Phasor Angles Research Articles

Emulating Synchrophasor Frequency Measurements With Transient Stability Simulation

In transient stability simulators such as PSS/E, the bus frequency is estimated using a window of (positive-sequence) phasor angle measurements. A digital filter is often used to account for the filtering effect in actual measurement devices and to eliminate sudden changes during frequency computations. Although transient stability simulators label the filtered angle derivative as the “frequency,” the frequency provided by such programs does not match actual measurements reported by phasor measurement units (PMUs), which makes it difficult to gauge the validity of studies (e.g., wide-area event detection and control applications) that are based on such simulations. In this paper, we implement a frequency computation method directly using positive phasor angles provided by simulators. The proposed method is tested on two systems extensively and validated against the measurements of an actual PMU. The improved frequency measurements closely match PMU responses. Cross-validation results also suggest the method may be used for other systems without conducting full time-domain simulations.

Machine learning methods for power line outage identification

As Phasor Measurement Units (PMUs) become widely deployed, power systems can take advantage of the large amount of data provided by PMUs and leverage the advances in big data analytics to improve real-time monitoring and diagnosis. In this paper, we develop practical analytics that are not tightly coupled with the power flow analysis and state estimation, as these tasks require detailed and accurate information about the power system. We focus on power line outage identification, and use a machine learning framework to locate line outages. The same framework is used for the prediction of both single line and multiple line outages. We investigate a range of machine learning algorithms and feature extraction methods. The algorithms are designed to capture the essential dynamic characteristics of the power system when the topology change occurs abruptly. The proposed methods use only voltage phasor angles obtained by continuously monitoring the buses. We tested the proposed methods on their prediction performance under different levels of noise and missingness. It is shown that the proposed methods have better tolerance for noisy data and incomplete data when compared to the previous work that involves solving power flow equations or state estimation equations.

Power System Analysis Using LabVIEW

The focus of this work is on investigation of LabVIEW electric power tool in particular and LabVIEW software in general for the analysis and design of electric power systems. Here we are targeting the solution of different electrical engineering problems which we very often face in teaching the course of power system analysis. At the time being, at Zarqa University, we are preparing a self study report for submission to ABET for accreditation of electrical engineering program. ABET considers that the application of different software tools during the learning process is essential and must be covered. Thus, power system analysis course has been selected as one of the courses that are decided to reach this outcome. As a result of that, a literature survey was conducted and several relevant topics were selected to be investigated. This included the following: simulation of on-line measurement of RMS and instantaneous values of electric power, calculation of symmetrical components using matrix analysis, on-line estimation of symmetrical components, use of phasor analysis to find phasor magnitude and phase angles, conversion of star to delta and delta to star configurations, and simulation of rotating phasors. All designed virtual instruments were analyzed, tested, and chosen solved examples gave very accurate results.

A Position-Independent Approach to Accurate Measurement of Broadband Electromagnetic Constitutive Parameters of Magnetodielectric Materials

Magnetodielectric materials have been recently attracting great attention owing to their significant advantages for miniaturization and wide bandwidth of antennas. A precise measurement of broadband permeability and permittivity is crucial to develop and evaluate advanced magnetodielectric materials. The Nicolson-Ross-Weir (NRW) method is widely used to extract electromagnetic constitutive parameters from measured scattering parameters. One of the drawbacks of this method is requiring direct measurement of the actual sample position in the measurement fixture, which leads to uncertainties in the measured permeability and permittivity. In this article, we improve the standard NRW method by removing the need for prior knowledge of sample position. For any isotropic material, the sample position in the measurement fixture can be precisely determined by matching the phasor angles of the reflection coefficients at the sample surfaces. Due to eliminating the error from the direct measurement of sample position, the improved NRW method effectively reduces the uncertainties in the calculated permeability and permittivity. Based on the results from two kinds of magnetodielectric materials measured in two sets of test fixtures of different geometries, this straightforward, explicit, and noniterative method is theoretically and experimentally proven to have a high and position-independent accuracy over a wide frequency range.

Line outage identification using comparison of bus power mismatch considering PMU outage

In this study, a novel algorithm for line outage identification is developed utilising the PMU provided phasor angles. For various outage cases, the simulated bus power mismatches (SBPMs) using bus susceptance matrix of the full network are to be stored. As soon as actual outage occurs, the bus power mismatches are computed using PMU provided pre outage and post outage phasor angles. Additionally, optimal PMU placement issue is also addressed to ensure the network observability in case of PMU outage. Moreover, random Gaussian noise with zero mean and standard deviation (SD) from 1% to 5% is incorporated in the developed model. Simulation was carried out on standard IEEE 5 bus, 14 bus, 30 bus, 57 bus, and 118 bus systems to check the viability and applicability of the proposed methodology. The obtained test results are found to be competitive with the existing methods.

Line outage identification using comparison of bus power mismatch considering PMU outage

In this study, a novel algorithm for line outage identification is developed utilising the PMU provided phasor angles. For various outage cases, the simulated bus power mismatches (SBPMs) using bus susceptance matrix of the full network are to be stored. As soon as actual outage occurs, the bus power mismatches are computed using PMU provided pre outage and post outage phasor angles. Additionally, optimal PMU placement issue is also addressed to ensure the network observability in case of PMU outage. Moreover, random Gaussian noise with zero mean and standard deviation (SD) from 1% to 5% is incorporated in the developed model. Simulation was carried out on standard IEEE 5 bus, 14 bus, 30 bus, 57 bus, and 118 bus systems to check the viability and applicability of the proposed methodology. The obtained test results are found to be competitive with the existing methods.

Preprocessing and Golomb-Rice Encoding for Lossless Compression of Phasor Angle Data

Phasor measurement units (PMUs) are being increasingly deployed to improve monitoring and control of the power grid due to their improved data synchronization and reporting rates in comparison with legacy metering devices. However, one drawback of their higher data rates is the associated increase in bandwidth (for transmission) and storage requirements (for data archives). Fortunately, typical grid behavior can lead to significant compression opportunities for phasor angle measurements. For example, operation of the grid at near-nominal frequency results in small changes in phase angles between frames, and the similarity in frequencies throughout the system results in a high level of correlation between phasor angles of different PMUs. This paper presents several methods for preprocessing of phasor angles that take advantage of these system characteristics, including a new method—frequency compensated difference encoding—that is able to significantly reduce angle data entropy. After the preprocessor stage, the signal is input to an entropy encoder, based on Golomb–Rice codes, that is ideal for high-throughput signal compression. The ability of the proposed methods to compress phase angles is demonstrated using a large corpus of data—over 1 billion phasor angles from 25 data sets—captured during typical and atypical grid conditions.

Reduction of Noise in Measurements of Phasor Angles by Using Two Digital Filters

An electric power system is monitored and controlled on the basis of its phasor information, such as amplitude, phase angle, and frequency. This phasor can be measured through discrete Fourier transform (DFT) coefficients of its positive nominal frequency. Then, the frequency estimate can be calculated from time variation of the measured phasor angle. The accuracy of the phasor-angle measurement and the frequency estimation are severely affected by noise in the power system signal and the leakage of the negative fundamental frequency in DFT. This paper proposes a DFT-based phasor-angle measurement algorithm to cope with both the noise effect and the leakage effect. In addition, a frequency estimation algorithm is developed to use the same technique in the phasor-angle measurement algorithm. These algorithms introduce two digital filters for the reduction of the noise effect. The effectiveness of the proposed algorithm in the noise effect reduction is verified through simulations.

A Dependency Graph Approach for Fault Detection and Localization Towards Secure Smart Grid

Fault diagnosis in power grids is known to be challenging, due to the massive scale and spatial coupling therein. In this study, we explore multiscale network inference for fault detection and localization. Specifically, we model the phasor angles across the buses as a Markov random field (MRF), where the conditional correlation coefficients of the MRF are quantified in terms of the physical parameters of power systems. Based on the MRF model, we then study decentralized network inference for fault diagnosis, through change detection and localization in the conditional correlation matrix of the MRF. Particularly, based on the hierarchical topology of practical power systems, we devise a multiscale network inference algorithm that carries out fault detection and localization in a decentralized manner. Simulation results are used to demonstrate the effectiveness of the proposed approach.

EEG synchrony during a perceptual-cognitive task: Widespread phase synchrony at all frequencies

(1) To examine the validity of comparing the phase of broad-band signals. (2) To measure phase synchrony over the whole head, at a variety of frequencies. The concept of broad band phase is investigated (a) by visual comparison of the time series of two channels of filtered data with the time series of the spatial analytic phase difference (SAPD) between the two channels and (b) using artificial sinusoids. Phase synchrony is then measured in 64-channel EEG recorded while human subjects performed a perceptual-cognitive task, by calculation of analytic phase differences between each channel and a frontal synchrony reference channel. The number of channels in synchrony with the reference channel at a series of frequency passbands is compared for data acquired using a common recording reference, the same data re-referenced to an average reference and artificial noise. Analytic phase is shown to represent the resultant of the phasor angles of all the narrow band signals incorporated in a composite waveform. Episodic global phase synchrony is identified in background EEG, in all passbands from theta to epsilon. Many of the episodes of widespread synchrony occur in both common-referenced and average-referenced data, but some common-reference episodes are not seen in average-referenced data. In both forms of data, synchrony is about equally widespread in all subjects at lower passbands, but more widespread in some subjects than others at higher passbands. (1) It is valid to measure the analytic phase of broad band EEG signals. (2) Non-local phase synchrony is intermittently present in all frequency bands from theta to epsilon, not only during and after external stimuli, but also in background EEG. (3) In some subjects synchrony is more widespread in gamma and epsilon bands than in beta, alpha or delta bands, but in others the reverse is true. (4) Some of the episodes of synchrony seen in common referenced data may be artifacts of a sudden decrease in power at the recording electrodes in comparison with the common reference electrode. However, most of the episodes of synchrony in common-referenced data cannot be explained in this fashion. (5) Episodes of widespread synchrony are not established instantaneously. During the establishment of most episodes of '40 Hz' synchrony, the number of channels in synchrony peaks after about 100 ms. If long-range phase synchrony really is a hallmark of consciousness, it should be present most of the time the subject is conscious. Our results confirm this prediction, and suggest that consciousness may involve not only gamma frequencies, but the whole range from theta to epsilon. The mechanism of synchrony establishment at the scalp as shown by the present method is relatively slow and thus more likely to involve chemical synapses than gap junctions, electric fields or quantum non-locality.

Midterm stability evaluation of wide‐area power system using synchronized phasor measurements

AbstractIn recent years, the PMU (Phasor Measurement Unit) has received a great deal of attention as a synchronized measurement system of power systems. Synchronized phasor angles obtained by the PMU provide valuable information for evaluating the stability of a bulk power system. The aspect of instability phenomena during midterm tends to be more complicated, and the stability analysis using the synchronized phasor measurements is effective in order to keep a complicated power system stable. This paper proposes a midterm stability evaluation method for the wide‐area power system using synchronized phasor measurements. By clustering the power system to some coherent groups, step‐out is predicted on the basis of an aggregated two‐machine equivalent power system. The midterm stability of a longitudinal power system model of Japan's 60‐Hz systems constructed by a hybrid‐type power system simulator is practically evaluated using the proposed method. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 147(1): 25–32, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10274