Wide-area Frequency Measurements Research Articles

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.

A Novel Event Detection and Classification Scheme Using Wide-Area Frequency Measurements

Automated event detection and classification are vital to power system monitoring. This article proposes a novel event detection and classification scheme based on wide area frequency measurement system (WAFMS). Raw frequency measurements obtained from WAFMS are used as the only input to the event detection and classification algorithm (EDCA). Wavelet-based signal pre-processing is used to denoise the data. Afterward, the rate of change of frequency (ROCOF) is estimated from the frequency measurements using the Kalman filter (KF). In the same step, phase angle difference (PAD) across different stations is estimated using WAFMS. Thus, the overall algorithm uses three features such as frequency, ROCOF, and PAD to detect and classify events in the power system. In the first step, an event is detected based on standard deviation (SD) of estimated ROCOF and PAD. In the second step, four types of events are classified using wide area frequency measurements. The suggested algorithms have been validated with real WAFMS data from the Indian Power System, recent 9th August 2019 U.K. blackout data collected from the U.K. power system, and 20th July 2017 oscillation event data obtained from ISO New England (ISO-NE) power system. As a promising tool for power system monitoring, the suggested scheme requires less input measurement for decision making and is having a low computational complexity, which is suitable for practical application.

Generator Coherency Using Zolotarev Polynomial Based Filter Bank and Principal Component Analysis

AbstractA method is proposed to identify the generators participating in an inter-area mode and the coherent generators by analyzing the discrete signals from phasor measurement units (PMU). In the present work, Zolotarev polynomial based filter bank (ZPBFB) is adopted to decompose the measured signals into monocomponents for modal frequency and damping. ZPBFB is preferred due to the narrow bandwidth of 0.1 Hz and hence closely spaced modes can be distinguished. All the generator speed signals are analysed with ZPBFB to identify the generators participating in an inter-area mode. Principal component analysis (PCA) is widely used for clustering sampled data. It is proposed in the present work to apply PCA on the decomposed signals, obtained from ZPBFB, of those generators participating in an inter-area mode for generator coherency. The efficacy of the proposed method is demonstrated on IEEE two-area test system, 16-machine, 68-bus system and on real time signals recorded by wide area frequency measurement system (WAFMS) in India on November 30, 2011. The detailed simulation results are presented. The performance of the proposed method is compared with small signal stability analysis and wavelet phase difference (WPD) approach.

Identification of Inter-Area Oscillations Using Zolotarev Polynomial Based Filter Bank With Eigen Realization Algorithm

Inter-area oscillations in power systems needs to be monitored and accurate estimation of frequency and damping of the oscillations in real time is vital as they provide considerable insight into system stability. Zolotarev polynomial based filter bank (ZPBFB) is proposed for decomposing the PMU signals into monocomponents. Modal frequency and damping are obtained from the decomposed monocomponent signals through eigen realization algorithm (ERA). The salient property of ZPBFB lies in signal decomposition with sum of decomposed signals produced by filter bank, without oversampling, is an exact replica of input signal with delay. A narrow bandwidth of 0.1 Hz is achieved in the frequency range of 0 to 1 Hz with ZPBFB. The robustness of the proposed method to noise is demonstrated using Monte Carlo simulations. The proposed ZPBFB and cosine modulated filter bank (CMFB) are implemented on two-area test system and 16-machine, 68-bus system and the performances are compared. The efficacy of the proposed method is also demonstrated on three real time signals recorded by wide area frequency measurement system (WAFMS) at 3 locations in India on November 30, 2011.

Principal Component Analysis of Wide-Area Phasor Measurements for Islanding Detection—A Geometric View

This paper presents a new technique for the detection of islanding conditions in electrical power systems. This problem is especially prevalent in systems with significant penetrations of distributed renewable generation. The proposed technique is based on the application of principal component analysis (PCA) to data sets of wide-area frequency measurements, recorded by phasor measurement units. The PCA approach was able to detect islanding accurately and quickly when compared with conventional RoCoF techniques, as well as with the frequency difference and change-of-angle difference methods recently proposed in the literature. The reliability and accuracy of the proposed PCA approach is demonstrated by using a number of test cases, which consider islanding and nonislanding events. The test cases are based on real data, recorded from several phasor measurement units located in the U.K. power system.

Wide Area Monitoring System based on the third generation Universal Mobile Telecommunication System (UMTS) for event identification

Abstract Smart grids are one of the most essential infrastructure components in the world today. Power systems have been becoming more and more complex, as a result of a considerable variety of new components being added, such as High Voltage Direct Current (HVDC) and power electronic devices, and numerous recent technologies continually being put into application, such as distributed generation. In recent years, wide-area voltage and frequency measurements are used to identify different events that occur in power systems. One of the most important events is the generator trip identification. This event could be easily identified as a sudden drop in both the system voltage level and frequency. On the other hand, high-speed, reliable and scalable data communication infrastructure is crucial in both construction and operation of wide-area voltage and frequency measurements. Universal Mobile Telecommunication System (UMTS), the 3G standard for mobile communication networks, was developed to provide high speed data transmission with reliable service performance for mobile users. Therefore, UMTS is considered a promising solution for providing a communication infrastructure for WAMS. 3G based EWAMS (Egyptian Wide Area Monitoring System) is designed and implemented in Egypt through deployment a number of Frequency Disturbance Recorders (FDRs) devices on a live 220 kV/500 kV Egyptian grid to identify the location of tripped generator in the power system. WAMS systems are used for both off-line studies and real-time applications. An important feature of these systems is their ability to provide continuous dynamic measurements that are precisely time synchronized across the power system. With real-time WAMS, the continuous measurements feed out as a data stream which can be applied to on-line applications such as monitoring and control. This paper focuses on developing an efficient and reliable wide area voltage and frequency measurements through UMTS mobile communication technology in addition to the analysis these measurements using Principal Component Analysis (PCA) in order to determine a specific signature and properties for each tripped generator in the power system network.

New Forensic ENF Reference Database for Media Recording Authentication Based on Harmony Search Technique Using GIS and Wide Area Frequency Measurements

In forensic sciences, verification of digital media recordings is an important aspect. Electrical network frequency (ENF) criterion is a promising technique for media recording authentication. The ENF reference database is recorded from a single point on the power grid based on the fact that the ENF variation is the same across all points on the grid. This fact is not valid in case of system disturbances, whereas the ENF as a reference database varies in time and space. Post-disturbance ENF recorded from a single point is mismatched with the ENF extracted from media recorded at any other point on the grid. This will lead to judicial errors in the forensic examination of recordings. A new method for establishing a robust ENF reference database using geographical information system (GIS) and wide area frequency measurements is proposed. The method is based on building the ENF reference database from a number of frequency sensors deployed over multipoint on the grid rather than single point. The minimum number of sensors required is determined according to the frequency sensitivity of the ENF extraction algorithm and the estimation accuracy of the frequency sensor. The sensors locations are decided based on partitioning the power grid to a set of geographical frequency coherent areas. A novel harmony search algorithm using GIS data and wide area frequency measurements is proposed to identify the geographical frequency coherent areas for different disturbance scenarios. Results showed that the proposed method can be used to enhance the accuracy of the ENF database matching process.

Power System Oscillation Modes Identifications: Guidelines for Applying TLS-ESPRIT Method

Abstract Fast measurements of power system quantities available through wide-area measurement systems enables direct observations for power system electromechanical oscillations. But the raw observations data need to be processed to obtain the quantitative measures required to make any inference regarding the power system state. A detailed discussion is presented for the theory behind the general problem of oscillatory mode indentification. This paper presents some results on oscillation mode identification applied to a wide-area frequency measurements system. Guidelines for selection of parametes for obtaining most reliable results from the applied method are provided. Finally, some results on real measurements are presented with our inference on them.

Wide-area Frequency-based Tripped Generator Locating Method for Interconnected Power Systems

Since the Internet-based real-time Global Positioning System(GPS) synchronized wide-area power system frequency monitoring network (FNET) was proposed in 2001, it has been monitoring the power system frequency in interconnected United States power systems and numerous interesting behaviors have been observed, including frequency excursion propagation. We address the consistency of a frequency excursion detection order of frequency disturbance recorders in FNET in relation to the same generation trip, as well as the ability to recreate by power systems dynamic simulation. We also propose a new method, as an application of FNET measurement, to locate a tripped generator using power systems dynamic simulation and wide-area frequency measurement. The simulation database of all the possible trips of generators in the interconnected power systems is created using the off-line power systems dynamic simulation. When FNET detects a sudden drop in the monitoring frequency, which is most likely due to a generation trip in power systems, the proposed algorithm locates a tripped generator by finding the best matching case of the measured frequency excursion in the simulation database in terms of the frequency drop detection order and the time of monitoring points.