David Macii

Synchrophasor Estimators Accuracy: A Comparative Analysis

The real-time high-accuracy measurement of waveform phasors is one of the many open challenges that need to be addressed in future smart grids. In this paper, the accuracy of four recently proposed synchrophasor estimators is analyzed and compared with the well-known one-cycle discrete Fourier transform estimator under the effect of static frequency offsets, amplitude modulation, phase modulation, harmonic distortion, and wideband noise. Two of the considered techniques track the phasor variations through finite-difference equations that estimate the first- and second-order derivatives of the phasor itself. The other two methods are instead based on a least squares estimation of the coefficients of the phasor Taylors series expansion. The analysis reported in this paper covers the main scenarios described in the Standard IEEE C37.118.1-2011. In particular, the influence of different signal parameters on the total vector error (TVE) values is quantified and used to determine the maximum TVE increments associated with distinct parameters and the corresponding upper bounds.

Accuracy Analysis and Enhancement of DFT-Based Synchrophasor Estimators in Off-Nominal Conditions

Synchrophasor estimation accuracy is a well-known critical issue in systems for smart grid monitoring and control. This paper deals with an in-depth analysis of the effect of both steady-state and dynamic disturbances on single-cycle and multicycle windowed discrete Fourier transform (DFT)-based synchrophasor estimators. Unlike other qualitative or simulation-based results found in the literature, this work provides two accurate and easy-to-use analytical expressions that can be used to determine the worst case range of variation of the total vector error (TVE) due to off-nominal frequency deviations. In such conditions, estimation accuracy is limited by two factors, i.e., the infiltration caused by the input signal image frequency and the scalloping loss associated with the spectrum main lobe of the chosen window. Starting from the aforementioned general analysis, a new two-term window minimizing the detrimental effects of image frequency tone is proposed. The accuracy of the related DFT-based synchrophasor estimator is evaluated under both static and dynamic conditions, which is the most interesting scenario for future smart grids. Moreover, the effect of waveform frequency measurement uncertainty on scalloping loss compensation is quantified. Several simulation results (including the effects of noise, harmonic distortion, and amplitude and phase modulation) confirm that the proposed window can significantly improve the accuracy achievable with a simple single-cycle DFT estimator. Indeed, TVE values much smaller than 1% can be achieved even in the worst case conditions reported in the standard IEEE C37.118.1-2011, when the frequency waveform deviations are within ±4% of the nominal value. In addition, the proposed solution could be useful to improve the performance of more complex dynamic phasor estimators, e.g., those in which the first- and second-order terms of the phasor Taylor series expansion result from the differences of consecutive DFT-based phasor estimates.

Flexible Indoor Localization and Tracking Based on a Wearable Platform and Sensor Data Fusion

Indoor localization and tracking of moving human targets is a task of recognized importance and difficulty. In this paper, we describe a position measurement technique based on the fusion of various sensor data collected using a wearable embedded platform. Since the accumulated measurement uncertainty affecting inertial data (especially due to the on-board accelerometer) usually makes the measured position values drift away quickly, a heuristic approach is used to keep velocity estimation uncertainty in the order of a few percent. As a result, unlike other solutions proposed in the literature, localization accuracy is good when the wearable platform is worn at the waist. Unbounded uncertainty growth is prevented by injecting the position values collected at a very low rate from the nodes of an external fixed infrastructure (e.g., based on cameras) into an extended Kalman filter. If the adjustment rate is in the order of several seconds and if such corrections are performed only when the user is detected to be in movement, the infrastructure remains idle most of time with evident benefits in terms of scalability. In fact, multiple platforms could work simultaneously in the same environment without saturating the communication channels.

A Frequency-Domain Algorithm for Dynamic Synchrophasor and Frequency Estimation

Next-generation phasor measurement units (PMUs) are expected to play a key role for monitoring the behavior of future smart grids. While most of the PMUs used nowadays in transmission networks rely on static phasor models, more sophisticated representations and stricter accuracy requirements are needed to track amplitude, phase, and frequency changes of power waveforms in strongly dynamic scenarios as those expected in future distribution systems. In this paper, a discrete Fourier transform (DFT)-based algorithm based on a dynamic phasor model (referred to as interpolated dynamic DFT-based synchrophasor estimator) is used to estimate not only amplitude and phase of the collected waveforms, but also their frequency and rate of change of frequency. The performances of the proposed method are evaluated through multiple simulations in different steady-state and transient conditions described in the Standard IEEE C37.118.1-2011.

Fast Synchrophasor Estimation by Means of Frequency-Domain and Time-Domain Algorithms

This paper presents a performance comparison of two classes of synchrophasor estimators recently proposed in the literature, i.e., the frequency-domain algorithms known as interpolated discrete Fourier transform (IpDFT), and the time-domain algorithms based on the weighted least squares (WLSs) approach. The analysis is focused on fast phasor estimation only and it is performed under steady-state, dynamic, and transient conditions, when the length of the observation interval is equal to one or two nominal cycles of the acquired electric waveform. The considered testing conditions include not only the worst-case scenarios specified in the IEEE Standard C37.118.1-2011, but they also combine the effect of static and dynamic disturbances. As accuracy performance parameters, the total vector error as well as the amplitude and phase estimation errors are considered and evaluated. Estimator responsiveness is analyzed instead in terms of response times, when amplitude or phase steps occur. The preferable one- and two-cycles IpDFT and WLS algorithms are first determined by choosing the windows and the number of Taylors series terms (in the WLS case only) assuring the best accuracy. It is shown that, when the time-domain approach is considered and one-cycle or two-cycle intervals are observed, the best accuracy is achieved by the WLS algorithm based on the rectangular window or the two-term one-cycle maximum image tone interference rejection (MIR) window, respectively. Conversely, when the frequency-domain approach is adopted, the best accuracy is achieved by the IpDFT-based on the MIR window related to the observed interval length. The estimates produced by the selected WLS and IpDFT algorithms are then compared against the boundaries specified in the Standard IEEE C37.118.1-2011 for P-and M-class compliance. During the discussion, advantages and disadvantages of both time-domain and frequency-domain approaches are highlighted.

A Data Fusion Technique for Wireless Ranging Performance Improvement

The increasing diffusion of mobile and portable devices provided with wireless connectivity makes the problem of distance measurement based on radio-frequency technologies increasingly important for the development of next-generation nomadic applications. In this paper, the performance limitations of two classic wireless ranging techniques based on received signal strength (RSS) and two-way time-of-flight (ToF) measurements, respectively, are analyzed and compared in detail. On the basis of this study, a data fusion algorithm is proposed to combine both techniques in order to improve ranging accuracy. The algorithm has been implemented and tested on the field using a dedicated embedded prototype made with commercial off-the-shelf components. Several experimental results prove that the combination of both techniques can significantly reduce measurement uncertainty. The results obtained with the developed prototype are not accurate enough for fine-grained position tracking in Ambient Assisted Living applications. However, the platform can be successfully used for reliable indoor zoning, e.g., for omnidirectional and adjustable hazard proximity detection. Most importantly, the proposed solution is absolutely general, and it is quite simple and light from the computational point of view. Accuracy could be further improved by using a more isotropic antenna and by integrating the ToF measurement technique at the lowest possible level on the same radio chip used for communication. Usually, this feature is not available in typical low-cost short-range wireless modules, e.g., for wireless sensor networks. Thus, the results of this research suggest that combining RSS with ToF measurements could be a viable solution for chip manufacturers interested in adding ranging capabilities to their radio modules.

Performance of Synchrophasor Estimators in Transient Conditions: A Comparative Analysis

Transient amplitude or phase changes in current or voltage waveforms may seriously affect synchrophasor estimators accuracy and responsiveness. The IEEE Standard C37.118.1-2011 specifies test conditions as well as accuracy and response delay limits for different types of disturbances. In this paper, the performances of three state-of-the-art techniques based on phasor Taylors series expansion specifically conceived to track phasors in dynamic conditions are analyzed and compared with the one-cycle discrete Fourier transform estimator under the effect of amplitude step changes, phase step changes, and linear frequency variations. Several simulation results show that the total vector error (TVE) tends to increase linearly with the step size. However, the peak TVE increments for a given step size are quite similar for all the considered techniques and are dominated by amplitude or phase errors, depending on whether the step affects the waveform amplitude or its phase, respectively. In this paper, the response times of the considered estimators for two different TVE thresholds are also analyzed and compared as a function of the step size, to assess their compliance to the requirements of the standard. Further simulation results show that in the case of linear frequency variations, responsiveness is not an issue and the TVE values of all estimators lie within the same worst case boundaries as those related to the case of static off-nominal frequency offsets.

Remote Didactic Laboratory “G. Savastano,” The Italian Experience for E-Learning at the Technical Universities in the Field of Electrical and Electronic Measurements: Overview on Didactic Experiments

The Remote Didactic Laboratory Laboratorio Didattico Remoto - LA.DI.RE. ldquoG. Savastanordquo is the e-learning measurement laboratory supported by the Italian Ministry of Education and University. It involves about 20 Italian universities and provides students of electric and electronic measurement courses with access to remote measurement laboratories delivering different didactic activities related to measurement experiments. In order to demonstrate the versatility for didactic use, the overview of some experiments is given. The didactic experiments summarized in this paper concern measurement characterization of instruments and communication systems, measurement devices for remote laboratories, basic electrical measurements, magnetic measurements, electromagnetic-interference measurements, and signal processing for measurement applications.

An open distributed measurement system based on an abstract client-server architecture

This paper describes in detail a Java-based, client-server architecture specifically designed to allow a flexible management of remote instruments. The main attributes of the proposed solution are portability and extensibility. The former feature is assured by the employment of the TCP/IP protocol suite and by the Java language properties. The latter is due to the high level of abstraction of the system implementation. This approach addresses a wide range of possible applications with high code reusability. In fact, the proposed architecture permits to drive many kinds of different devices and can be easily upgraded simply by adding a limited amount of code on the server computer whenever a new instrument is connected to the system.

Bayesian linear state estimation using smart meters and PMUs measurements in distribution grids

In this work we address the problem of static state estimation (SE) in distribution grids by leveraging historical meter data (pseudo-measurements) with real-time measurements from synchrophasors (PMU data). We present a Bayesian linear estimator based on a linear approximation of the power flow equations for distribution networks, which is computationally more efficient than standard nonlinear weighted least squares (WLS) estimators. We show via numerical simulations that the proposed strategy performs similarly to the standard WLS estimator on a small distribution network. A key advantage of the proposed approach is that it provides explicit off-line computation of the estimation error confidence intervals, which we use to explore the tradeoffs between number of PMUs, PMU placement and measurement uncertainty. Since the estimation error in distribution systems tends to be dominated by uncertainty in loads and scarcity of instrumented nodes, the linearized method along with the use of high-precision PMUs may be a suitable way to facilitate on-line state estimation where it was previously impractical.