Synchrophasor Measurements Research Articles

Operating state assessment in distribution network based on empirical spectral analysis

The operating state assessment is an important task in distribution network, result of which can offer support on the safety analysis and control decision. With the deployments of advanced supervisory control and data acquisition (SCADA) systems and micro-phasor measurement units (µPMU), massive amount of measurement data is collected, which makes it possible for the real-time operating state assessment of the entire system. In this paper, a data-driven approach is proposed for real-time operating state assessment in distribution networks. Firstly, spatio-temporal data set is formulated by arranging highdimensional synchrophasor measurements in chronological order. Based on the empirical spectral analysis of signal plus noise matrix using the Ring Law in the RMT, the mean spectral radius (MSR) is introduced to indicate the system state in macroscopic. The developed approach is sensitive to the variation of the system state and robust against random fluctuations and measurement errors. Cases on the synthetic data generated from IEEE standard test system validate the effectiveness of the approach.

Artificial Intelligence based Optimal Placement of Phasor Measurement Unit for Smart Grid

A Phasor Measurement Unit (PMU) device ensures the stability, reliability, and proper visibility of critical areas of the power grid by providing a synchro phasor measurement of both voltage and current in real-time. Since it is not practical to place them at each branch of the system, the main concern lies in achieving entire network observability either by direct or indirect measurement through an optimal set of PMUs placed at the optimal location. This gives rise to the Optimal PMU Placement Problem (OPP). In this paper, OPP is solved by an optimization technique i.e., a Genetic Algorithm. The constraints that can greatly affect obtaining optimal solutions are reviewed and the effect of including Zero Injection Bus (ZIB) on the proposed method in solving OPP is studied. The algorithm is applied to IEEE-14 and IEEE-30 bus test systems for validation purposes. Since optimal sets of solutions are obtained from the proposed method, the solutions are ranked by the system observability redundancy index to find the best one. Further, a comparative analysis of the result is done with the depth first search algorithm and other widely used algorithms.

The power quality detection and synchrophasor measurement based on compressive sensing

In order to improve the effect of power quality detection and synchrophasor measurement, this paper studies power quality detection and synchrophasor measurement with the support of compressive sensing technology. Based on the DFT synchrophasor measurement, this paper uses the RDFT recursive formula to simplify the DFT calculation amount, and uses the least squares estimation method to fit the phase angle sequence to calculate the system frequency. According to the obtained frequency estimation value, re-sampling is carried out to correct the original sampling point, and the frequency secondary calculation is iteratively performed, the detection accuracy of high frequency and phase angle, and the linear measurement of the signal is realized by using the Gaussian random measurement matrix, and the compressed sensing signal is obtained. The experimental data statistics show that the model proposed in this paper for power quality detection and synchrophasor measurement based on compressive sensing has a good effect.

Online Realization of an Ambient Signal-Based Load Modeling Algorithm and Its Application in Field Measurement Data

With the development of synchrophasor measurement techniques, ambient signal-based load modeling is recently proposed to track the time-varying characteristics of power loads. On this basis, the hardware realization of this approach, which includes the local load modeling devices and the data center, is proposed and tested with the field measurement data from China Southern Power Grid. In this way, practical load model parameters can be identified from field measurement data both online and offline by the hardware system. To begin with, the hardware system, which is the first realization of an ambient signal-based load modeling algorithm, offers sufficient field measurements for load modeling. Then, the identification results of the field measurements verify the effectiveness of the ambient signal-based load modeling algorithm. Besides, the identified load model parameters for different substations during different times demonstrate the time-varying and the distributed characteristics of power loads.

Parameter Identification With Synchrophasor Trajectory Fitting Technique for Sub-/Super-Synchronous Oscillations

To enhance the real-time monitoring of sub-/super-synchronous oscillation dynamics by utilizing the advantages of wide-area time-synchronization and dynamic measurement of synchrophasor measurement data, the idea of a parameter identification algorithm with synchrophasor trajectory fitting (PTF) is proposed in this letter to identify the parameters of each component of the instantaneous signal during sub-/super-synchronous oscillations. Simulated PMU data are used to demonstrate the proposed idea and verify the performance of PTF compared with the interpolated DFT algorithm. Discussions are also provided for further improvements.

Real-time monitoring and control of energy security indicators based on synchrophasor measurements

Based on the analysis of the development of the Azerbaijan EPS, it is distinguished by its power and network structure, expanded intersystem communications, and is substantiated by a monitoring and control plan based on synchrophasor measurements of the state of the reliability mode - an indicator of energy security. The effectiveness of a large-scale assessment of the PMU installation in the Azerbaijan EPS. Keywords: energy security; regime reliability; power system; SCADA/EMS – WAMS, PMU.

Synchrophasor-Based Online Transient Stability Assessment Using Regression Models

An online post-fault transient stability assessment method is proposed in this study using synchrophasor or PMU measurements. Initially, a post-fault multimachine system is converted into a suitable one machine infinite bus (OMIB) system using the single machine equivalent (SIME) method. Thus, the - trajectory obtained through the OMIB system enabled a normalized transient stability index to be calculated offline. By using synchrophasor measurements before and during the fault as inputs, the regression model can be trained offline to predict the normalized stability margins. Following a fault, the synchrophasor measurements are used as input to this trained model for online stability margin prediction. If the predicted margin is negative, then the post-fault power system is indicated to be unstable. Alternatively, positive values for the predicted margin identify the system as stable. The proposed assessment method is verified using the New England (NE) 39 bus test system. The results obtained are then compared with offline simulations.

Transmission network angle stability protectionbased on synchrophasor data in control centre

Angle stability appears in many forms in transmission network. There are small active power oscillations which do not endanger the normal operations whereas medium and large oscillations have implications on normal operations. These latter kinds of oscillations in some cases develop in out of step condition, which is dangerous disturbance with serious impact on transmission network and generating units. Transmission network operator’s challenges and obligations are to treat in the right manner angle stability issues in their network. Controlling and protecting network needs to be done in efficient way in order to disconnect disturbance quickly and prevent abnormal network operation without exporting disturbance in surrounding networks. Synchrophasor measurements in control centre offer a platform, which responds in a new way on angle stability in transmission network. Those measurements which are collected in phasor data concentrators, which is a part of Wide Area Monitoring will be used for creating out of step protection. This is the first step to extended system to Wide Area Monitoring Protecting And Control (WAMPAC). Paper gives progress of such project in Croatian Transmission Network Operator (HOPS). Firstly, there will be stated motives for development of new out of step protection based on synchrophasor measurements. Some feasibility aspect elaborated with emphasis on communications latency. Furthermore, designed Matlab model for transmission network and protection with small portions of simulations results and analyses presented in paper reveal potential of proposed solutions. This new protection is based on using voltage angles values from phasor data stream in phasor data concentrator.

Compressed-DMD for Electromechanical Mode Estimation from High-Dimensional Ambient Data

Accurate and rapid estimation of electromechanical mode plays an important role in sensing the security situation of power systems. In this paper, the Compressed Dynamic Mode Decompensation (Compressed-DMD) based estimation approach was proposed to extract the electromechanical mode from high-dimensional ambient data measured by the synchrophasor measurement unit. To improve the efficiency of DMD in processing high-dimensional ambient data under the premise of ensuring calculation accuracy, the Compressed-DMD was introduced to generate the approximation of the high-dimensional left and right singular vectors by employing the aggressive random test matrices and truncated eigendecomposition. Simulation examples of IEEE 16-generator 5-area system and real measurements verify the feasibility and effectiveness of the proposed method.

A Comprehensive Framework for the Assessment of Synchrophasor Communication Networks from the Perspective of Situational Awareness in a Smart Grid Cyber Physical System

The conventional power grid is modernizing into a cyber-physical smart grid. In this system, there are several applications, an important being the synchrophasor measurement system. Sensors called the phasor measurement units, measure the synchrophasors and communicate them to the phasor data concentrator using the synchrophasor communication networks. Situational awareness helps in the quick perception of the environment and in taking commensurate actions by the power system operator. Thus, the synchrophasor communication networks play an important role and must be assessed from the perspective of the operator’s situational awareness. In this context, a comprehensive situational awareness analysis metric is proposed. The proposed metric is based on hardware reliability, data reliability, and network delay. As a case study, a practical power grid of India (West Bengal Power Grid) is considered for assessing its situational awareness. The synchrophasor communication networks of the West Bengal power grid are simulated in the QualNet network simulator to validate the proposed situational awareness framework.

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.

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.

Enhanced Support Recovery for PMU Measurements Based on Taylor–Fourier Compressive Sensing Approach

Modern distribution networks are characterized by higher distortion and faster variability of voltages and currents. Accurate synchrophasor, frequency and ROCOF measurements thus ask for new techniques trying to reduce latency while limiting the impact of spurious components. In this respect, Taylor-Fourier Multifrequency approach is a good candidate for Phasor Measurement Units intended for distribution system applications. In the present paper, we propose an enhanced version of this approach based on the joint application of window functions and iterative support refinement by means of the phasor first order derivative. The performance of the algorithm is thoroughly characterized through extensive numerical simulation of non-standard test conditions that reproduce the challenges of real-world scenarios, with fundamental dynamics superimposed to interfering tones. The reported results confirm the enhanced spectral support recovery, resulting in a remarkable improvement of estimation accuracy.

Design of Compressive Sensing Adaptive Taylor-Fourier Comb Filters for Harmonic Synchrophasor Estimation

In modern power systems, phasor measurements are expected to deal with challenging conditions, e.g. fast dynamics and high distortion levels. Taylor-Fourier Multifrequency models represent a promising solution, but their performance is strongly related to the accurate extraction of the signal spectral support. In this context, this paper proposes an enhanced method for support recovery that exploits the inherent block-sparsity properties of electrical signals. The proposed method is fully characterized in diverse and distorted test conditions, inspired by reference standards and real-world scenarios. The comparison against another Compressive Sensing based approach confirms the significant improvement in terms of both recovered support exactness and synchrophasor measurement accuracy.

Phasor Measurement Unit With Digital Inputs: Synchronization and Interoperability Issues

In recent years, the electrical substations are experiencing a rapid transition towards a fully digital measurement infrastructure, in terms of data acquisition, storage and processing. The IEC Std 61850-9-2 defines the data format, also known as Sampled Value (SV), to be employed by instrument transformers, merging units, and controller devices. In this scenario, it is reasonable to expect that also Phasor Measurement Units (PMUs) will be directly connected with digital instrument transformers and will be required to process directly the SV data stream. In this paper, we present the design and development of a stand-alone PMU based on digital inputs. The prototype has been characterized in terms of estimation accuracy and enriched with a novel functionality that allows for monitoring the time quality of the SV data stream. In this way, the device truly becomes an Intelligent Electronic Device (IED) that guarantees higher interoperability as well as a more robust management of sporadic synchronization issues. The proposed results confirm the potential of SV-based PMUs, and highlight the possibility of further enhancement for synchrophasor measurements based on digital inputs only.

State and Topology Estimation for Unobservable Distribution Systems using Deep Neural Networks.

Time-synchronized state estimation for reconfigurable distribution networks is challenging because of limited real-time observability. This paper addresses this challenge by formulating a deep learning (DL)-based approach for topology identification (TI) and unbalanced three-phase distribution system state estimation (DSSE). Two deep neural networks (DNNs) are trained for time-synchronized DNN-based TI and DSSE, respectively, for systems that are incompletely observed by synchrophasor measurement devices (SMDs) in real-time. A data-driven approach for judicious SMD placement to facilitate reliable TI and DSSE is also provided. Robustness of the proposed methodology is demonstrated by considering non-Gaussian noise in the SMD measurements. A comparison of the DNN-based DSSE with more conventional approaches indicates that the DL-based approach gives better accuracy with smaller number of SMDs.

Attack detection for spoofed synchrophasor measurements using segmentation network

Attack detection for spoofed synchrophasor measurements using segmentation network

DRTP: A Disruption Resilient Hop-by-Hop Transport Protocol for Synchrophasors Measurement in Electric Transmission Grids

In a modern electric power transmission grid, the phasor measurement unit requires a reliable transport of its sampled statistics with a low end-to-end failure rate (EEFR) to ensure the accuracy of the grid state estimation. However, EEFR can be deteriorated by packet losses due to multiple link disruptions in the primary forwarding path (PP). To address that, we investigate a novel disruption resilient transport protocol (DRTP) enabling hop-by-hop retransmission utilizing the redundant subpaths (RSPs) available for the PP to increase reliability. It addresses the new distributed collaboration issue under multiple link failures to avoid cache mismatching. These have not been considered by the existing approaches. The DRTP was evaluated in the ndnSIM simulator through both the typical and general routes that are constructed from real transmission grids. The numerical results demonstrate that it has a significant advantage in reducing the EEFR with a low end-to-end delivery time under serious link disruptions.

Development of cost-effective phasor measurement unit for wide area monitoring system applications

<span>Sustained growth in the demand with unprecedented investments in the transmission infrastructure resulted in narrow operational margins for power system operators across the globe. As a result, power networks are operating near to stability limits. This has demanded the electrical utilities to explore new avenues for control and protection of wide area systems. Present supervisory control and data acquisition/energy management systems (SCADA/EMS) can only facilitate steady state model of the network, whereas synchrophasor measurements with GPS time stamp from wide area can provide dynamic view of power grid that enables supervision, and protection of power network and allow the operator to take necessary control/remedial measures in the new regime of grid operations. Construction of phasor measurement unit (PMU) that provide synchrophasors for the assessment of system state is widely accepted as an essential component for the successful execution of wide area monitoring system (WAMS) applications. Commercial PMUs comes with many constraints such as cost, proprietary hardware designs and software. All these constraints have limited the deployment of PMUs at high voltage transmission systems alone. This paper addresses the issues by developing a cost-effective PMU with open-source hardware, which can be easily modified as per the requirements of the applications. The proposed device is tested with IEEE standards.</span>

Online Detection of Low-Quality Synchrophasor Data Considering Frequency Similarity

This letter proposes a new approach for online detection of low-quality synchrophasor data under both normal and event conditions. The proposed approach utilizes the features of synchrophasor data in time and frequency domains to distinguish multiple regional PMU signals and detect low-quality synchrophasor data. It is more effective to detect low-quality data with apparently indistinguishable profiles. Case studies from recorded synchrophasor measurements verify the effectiveness of the proposed approach for detecting low-quality synchrophasor data in frequency, voltage magnitude and voltage angle.