Synchronized Phasor Measurement Units Research Articles

Assessment of Power System Stability During Transients Using Deep Residual Shrinkage Network and CBAM Integration

Aiming at the noise that may exist in the data collection and transmission of power system synchronous phasor measurement unit (PMU), as well as the imbalance between stable and unstable samples, making the model likely to tilt to most kinds of samples, thus affecting the evaluation results of power system transient stability model, a transient stability assessment method integrating Convolutional Block Attention Module (CBAM) and deep residual shrinkage network is proposed. First, the mapping relationship between the input values and the labels of the stability results is established, and the electrical quantities are transformed into the form of convolutional feature maps to be input into the model. Second, channel attention module and spatial attention module are introduced, and soft threshold function is used to automatically learn the noise threshold and reduce the interference of the noise. As the model tends to favor the majority of the samples during training, gradient harmonized mechanism (GHM) loss function is introduced to improve the attention of the minority of samples as well as the training effect and evaluation performance of the model. Finally, the model is tested by simulation on the IEEE39 node system.

Dynamic state estimation of distribution networks with mixed measurements based on Cubature Kalman Filter

The integration of synchronized phasor measurement units (μPMU) has introduced diverse data sources into the distribution network. Each has distinct time scales and precision levels. To enable effective decision-making, it is crucial to amalgamate these measurements efficiently, ensuring both speed and accuracy in distribution network state estimation. This study explores a dynamic state estimation approach for distribution networks, employing Cubature Kalman Filtering (CKF) as the central methodology. By deeply fusing μPMU, AMI and SCADA data and incorporating CKF techniques, it improves accuracy and stability, which is validated on the IEEE 37-node system. This research supports advanced distribution network apps and large-scale data analysis.

Analysis of Bus Vulnerability Conducted Using a Synchronized Phasor Measurement Unit in Order to Achieve the Maximum Observability

Phasor measurement units (PMUs) have gained significant interest in recent decades. These instruments are used to measure synchronized phasor data. PMUs are gradually but definitely taking over power grids because of the significant phasor information that they generate for both regular and irregular conditions for the purpose of maintaining safety and control. PMUs may be used for a variety of purposes, including state estimation, which is a common task. In order to make state estimation more reliable, a variety of approaches have been looked into, and one of them is the positioning of PMUs. This paper provides a plan for the implementation of the PMUs, taking into account the potential for failure and vulnerability posed by PMU-equipped buses. Two separate studies were carried out and evaluated with the goal of solving the optimum PMU placement problem (OPPP), which pertains to the grids. The findings of the first study show that the maximum bus observability may be accomplished with the fewest possible number of PMUs, even while taking into consideration the fact that there is a risk that one or more PMUs would malfunction. This investigation was carried out with common measures such as zero injection bus (ZIB) and branch flow measurements, both with and without them, in order to assess the outcomes. The second research focused on selecting the PMU-equipped bus’s vulnerability analysis as its primary area of investigation. All of the tests were completed by using binary integer linear programming. Specifically, the described method is meant to be used with an existing PMU framework and in the case that new locations for new PMUs are necessary to be furnished with existing PMUs. This results confirm that the recommended strategy can be implemented successfully on the IEEE benchmark test systems.

Allocation of synchronized phasor measurement units for power grid observability using advanced binary accelerated particle swarm optimization approach

Large-scale power grid observability is still a challenge because of deteriorating infrastructure and the incorporation of renewable energy sources. A smart grid that makes use of cutting-edge technology, such as a phasor measurement unit (PMU), is an excellent option for monitoring and bringing networks up to speed with the latest information. Latterly, the considerable investment required for the deployment locations has slowed down the adoption of PMU. Therefore, because PMUs are expensive, it is necessary to deploy them in the best possible places on large-scale power grids. The most significant share of optimal PMU placement problems (OPPP) is defined as 0–1 knapsack problems. Considering this, the development of an effective optimization technique that can handle difficulties has emerged as an appealing topic in recent years. In this paper, a meta-heuristic algorithm based on the binary particle swarm algorithm (BPSO), a binary accelerated particle swarm optimization (BAPSO), is offered for solving OPPP. Since earlier research has shown that BPSO is likely to stick to local optima, the majority of them evaluated their suggested technique using small-scale test systems. The technique that has been suggested searches for the optimal solution by employing two topologies—one global and one local—that are analogous to BPSO. This work determines the optimal PMU position for a large network in a reasonable amount of time by fine-tuning the acceleration factor. Additionally, in order to employ fewer PMUs, an integration strategy was put into place for the radial buses. The OPPP solutions are provided by the suggested method within a reasonable period with prior solutions published in reliable publications, according to computational findings.

An Optimization-Based Robust Dynamic State Estimation for Power Systems with Synchronized Phasor Measurement Units, Involving Disturbance Rejection

State estimation provides the best estimate of the system states using a set of measurements that is divided into two main classes; static and dynamic types. The state estimator should provide an acceptable response in the presence of system changes and/or disturbances. To achieve this aim, considering the high rate of data changes and the high volume of exchanging information, the phasor measurement units could play an outstanding role. Furthermore, due to the inevitable errors of the measurements, and to provide an authentic estimate of the system states using the measured data, a state estimator should be able to eliminate or decrease the undesirable effect of bad data or outliers on the final output of the process. This type of state estimator is called a robust type. In this paper, a dynamic state estimator for a system with the synchronized phasor measurement units is utilized, which is capable of decreasing the effect of disturbances. Simultaneously, the robustness of the state estimation process in the presence of outliers is considered, which enables the state estimation process to reduce the negative effect of outliers on its final output. Therefore, the implemented process is called a robust dynamic state estimation method. By defining different scenarios and utilizing numerical indices, simulation results are thoroughly analyzed based on an explanatory three-bus network and the IEEE standard 14-bus and 57-bus networks using the MATPOWER tool.

INCREASING AN ACCURACY OF CONTROL ACTION VOLUME CALCULATION IN CENTRALIZED EMERGENCY CONTROL SYSTEM FOR STATE ESTIMATION OF POWER SYSTEMS

The paper presents the results of the study on the effectiveness and advisability of voltage’s and current’s angles usage, collected from a wide-area monitoring system, to increase an accuracy of control actions volume calculation in case of power system’s state estimation. Centralized emergency control system architecture of a power pool system is shown to better understand the research core. We emphasize that the state estimation software module is the key module in a high level hardware and software package. Ways of telemetry and synchronized phasor measurements collection are outlined. For research practice, Gauss-Newton mathematical method is modified via measurement vector, vector-function, and scalar matrix of weight coefficients. Experiments are provided by IEEE 14-bus power system and 500–220 kV real backbone network. These power systems have several control areas, connected by interchanges. According to experiment results, we conclude that using not only voltage’s and current’s modules but also angles increases an accuracy of control actions volume calculation and effectiveness of a centralized emergency control system operation in the part of a control action formation. Therewith, the usage of current’s modules and angles raises the execution time of the state estimation software module. It is undesirable for real time systems operation. Therefore, it is reasonable to take into account current’s modules and angles only for those interchanges in emergency mode, when intensity factor, characterizing the limit of static stability, is more than 0.92. We also find out that control action volume calculation is sensitive to mistakes in current’s angles measurements. Thus, for reliable usage of current’s modules and angles as data for a state estimation and control action volume calculation, it is necessary to prevent timing errors of synchronized phasor measurement units and also develop a phase shift correction algorithm.

Minimizing the Total Cost of WAMS Using Artificial Electric Field Algorithm

Wide area monitoring system (WAMS) is one of the most important technologies in modern power systems, it gathers the synchronized time stamped measurements from wide area across power system through a high reporting measuring device such as synchronized phasor measurement units (PMUs).Due to the high cost of PMU itself and its installation cost, it is often difficult to install PMU at each bus in the power system. However, there are several approaches to solve the optimal PMU placement (OPP) with various optimization algorithms. In this paper, a realistic cost model has been proposed to provide optimal PMUs placement (OPP). The proposed model has been solved using artificial electric field algorithm (AEFA), which is a novel optimization algorithm, it was proposed by 2019. In this paper, a binary form of AEFA has been proposed to solve the proposed cost model. AEFA has been implemented in MATALB programming environment, and the results demonstrate that the proposed cost model provides a realistic view of WAMS cost. Additionally, the results have been compared with other optimization algorithm, and it demonstrates that the AEFA is efficient to solve the OPP problem.

Synchronized Phasor Measurement Unit-Based Central Controller for Normal and Contingent Operation of a High-Capacity HVDC Macrogrid for the Continental US

This paper presents a Synchronized Phasor Measurement Unit (PMU) based controller to support the coordination and operation of a high-capacity high-voltage direct current (HVDC) macrogrid transmission for the continental US. The proposed controller allows for optimal scheduling of each segment of the multi-terminal HVDC network under normal and contingent conditions, while considering minimum levels of frequency response requirements. The performance of the proposed controller is tested on a 100,222-bus representation of the US Eastern and Western interconnections. Results show that a centralized PMU-based controller improves the frequency nadir of the HVDC macrogrid under contingency conditions by 25.9%. Furthermore, the primary frequency response (PFR) of the HVDC macrogrid is increased by 33.4%. The performance of each interconnection under the largest credible contingency conditions is also discussed.

Fault Location Algorithm in Distribution Networks Considering Distributed Capacitive Current

In recent years, with the expansion of urban scale and construction of energy infrastructure, more cities construct underground cables to replace overhead lines from the perspective of environment and safety. Thus, more distributed capacitive current flows back to distribution networks under fault conditions and affects the accuracy of fault locating. This paper proposes an iterative modification method of capacitive current to decrease the uncertainty of complex equations with micro synchronous phasor measurement unit (μPMU) data. Firstly, the initial fault location is calculated by using phasor measurement data without the shunt effect of grounding capacitance. Then, the capacitive current is estimated by the initial fault location distance, and the location result is modified by an iterative strategy. Finally, after iteration modification, a more accurate real number solution for complex equations can be obtained for complicated distribution networks with the uncertain capacitive current. The simulation results of a real underground distribution network and a modified IEEE 33 node test feeder in MATLAB/Simulink show that the proposed algorithm has higher accuracy than the traditional methods which do not have the iterative modification method of capacitive current under different fault locations, fault resistances, fault types and the neutral point grounding modes.

Method of amplitude data recovery in PMU measurements that considers synchronisation errors

The synchronised phasor measurement units (PMUs), serving as ‘GridEye’, provide data that improve the observability and controllability of the power grid due to its high accuracy and high-upload rate. However, missing or abnormal data may seriously affect its applications. This study proposes a method to recover the missing or abnormal amplitude data in PMU measurements (i.e. the active power, reactive power, positive sequence current, and voltage amplitude), based on the historical PMU data obtained from both ends of the line, which is independent of the transmission line parameters and the phase angle that may be influenced by synchronisation. First, the issues in the quality of measured PMU data are analysed, and the motivation of the proposed method is stated. Then, a method to screen out the bad data from the historical data is proposed based on the density-based spatial clustering of applications with noise. Furthermore, the model of data recovery is established, and the recovery method, which recovers the voltage amplitude, active power, reactive power, and current amplitude in sequence, using historical amplitude data to calculate related recovery coefficients is proposed. Finally, the effectiveness and practicability of the proposed method are verified by examples of simulation and measured data.

Low‐loss image‐based compression for synchrophasor measurements

Deployments of high-sampling rate synchronised phasor measurement units (PMUs) are growing rapidly throughout the world, and with the advent of microPMUs, spreading from bulk transmission through distribution systems. The growing volume of PMU data presents challenges in its communication and storage, motivating consideration of compression algorithms. This study presents a novel lossy compression algorithm that exploits particular characteristics of power system measurements to improve the compression. Concepts successfully applied in image compression are tailored to the spatio-temporal correlations induced between electrical quantities via their network interconnections. The quality of the resulting compression is judged on the balance of storage space savings versus the accuracy of data reconstruction. In representative real-world and transient simulation datasets, the technique developed can provide storage compression in the range of 40:1 when different physical quantities are compressed together. The compression ratios can be in the range of 90:1 for voltage magnitudes and 190:1 for frequency when the measurements are compressed separately. The high-compression ratios are achieved while maintaining low-loss (high-accuracy) reconstruction.

Real-time static voltage stability assessment in large-scale power systems based on spectrum estimation of phasor measurement unit data

Real-time static voltage stability assessment is crucial to a stressed modern grid. This paper, based on the moment-based spectrum estimation method, proposes a data-driven approach to gain insight into changes of voltage magnitudes via synchronous phasor measurement unit (PMU) data, such that proper actions can be taken against voltage collapse. Built upon random matrix theory, an inverse Jacobian related indicator, i.e., spectrum estimation based stability indicator (SESI), is introduced in this paper to track the motion of the system. After considering the relationship between moments and distributions, this method allows for the regime where the sample size is significantly smaller than the dimensionality. It is adaptive to the real-time static voltage stability assessment in large-scale power systems where the sample size in a sliding window is extremely smaller than the dimensionality of measurement variables, hence delivering a recent status with a low computational cost. In this way, the static voltage stability assessment of a power system with massive amounts of measurement variables can be more sensitively and efficiently implemented. Case studies with the IEEE 118-bus system, the IEEE 300-bus system, and a Polish 2383-bus system verify the effectiveness of the proposed approach.

Experimental Validation of High-Performance HIL-Based Real-Time PMU Model for WAMS

This article presents a novel real-time hardware-in-loop-based model for synchronized phasor measurement unit (PMU) which incorporates an adaptive observer to estimate the phasor quantities of the actual hardware-based PMU model. The proposed model is feasible for a wide-area monitoring system (WAMS) in modern power grids. The performance of the proposed model is compared to the conventional algorithms of the performance (P)-class and measurement (M)-class PMU models in terms of total vector error and rate of change of frequency under different scenarios (frequency ramp, unbalance with interharmonics, and out-of-bound offnominal frequency). The main advantages of the proposed model compared to existing models are as follows: (1) combining the advantages of both P and M classes in terms of achieving required standard steady-state performance (IEEE C37.118-2005) while capturing the dynamic system performance, (2) improving the redundancy due to PMU loss, (3) allowing faster implementations and advanced visualization tools, and (4) enhancing WAMS accuracy performance. Despite the advantageous introduced utilizing the proposed model, there is still a tradeoff gap between the investment cost of the installed hardware-based PMUs and system redundancy. Moreover, a laboratory-scale six-bus setup is built and tested to demonstrate the practical validity of the proposed model.

An adaptive filters based PMU algorithm for both steady-state and dynamic conditions in distribution networks

Although synchronized phasor measurement unit (PMU) technology is widely applied in transmission networks, conventional PMU algorithms suffer from new challenges (e.g. large frequency deviation, multiple interferences and dynamic behaviors, etc.) if directly applied to distribution networks. On the basis of predecessors' research, this paper presents a comprehensive PMU algorithm, using adaptive filters to simultaneously satisfy the high-precision and dynamic-response requirements of phasor estimation in distribution networks. In this algorithm, out-of-band (OOB) interferences that are difficult to be filtered out, are specifically considered in both steady-state and dynamic signal modelling processes. Based on the models, a finite impulse response (FIR) filter and a Taylor–Fourier transform (TFT) filter that both contains notches at the OOB interferences are elaborately designed and implemented in two parallel channels. With the support of a super-resolution frequency analysis method for signal components, the filters’ central frequency and notches’ position can be online adaptively adjusted. Finally, the outputs are switched between the two-channel estimations according to a designed transient recognition strategy. Test results in IEEE standard scenarios and some other realistic but severe scenarios demonstrate the effectiveness and reliability of this proposed algorithm.

Statistical Characterization of PMU Error for Robust WAMS Based Analytics

Synchronized phasor measurement unit (PMU) data contain rich information about power systems, hence the quality of estimates is of utmost concern. The existing methodologies for estimation rely on certain assumptions regarding the error in the measurement data. This paper revisits a key assumption specifically the Gaussian character of the error. A quantification of the PMU error yields its nature and statistical properties including its dependence on various sections of the PMU instrumentation channel (supposedly the major source of error in the PMU data). The non Gaussian nature of the error is asserted using various null hypotheses tests and a novel Gaussian mixture model based clustering technique is proposed to characterize and relate the errors present in PMU measurement data to the saturation in current transformer, cable length and the PMU burden. The proposed approach is tested using both real and synthetic PMU datasets. The ultimate goal of the paper is towards creating a PMU error emulator for testing and research of data analytic algorithms focused on crucial WAMS based applications.

A new approach for df/dt and active power imbalance in power system estimation using Huang’s Empirical Mode decomposition

In this paper, Huang’s Empirical Mode Decomposition approach is proposed for df/dt and active power imbalance in power system estimation. Applied approach implies availability of synchronized phasor measurement units. In addition to the successful applications in the analysis of nonstationary dynamic behavior of power system, identifications and analyses of low-frequency electromechanical oscillations and signals denoising, this approach also enables direct estimation of rate of change of a weighted average frequency (frequency of the center of inertia), as well as assessment of the overall imbalance in the power system. This demonstration is performed using computer simulation testing on the 39 Bus New England System and Western System Coordinating Council 118 bus test systems in the DigSILENT PowerFactory power system analysis software package. To validate the proposed approach the actual frequency information are used. Empirical Mode Decomposition approach is compared with Discrete Wavelet Transform, Method of Least Squares and the results from the DigSILENT PowerFactory. Also, performance of the empirical mode decomposition are compared with performances of the multivariate empirical mode decomposition and noise assisted multivariate empirical mode decomposition on both, simulated signals and field measurements. Applied approach is implemented in the MATLAB environment and results show very high accuracy.

Harmonic state estimation for distribution systems based on optimization models considering daily load profiles

This paper presents a novel static harmonic state estimation methodology for power distribution networks based on optimization models, assuming a limited number of synchronized phasor measurement units (PMUs) strategically allocated along the feeders. Optimization problems are formulated individually for each harmonic order to be analyzed in regular time intervals, with the purpose of estimating daily load profiles and harmonic components from dominant sources. Active and reactive powers are treated as inequality constraints for buses which are not monitored in real time by PMUs. The optimization problems are solved by safety barrier interior point method, in which a relaxation parameter is introduced for the constraints which reach their corresponding upper/lower bounds in order to avoid constraints violation. Simulations are carried out using a 69-bus power distribution system. Results are presented and discussed to prove the efficiency of the proposed method, including sensitivity analysis for parameters used by the algorithm.

Mitigating the Risk of Voltage Collapse Using Statistical Measures From PMU Data

With the continued deployment of synchronized phasor measurement units (PMUs), high sample rate data are rapidly increasing the real time observability of power systems. Prior research has shown that the statistics of these data can provide useful information regarding network stability, but it is not yet known how this statistical information can be actionably used to improve power system stability. To address this issue, this paper presents a method that gauges and improves the voltage stability of a system using the statistics present in PMU data streams. Leveraging an analytical solver to determine a range of “critical” bus voltage variances, the presented methods monitor raw statistical data in an observable load pocket to determine when control actions are needed to mitigate the risk of voltage collapse. A simple reactive power controller is then implemented, which acts dynamically to maintain an acceptable voltage stability margin within the system. Time domain simulations on 3-bus and 39-bus test cases demonstrate that the resulting statistical controller can outperform more conventional feedback control systems by maintaining voltage stability margins while loads simultaneously increase and fluctuate.

A Backup Protection Technique for Three-Terminal Multisection Compound Transmission Lines

This paper presents a backup non-iterative protection technique for three-terminal multisection compound untransposed double-circuit transmission lines using synchronized phasor measurement units. The proposed technique is based on a distributed line model taking into account the mutual couplings between the two circuits. Synchronized voltage and current measurements in the phase domain are utilized for fault detection, classification, and location. The proposed technique can discriminate internal transmissions lines faults from other load change conditions or external faults and identify correctly the faulty branch and fault type, as well as determine accurately the fault location. The proposed algorithm is tested under different fault resistances, different fault locations, different fault inception angles, different fault types, non-linear high impedance faults, evolving faults, and synchrophasor errors, as well as transmission line parameters errors. Extensive simulation studies carried out using MATLAB software show that the proposed protection technique yields acceptable performance for all simulated cases.

Supervising zone‐3 operation of the distance relay using synchronised phasor measurements

The study presents a new protection scheme to enhance the zone-3 operation of the distance relay. The proposed scheme develops an index based on the rate of change of active power and angle derived from synchronised phasor measurement units (PMUs). It is found that it clearly distinguishes faults from several stressed conditions those are likely to occur, and takes necessary action. The proposed scheme is developed and validated for a modified Western System Coordinating Council 9-bus, 3-machine system and New England 39-bus system with different fault scenarios on a MATLAB/Simulink platform. Further to test the robustness, the proposed method is tested on a real-time digital simulator platform using phasors received from gigabit transceiver network PMUs. Extensive performance testing for faulted as well as stressed conditions such as stable power swing, load encroachment and voltage stressed conditions indicate that the proposed scheme is highly reliable in enhancing the zone-3 operation of distance relay.