as a kind of network attack, which seriously affects the safe operation of CPPS. Aiming at these problem, a risk mitigation strategy based on SCADA/WAMS hybrid measurement networks is proposed. Firstly, a malicious data detection mechanism based on dynamic time warping (DTW) distance is proposed, which includes two parts: state predictor and malicious data identifier. Then, based on the attack detection results, a risk mitigation model is proposed which minimizes the risk level of the system by disabling the damaged meters caused by the propagation of malicious data, while maintaining the observability of CPPS. Finally, the cooperation mechanism of MDIA detection and multi-scenario risk mitigation strategy for hybrid measurement networks is proposed. Case study based on IEEE 14-bus system and IEEE 57-bus system verifies the effectiveness of the risk mitigation strategy proposed in this article.

Can Center-of-Inertia Model be Identified From Ambient Frequency Measurements?

This letter analyzes the difficulty of estimating power system inertia under ambient conditions using the Center-of-Inertia (CoI) system model. We show that the main obstacle to doing this is a difficulty in detecting a peak in the Power Spectral Density (PSD) of the frequency trace. This is due to a combination of two factors: (i) the Ornstein-Uhlenbeck (OU) process with a high mean-reversion time, which models the load disturbance and is mathematically equivalent to a low-pass filter with a high time constant; (ii) the CoI dominant mode is highly damped. This observation also explains why it is possible to estimate system inertia under ambient conditions using wide-area PMU measurements by exploiting information about inter-area oscillations which have lower damping than the dominant mode of the CoI model. We validated those findings by using the PSD of the actual 2-hour frequency trace for Great Britain from 00:00 to 02:00 of January 01, 2019.

Voltage instability curtailment and quality improvement with phasor measurement unit in power system

PurposeThe earlier methods are more resilient to improvements such as load shift and path change. This results in problems such as a voltage drop and a high reactive flux. In addition, due to the delay, congestion or interruption of the transmission, the system cannot receive all phasor measurement unit (PMU) measurements at the relevant time as well as the presence of noise in the received data.Design/methodology/approachWith the development of wide area measurement system technologies, it seems to be possible to track voltage stability online via time-stamped PMUs. As the voltage instability causes a voltage decomposition, voltage instability is one of the most important problems when monitoring the power supply.FindingsThis harmonic distortion significantly decreases the data quality in the grid. As a result, instability ascertainment based on PMU has been suggested as a method for detecting voltage instability in power systems monitored with PMU. In addition, a technique called instability amendment via load dropping has been proposed to keep the device from collapsing due to voltage failure.Originality/valueTo improve the power output, the power prominence melioration technique was developed. This proposed system has been implemented in MATLAB Simulink and compared with the recent researches.

Security enhancement of time synchronization and fault identification in WAMS using a two-layer blockchain framework

In this paper, we propose an auxiliary two-layer blockchain framework to improve the security and reliability of Wide Area Measurement Systems (WAMS) in smart grids against adverse manipulation of time synchronization and interference with fault identification. The framework benefits from the blockchain’s inherent advantages, such as distributed storage, consensus mechanism, and avoidance of single-point of failure while addressing typical challenges of employing blockchain technology in smart grids, such as the limitation of computation power and the high bandwidth requirements for data exchange. In the first layer of the proposed architecture, the security state of the system is determined based on the state opinion of Phasor Measurement Units (PMUs), using a consensus mechanism. Then, in the second layer, Phasor Data Concentrators (PDCs) use the first layer opinion to preserve the proper WAMS operation when some of the PMUs are compromised. In this setting and by utilizing a co-simulation testbed, we show the effectiveness of using smart contracts whereby PMUs and PDCs can reliably communicate and aggregate smart grid measurements while time synchronization and fault identification functionalities are appropriately maintained. We also evaluate several deployment scenarios and provide corresponding recommendations for the security enhancement of WAMS. Finally, we detail a fortification strategy that the Power System Operator (PSO) can use to harden the blockchain network, based on an adversarial model.

PMU placement with multi-objective optimization considering resilient communication infrastructure

A Phasor Measurement Unit (PMU) is the most advanced equipment used to bring a good level of situational awareness to Wide-Area Measurement System (WAMS) in power systems. However, the underlying cost for such PMU-based supervisory systems is the limiting factor that affects the extent of installed syncrophasor devices in a power network. This work aims to formulate the optimal PMU placement problem in a power transmission system which seeks to jointly minimize the risk of inobservability for State Estimation and also the overall total cost. Thus, it is proposed a multi-objective algorithm that uses numerical observability indicators to characterize measurement plan robustness and also graph theory tools to address the total cost optimization problem, which considers practical and more realistic aspects of the installation of PMUs, as well as addressing costs for the network communication infrastructure. Moreover, non-dominated Pareto solutions are built, which in a real scenario, would serve better for judicious decisions by the planners of a measurement system.

Resiliency Estimation of Synchrophasor Communication Networks in a Wide Area Measurement System

The power grid is evolving into a smart grid due to the diverse energy generation and distribution. This complex grid has to be continuously monitored in real-time for its safe operation. Sensors known as phasor measurement units (PMUs) are used for obtaining health information pertaining to the grid in terms of time-synchronized voltage and current phasors. Measurements from several PMUs are sent through a synchrophasor communication network (SCN) to the phasor data concentrator (PDC). The PMUs, the PDC and the SCN together constitute the wide area measurement system (WAMS). Being an important constituent of the WAMS, the resiliency estimation of SCNs is paramount for their proper design. Resilience is a measure of the systems resistance to the disturbances or a measure of its ability to bounce back to a functional state in the event of failure. This paper presents a quantitative metric for estimating the resiliency of SCNs. Monte Carlo simulation (MCS) models are used to simulate random component failures, and the data is used for measuring the resiliency of the SCNs. A multi-objective genetic algorithm (GA) is used for optimizing the placement of PMUs and the PDC, to observe the power system with the minimum number of PMUs, and to simultaneously maximize the resilience. The practical power grid of West Bengal, India, is analyzed as a case study. This work can be a significant contribution to the power sector as it assists in the proper planning and placement of the communication infrastructure in a WAMS.

Data network traffic analysis and optimization strategy of real-time power grid dynamic monitoring system for wide-frequency measurements

The application and development of a wide-area measurement system (WAMS) has enabled many applications and led to several requirements based on dynamic measurement data. Such data are transmitted as big data information flow. To ensure effective transmission of wide-frequency electrical information by the communication protocol of a WAMS, this study performs real-time traffic monitoring and analysis of the data network of a power information system, and establishes corresponding network optimization strategies to solve existing transmission problems. This study utilizes the traffic analysis results obtained using the current real-time dynamic monitoring system to design an optimization strategy, covering the optimization in three progressive levels: the underlying communication protocol, source data, and transmission process. Optimization of the system structure and scheduling optimization of data information are validated to be feasible and practical via tests.

Data source authentication for wide-area synchrophasor measurements based on spatial signature extraction and quadratic kernel SVM

As essential components of the wide-area measurement system (WAMS), phasor measurement units (PMUs), frequency disturbance recorders (FDRs) and universal grid analyzers (UGAs) collect valuable data continuously to reveal the dynamic variations of power systems and to enhance the operators’ situational awareness ability. However, these devices are vulnerable to multiple types of data exception emerging in recent years, such as data source ID mix exception spoofing, substantially threatening system security. To ensure the cyber security of WAMS, this work proposes a new spatial signature extraction method, followed by the quadratic kernel support vector machine (QKSVM)-based algorithm, to authenticate data source in WAMS. First, the load–frequency characteristic (LFC), which can represent the impacts of load variations on frequency, is utilized to extract the spatial signatures of FDRs located in different regions. Then, the quadratic kernel function is employed in the QKSVM-based algorithm to map the signatures into Hilbert space to authenticate the data source more accurately. Finally, case studies in the U.S. Western and Eastern power systems show that the proposed model-free algorithm is less sensitive to system sizes, and can achieve a higher authentication accuracy in a much shorter window length compared with other algorithms.

Delay dependent wide area damping controller with actuator saturation and communication failure for wind integrated power system

Integration of wind farm with power system introduces nonlinearity and complexity of the power system, which deteriorates the performance of a wide area damping controller (WADC). A WADC is designed in this paper for wind energy conversion system (WECS) integrated power system taking the communication latency and communication failure of the wide area measurement system (WAMS) into consideration. Apart from communication delay and communication failure, the effect of saturation is also considered in this paper. A state feedback stabilizing controller is designed using linear matrix inequality (LMI) platform. The control signal chosen here is combination of local and global signal to ensure stability during communication failure. The inter-area oscillation is reduced by controlling the reactive power of the wind farm. The effectiveness of the controller developed is verified using a WECS integrated modified 11-bus test system and modified IEEE 39-bus test system. The simulation results show that the designed controller guarantees stability and also can eliminate inter-area oscillations effectively of a WECS integrated power system.

Real-Time Event Detection Based on Weibull Distribution Using Synchrophasor Measurements for Enhanced Situational Awareness

The proliferation of Phasor Measurement Units (PMUs) to monitor power grid dynamics at a high resolution (10–100 samples/sec) has opened a new paradigm to situational awareness. Existing event detection techniques for identifying multiple events like transmission line faults, generation trip, line trip, load loss, current transformer (CT) failure, islanding, etc., are prone to misdetection, delayed detection, and false detection. Moreover, most of them can detect events either with fast (transient events) or slow dynamics (oscillatory and excursion events) using synchrophasor measurements. This paper focuses on detecting events with both fast and slow dynamics using wide-area frequency measurements. To this end, a novel method is proposed based on Weibull distribution, which we call as Weibull-based Excursion Transient and Oscillatory (WETO) method. The WETO method can identify the time of inception, location, and severity of the event in near real-time using only a single parameter, known as variability. The events are detected within a time window of 5 cycles using only frequency measurements. The proposed method is validated for the Indian as well as the North American grid disturbances, and the results show that it would be beneficial to the system operator in visualizing the true situation of the grid events.

Denial-of-Service Attacks Pre-Emptive and Detection Framework for Synchrophasor Based Wide Area Protection Applications

Synchrophasor technology has been very effective in addressing complex protection problems. Based on the experimental study of the impact of denial-of-service (DoS) cyberattacks on synchrophasor-assisted protection scheme, “adaptive dependability/security bias protection scheme,” a DoS pre-emptive and detection framework is presented in this article. The suggested structure helps in the identification of different types of DoS attacks (targeting data availability) and address resolution protocol (ARP) spoofing (compromising data confidentiality) via unique fingerprints developed using Wireshark network data. Redundant PDC datastream and random data path selector module (RDPS) in the framework help reduce the probability of a successful DoS attack. However, during a successful attack, the framework ensures that a healthy PDC datastream is used by the end application. The proposed methodology's efficacy has been verified using a western system coordinating council 9 bus, and IEEE 39 bus test systems on the real-time digital simulator (RTDS) based cyberphysical wide area measurement system testbed with industrial standard hardware phasor measurement units (PMUs). The results show that the proposed framework can effectively improve the performance of the synchrophasor-based adaptive dependability/security bias scheme during DoS attacks and avoid maloperation of the protective devices, which enhances the power system's stability.

Cyber-Attack Identification of Synchrophasor Data Via VMD and Multifusion SVM

A large amount of synchrophasor data in the wide area measurement system (WAMS) needs to be collected and transmitted to the phasor data concentrator, thereby increasing the possibility of being attacked by hackers. The attacked data are therefore hidden into the normal synchrophasor data so that the synchrophasor data based application will be affected. To remedy this problem, an identification framework is proposed to detect the data cyber-attack in WAMS utilizing variational mode decomposition (VMD) and multifusion support vector machine (MSVM). First, VMD is used to transform the attacked data into multiple modal components. Thereafter, a novel MSVM is employed to classify the deterministic features using the proposed linear combined multikernel (LCM). This LCM can fuse multiple types of features, including the time, frequency, and statistical domains of the synchrophasor data. Utilizing the actual data from FNET/GridEye, different experiments are conducted under multiple attack strengths and types. The results demonstrate that the identification framework has higher precision and robustness compared with other conventional classifiers.

Fast Path Recovery for Single Link Failure in SDN-Enabled Wide Area Measurement System

In the wide area measurement system (WAMS), the end-to-end transmission delay between the phasor measurement unit (PMU) and phasor data concentrator (PDC) is strictly constrained for real-time monitoring and protection applications. When a communication link failure happens, fast path recovery is required to reduce the impact of measurement losses. In this work, the promising software-defined network (SDN) technique is leveraged to compute the re-routing path in a global view upon a single link failure. More specifically, a hybrid fast path recovery algorithm (HFPR-A) is proposed based on the principle of simplicity: in some cases, the shortest path or approximate shortest path between PMU and PDC can be recovered by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adding only one edge</i> to the original forwarding tree; while in the other cases, the shortest paths can be recovered with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">lower computational complexity</i> than the traditional Dijkstra’s algorithm. The proposed HFPR-A is implemented on the Ryu + Mininet testbed, and the simulation results on different IEEE benchmark test power systems show that the proposed HFPR-A could find shorter re-routing paths than the existing methods with a low-enough response time.

Influence of Sensor Feedback Limitations on Power Oscillation Damping and Transient Stability

Fundamental sensor feedback limitations for improving rotor angle stability using local frequency or phase angle measurement are derived. Using a two-machine power system model, it is shown that improved damping of inter-area oscillations must come at the cost of reduced transient stability margins, regardless of the control design method. The control limitations stem from that the excitation of an inter-area mode by external disturbances cannot be estimated with certainty using local frequency information. The results are validated on a modified Kundur four-machine two-area test system where the active power is modulated on an embedded high-voltage dc link. Damping control using local phase angle measurements, unavoidably leads to an increased rotor angle deviation following certain load disturbances. For a highly stressed system, it is shown that this may lead to transient instability. The limitations derived in the paper may motivate the need for wide-area measurements in power oscillation damping control.

A Transient Stability Assessment Model Based on Fault Severity Assignment

Maintaining accurate and fast transient stability is essential for safe operation of the power system. With the development of wide-area measurement system, machine learning–based transient stability assessment has become the trend. However, in realistic application of the power system, the impacts on evaluation rules between critical samples and noncritical samples are different. Thus, an improved cost-sensitive coefficient assignment method based on fault severity is proposed. First, the fault severity of each unstable sample is calculated. Then, the correction coefficient of the loss function of the unstable sample is linearized according to different fault severities. The closer the sample is to the critical case, the higher the cost coefficient is. Finally, the improved cost-sensitive method is combined with the deep learning model and tested in the IEEE-39 bus system. As shown in the results, the improved cost-sensitive method, which gives different correction coefficients to samples according to different fault severities, has better performance.

Damping of Subsynchronous Resonance in Utility DFIG-Based Wind Farms Using Wide-Area Fuzzy Control Approach

This paper presents a novel fuzzy control scheme for damping the subsynchronous resonance (SSR) according to the wide-area measurement system (WAMS) in power systems including doubly fed induction generator (DFIG)-based wind farms connected to series capacitive compensated transmission networks. The SSR damping is attained by adding the fuzzy controller as a supplementary signal at the stator voltage loop of the grid-side converter (GSC) of DFIG wind farms. Additionally, time delays due to communication signals are important when using WAMSs. If the time delays are ignored, it causes system instability. In this paper, the time delays are modeled with a separate fuzzy input to the controller. The new fuzzy control approach is executed by using the angular velocity of synchronous generators (w) and its variation in the angular velocity (dw/dt). The effectiveness and success of the WAMS-based fuzzy controller is demonstrated by comparison with the particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) optimization methods. The efficacy and validity of the planned auxiliary damping control are verified on a modified version of the IEEE second benchmark model including DFIG-based wind farms via time simulations using the MATLAB/Simulink toolbox.

An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles

Modern power system requires advanced and intelligent sensors-based protection such as a Phasor Measurement Unit that can provide faster, accurate, and real-time data acquisition. The aim is to allow accurate action-based performance for analysts in monitoring the transmission lines so that rapid actions can be taken during abnormal circumstances before the blackout occurs. Among different algorithms, this study focuses on modelling the non-recursive phasor estimation method in a power Simulink environment for a standard test system equipped with a developed algorithm to detect the fault zone. The algorithm includes an index for faulty bus classification based on the positive-sequence voltage measurements of the pre-fault and post-fault conditions, where the bus with a maximum differential percentage is identified as a faulted bus. An important differentiation of this work is that the proposed algorithm can coordinate with all phasor measurement units to accurately determine the faulty line using the index of unwrapped dynamic phase angles. Furthermore, the robustness of the indices is analyzed in the presence of sudden load change, measurement noise, and during nonlinear high-impedance faults. The performance of the comprehensive algorithm is investigated on the IEEE 9-bus and 39-bus standard test systems by applying different faults scenarios, considering several factors such as fault inception angles, line-fault resistance, ground-fault resistance. The comparative studies have shown that the proposed indices can play a significant role in segregating the fault and non-fault conditions, as they are needed to supervise the appropriate relays for enhancing the overall security of the power grid.