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Paolo Pegoraro

Università degli Studi di Cagliari, DIEE, Faculty Member

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Associate Professor of Instrumentation and Measurement

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Alexandra Von Meier

Thierry H Van Cutsem

Université de Liège

Julius-Maximilians-Universitaet Wuerzburg, CASCC

GUSTAVO VALERIO VIDAL VALVERDE

Virginia Tech

Eindhoven University of Technology

A. P. Sakis Meliopoulos

KTH Royal Institute of Technology

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Papers by Paolo Pegoraro

Refined Modeling and Compensation of Current Transformers Behavior for Line Parameters Estimation Based on Synchronized Measurements

IEEE Open Journal of Instrumentation and Measurement

Nowadays, in modern management and control applications, line parameters need to be known more ac... more Nowadays, in modern management and control applications, line parameters need to be known more accurately than in the past to achieve a reliable operation of the distribution grids. Phasor measurement units (PMUs) may improve line parameter estimation processes, but the accuracy of the result is affected by all the elements of the PMU-based measurement chain, in particular by the instrument transformers. Current transformers (CTs) are nonlinear and, therefore, their behavior is not easily described: their models cannot be straightforwardly included in the estimation problem. In this regard, this article refines modeling and compensation of CT systematic errors in line parameter estimation processes, based on different methods to describe the transformer behavior under various operating conditions. As the main result, the systematic errors of CTs are remarkably identified and mitigated. Moreover, the estimation of shunt susceptance values is significantly improved. INDEX TERMS Current transformers (CTs), instrument transformers (ITs), line parameters, power distribution systems (DSs), random errors, synchrophasor measurements, systematic errors, voltage transformers (VTs).

Estimation of Line Parameters, Tap Changer Ratios, and Systematic Measurement Errors Based on Synchronized Measurements and a General Model of Tap-Changing Transformers

IEEE Open Journal of Instrumentation and Measurement

A primary requirement for the transmission system operator is an accurate knowledge of grid param... more A primary requirement for the transmission system operator is an accurate knowledge of grid parameters. Moreover, the availability of effective and accurate monitoring tools allows the proper operation of power transmission grids. However, in spite of the now widespread possibility of having monitoring systems based on synchronized measurements, the monitoring applications can be affected not only by the inevitable uncertainty sources but also by the simplified or incomplete modeling of the network components. For this reason, the impact on power system monitoring and control applications of tap-changing transformer models is a key point. In this scenario, this article presents a method to estimate simultaneously line parameters, tap changer ratios, and systematic measurement errors associated with the instrument transformers. The method exploits a flexible model of the tap-changing transformer based on a parameter representing the ratio between the two winding impedances of the transformer. The proposal is based also on the suitable modeling of the measurement chain and on the constraints introduced by the equations of involved transmissions lines and transformers. The validation has been carried out by means of tests performed on the IEEE 14 Bus Test Case. INDEX TERMS Current measurement, instrument transformers, measurement errors, parameter estimation, phasor measurement units (PMUs), power transmission lines, tap changers, voltage measurement. I. INTRODUCTION A CCURATE modeling of network components is increasingly in demand for modern power systems. In this context, the models of power transformers and particularly of tap-changing transformers can be critical. Two are the most used tap-changing transformer models for power system studies (see, [1], [2], [3]), considered not only in the literature but also in software packages implementation. These two models represent the tap-changing transformer as a π-branch assuming that the transformer short circuit impedance is provided either by nominal winding or by the tapped winding. The values for the model parameters can be obtained from the nameplate data provided by manufacturers, reporting, for example, the short circuit impedance. Nevertheless, it is important to highlight that, commonly, the nameplate data do not provide detailed data on the nominal and tapped windings [4], because manufacturers are not compelled by regulations to make this information available to customers. These models have been largely applied in studies concerning power systems: in [5], a single-phase estimator of both power system state and transformer tap positions is

Effect of Unbalance on Positive-Sequence Synchrophasor, Frequency, and ROCOF Estimations

IEEE Transactions on Instrumentation and Measurement, 2018

An IoT architecture for wide area measurement systems: A virtualized PMU based approach

2016 IEEE International Energy Conference (ENERGYCON), 2016

Internet of Things (IoT) technologies are pervading different application domains by relying on s... more Internet of Things (IoT) technologies are pervading different application domains by relying on sensing and actuating devices that share, process and present meaningful real-world information. One of the most important of these domains is certainly the Smart Grid (SG), where the use of advanced measurement and control equipment and the diffusion of communication technologies are making an adaptive, reliable, and efficient management of the energy possible, with several new applications. In this scenario, this paper focuses on one of the major IoT features, which is the virtualization, and proposes an IoT solution for wide area measurement systems where virtualized phasor measurement resources are introduced. Such a solution is intended to make a programmable and smart environment fostering interoperability, reusability and flexibility of SG services. The performance of the system is evaluated for both the traffic generated and the latency to understand which scenarios can benefit from its deployment.

IoT cloud-based distribution system state estimation: Virtual objects and context-awareness

2016 IEEE International Conference on Communications (ICC), 2016

This paper presents an IoT cloud-based state estimation system for distribution networks in which... more This paper presents an IoT cloud-based state estimation system for distribution networks in which the PMUs (Phasor Measurement Units) are virtualized with respect to the physical devices. In the considered system only application level entities are put in the cloud, whereas virtualized PMUs are running in the communication network edge (i.e. closer to the physical objects) in order to have a certain degree of local logic, which allows to implement a bandwidth-efficient and smart data transmission to the involved applications in the cloud. The major contributions of the paper are the following: we demonstrate that a cloud-based architecture is capable of achieving the QoS level required by the specific state estimation application; we show that implementing a certain local logic for data transmission in the cloud, the result of the state estimation is not degraded with respect to the case of an estimation that takes place frequently at fixed intervals; we show the results in terms of latency and reduced network load for a reference smart grid network.

Adaptive PMU-based distribution system state estimation exploiting the cloud-based IoT paradigm

2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016

This paper presents an adaptive Distribution System State Estimation (DSSE) which relies on a Clo... more This paper presents an adaptive Distribution System State Estimation (DSSE) which relies on a Cloud-based IoT paradigm. The methodology is adaptive in terms of the rate of execution of the estimation process which varies depending on the indications of the distributed measurement system. The system is composed, in particular, of Phasor Measurement Units (PMUs). PMUs are virtualized with respect to the physical devices and the corresponding virtualizing modules run in the communication network edge (i.e. closer to the physical objects). PMUs are set at a higher measurement rate, while the estimation process works at a given slower rate, for example once per second, in normal operative conditions. A local decision algorithm implemented in the virtualized module, monitors the measured quantities in order to detect and address possible unexpected dynamics. In particular, different metrics can be applied: the variations and the trend of variation of the rms voltage values, but also the Rate Of Change Of Frequency (ROCOF) of the monitored signals can be used to trigger rate variation in the DSSE. In case dynamics are detected, the measurement data is sent to the DSSE at higher rates and the estimation process runs consequently on a finer time scale. In the considered system only application level entities are located in the Cloud, thus allowing to obtain a bandwidth-efficient and smart data transmission. The results obtained on a 13-bus systems prove the goodness of the proposed methodologies.

Bayesian Approach for Distribution System State Estimation With Non-Gaussian Uncertainty Models

IEEE Transactions on Instrumentation and Measurement, 2017

To deal with the increasing complexity of distribution networks that are experiencing important c... more To deal with the increasing complexity of distribution networks that are experiencing important changes, due to the widespread installation of Distributed Generation and the expected penetration of new energy resources, modern control applications must rely on an accurate picture of the grid status, given by the Distribution System State Estimator (DSSE). DSSE is required to integrate all the available information on loads and generators power exchanges (pseudomeasurements) with the realtime measurements available from the field. In most cases the statistical behavior of the measured and pseudomeasured quantities cannot be approximated by a Gaussian distribution. For this reason, it is necessary to design estimators that are able to use measurements and forecast data on power flows that can show a non-Gaussian behavior. In this paper, a DSSE algorithm based on Bayes's rule, conceived to perfectly match the uncertainty description of the available input information, is presented. The method is able to correctly handle the measurement uncertainty of conventional and synchronized measurements and to include possible correlation existing between the pseudomeasurements. Its applicability to medium voltage distribution networks and its advantages, in terms of accuracy of both estimated quantities and uncertainty intervals, is demonstrated.

Monitoring and Automation of Complex Power Systems

Energies

This Special Issue aims at collecting new research contributions and perspectives on the topic of... more

Space Vector Taylor–Fourier Models for Synchrophasor, Frequency, and ROCOF Measurements in Three-Phase Systems

IEEE Transactions on Instrumentation and Measurement, 2019

Taylor-Fourier (TF) filters represent a powerful tool to design PMU algorithms able to estimate s... more Taylor-Fourier (TF) filters represent a powerful tool to design PMU algorithms able to estimate synchrophasor, frequency and rate of change of frequency (ROCOF). The resulting techniques are based on dynamic representations of the synchrophasor, hence they are particularly suitable to track the evolution of its parameters during time-varying conditions. Electrical quantities in power systems are typically three-phase and weakly unbalanced, but most PMU measurement techniques are developed by considering them as a set of three singlephase signals; on the contrary, this peculiarity can be favorably exploited to improve accuracy and reduce the computational cost. In this respect, the present paper proposes to directly perform the TF expansion of the space vector (SV) samples obtained from three-phase measurements. A new paradigm allows to independently estimate positive and negative sequence synchrophasors along with system frequency and ROCOF, leveraging the threephase characteristics. Performance of the proposed technique is assessed by using test signals inspired by standard IEEE C37.118.1-2011, including noise as well as magnitude and phase unbalance. Achieved results highlight the flexibility of the enhanced SV-based approach, which is capable to combine excellent dynamic performance together with accurate estimation of both positive and negative sequence components.

A New Kalman Filter Approach Including System Frequency for an Effective PMU-based Power System State Estimation

2019 IEEE 10th International Workshop on Applied Measurements for Power Systems (AMPS), 2019

This paper presents a new PMU-based Kalman Filter approach for Power System State Estimation, in ... more This paper presents a new PMU-based Kalman Filter approach for Power System State Estimation, in which an estimator model is proposed to include the system frequency and exploit synchronized frequency measurements. The performance of this new estimator is evaluated in comparison to different state estimation methodologies, in order to assess the impact and potential benefits given by the integration of the frequency input. The improvement in the estimation accuracy achievable for the quantities of interest (node voltages and branch currents) thanks to the proposed approach is assessed under realistic operating conditions, taking into account, in particular, the possible occurrence of off-nominal frequency conditions. The main findings and results obtained by means of simulations performed on a standard IEEE network are presented and discussed.

Fast multi-area approach for distribution system state estimation

2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016

This paper presents the application of a fast twostep multi-area approach for state estimation in... more This paper presents the application of a fast twostep multi-area approach for state estimation in wide-area distribution systems. In a previous paper [10], the authors have assessed the possibility to perform Distribution System State Estimation (DSSE) in a multi-area framework, designing the methodology according to the configuration of the measurement infrastructure. In this paper, constraints associated to the measurement placement are removed and the methodology proposed in [10] has been generalized to deal with every possible measurement system. A new second step procedure has been also designed to obtain a more computationally efficient refinement of the voltage profile. The proposed multi-area method can be performed in a decentralized way and with parallel processing, relying on limited data communication. Test results, obtained on the 123-bus IEEE test network, are presented and discussed.

Low-Latency, Three-Phase PMU Algorithms: Review and Performance Comparison

Phasor Measurement Units are the most advanced instruments for power network monitoring, since th... more Phasor Measurement Units are the most advanced instruments for power network monitoring, since they allow phasors, frequency and rate of change of frequency (ROCOF) to be measured in predetermined time instants with respect to an absolute time reference. The employed estimation algorithm plays a key role in overall performance under off-nominal conditions; the challenge to be faced is combining high steady-state accuracy with fast responsiveness in dynamic conditions, small reporting latency and reduced computational burden. Under regular operation, AC power networks are weakly unbalanced three-phase systems. Based on this consideration, the recent literature has proposed native three-phase estimation algorithms that effectively exploit this property to accurately identify the positive sequence synchrophasor, frequency and ROCOF. In this respect, the present paper describes three among the most promising three-phase algorithms based on the Space Vector transformation. By means of nu...

An Efficient and Accurate Solution for Distribution System State Estimation with Multiarea Architecture

IEEE Transactions on Instrumentation and Measurement, 2017

Distribution System State Estimation (DSSE) is an essential tool for the management and control o... more Distribution System State Estimation (DSSE) is an essential tool for the management and control of future distribution networks. Distribution grids are usually characterized by a very large number of nodes and different voltage levels. Moreover, different portions of the system can be operated by different Distribution System Operators. In this context, multiarea approaches are key tools to efficiently perform DSSE. This paper presents a novel approach for Multi-Area State Estimation in distribution systems. The proposed algorithm is based on a twostep procedure, where the first-step local estimations are refined through a newly designed second step that allows the integration of the measurement information available in the adjacent areas. The main novelty in this paper is the mathematical analysis of the impact brought by possible measurements shared among different areas, which drives the design of a new efficient Weighted Least Squares formulation of the second step to maximize the achievable estimation accuracy. Tests performed on the unbalanced IEEE 123-bus network prove the goodness of the new multiarea estimator proposed and show the accuracy and efficiency enhancements obtainable with respect to previous literature.

Bayesian distribution system state estimation in presence of non-Gaussian pseudo-measurements

2016 IEEE International Workshop on Applied Measurements for Power Systems (AMPS), 2016

Distribution System State Estimation (DSSE) is nowadays essential to enable the smart management ... more Distribution System State Estimation (DSSE) is nowadays essential to enable the smart management of medium and low voltage grids. Due to the lack of a suitable measurement infrastructure, DSSE usually relies on the use of power injection pseudo-measurements derived from the knowledge of the historical and statistical behaviour of loads and generators. The uncertainty of these pseudo-measurements could not fit with the normal distribution typically considered in DSSE. For this reason, suitable approaches have to be designed both to model the pseudo-measurements uncertainty and to duly consider it in the DSSE process. This paper proposes a DSSE algorithm based on the Bayesian theory able to properly handle pseudomeasurements with any uncertainty distribution. The procedure used to cluster different categories of prosumers and to generate the pseudo-measurement parameters provided as input to the DSSE is also presented. Tests on a low voltage network show the applicability of the proposed approach and the associated benefits.

Uncertainty of Voltage Profile in PMU-Based Distribution System State Estimation

IEEE Transactions on Instrumentation and Measurement, 2016

Distribution System State Estimation (DSSE) tools are required to estimate the real operating con... more Distribution System State Estimation (DSSE) tools are required to estimate the real operating conditions of power distribution networks. The accuracy of the quantities estimated through DSSE plays a key role for the effectiveness of the management and controls functions. The paper presents a comprehensive mathematical analysis, aimed at highlighting the most important factors affecting the accuracy of the voltage profile obtained by means of Weighted Least Squares (WLS) estimators. The proposed analysis shows the way in which the uncertainty components of the voltage estimations depends on the measurement system available on the field. In particular, this paper considers synchrophasors measurements provided by Phasor Measurement Units (PMUs) and hybrid measurements systems presenting also conventional devices. Tests performed on a 95-bus network prove the validity of the theoretical analysis and show the importance of the results also in a meter placement perspective, emphasizing the requirements needed to achieve specific accuracy targets.

Multi-source neural networks based on fixed and multiple resolution analysis for speech recognition

IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222), 2001

Multi Source Neural Networks ... is practically feasible thanks to the use of a NN architecture d... more

Compressive Sensing of a Taylor-Fourier Multifrequency Model for Synchrophasor Estimation

IEEE Transactions on Instrumentation and Measurement, 2015

Synchrophasor measurements, performed by phasor measurement units (PMUs), are becoming increasing... more Synchrophasor measurements, performed by phasor measurement units (PMUs), are becoming increasingly important for power system network monitoring. Synchrophasor standards define test signals for verification of PMU compliance, and set acceptance limits in each test condition for two performance classes (P and M). Several PMU algorithms have been proposed to deal with steady-state and dynamic operating conditions identified by the standard. Research and discussion arising from design, implementation, testing and characterization of PMUs evidenced that some disturbances, such as interharmonic interfering signals, can seriously degrade synchrophasor measurement accuracy. In this paper, a new Compressive Sensing (CS) approach is introduced and applied to synchrophasor measurements using a Taylor-Fourier multifrequency model (CSTFM). The aim is to exploit, in a joint method, the properties of CS and the Taylor-Fourier transform to identify the most relevant components of the signal, even under dynamic conditions, and to model them in the estimation procedure, thus limiting the impact of harmonic and interhamonic interferences. The CSTFM approach is verified using composite tests derived from the test conditions of the synchrophasor standard and simulation results are presented to show its potentialities.

E-learning in instrumentation and measurement courses

Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510)

E-learning is the one possible evolution of traditional teaching techniques and is becoming a mat... more E-learning is the one possible evolution of traditional teaching techniques and is becoming a mature technology. Several commercial suites are available to author multimedia courses either to be distributed in physical form (e.g. on CD or DVD) or to be used on-line. However the application of these suites to the instrumentation and measurement courses and in general to courses that

Platform independent architectures for cooperative remote control of automated test laboratories

Proceedings AUTOTESTCON 2003. IEEE Systems Readiness Technology Conference.

Compressive sensing plus Taylor-Fourier Transform for synchrophasor estimation

2014 IEEE International Workshop on Applied Measurements for Power Systems Proceedings (AMPS), 2014

The synchrophasor Standard IEEE C37.118.1, along with its amendment, defines two compliance class... more The synchrophasor Standard IEEE C37.118.1, along with its amendment, defines two compliance classes for phasor measurement units (PMUs), the different test signals to be adopted for verification and the limits that should be respected for each test condition. In recent years, many synchrophasor estimation algorithms have been proposed to deal with the operative conditions identified by the standard, that can be both steady state and dynamic. The research has shown that some disturbances, such as interharmonic interfering signals, can seriously degrade synchrophasor measurement accuracy. In this work, a new two-stage approach, relying on Compressive Sensing (CS) and Taylor Fourier Transform (TFT), is proposed to identify the most relevant interfering components in the signal spectrum and to limit their impact on synchrophasor estimation. Simulation results are reported to confirm the algorithm efficiency.

Refined Modeling and Compensation of Current Transformers Behavior for Line Parameters Estimation Based on Synchronized Measurements

IEEE Open Journal of Instrumentation and Measurement

Nowadays, in modern management and control applications, line parameters need to be known more ac... more Nowadays, in modern management and control applications, line parameters need to be known more accurately than in the past to achieve a reliable operation of the distribution grids. Phasor measurement units (PMUs) may improve line parameter estimation processes, but the accuracy of the result is affected by all the elements of the PMU-based measurement chain, in particular by the instrument transformers. Current transformers (CTs) are nonlinear and, therefore, their behavior is not easily described: their models cannot be straightforwardly included in the estimation problem. In this regard, this article refines modeling and compensation of CT systematic errors in line parameter estimation processes, based on different methods to describe the transformer behavior under various operating conditions. As the main result, the systematic errors of CTs are remarkably identified and mitigated. Moreover, the estimation of shunt susceptance values is significantly improved. INDEX TERMS Current transformers (CTs), instrument transformers (ITs), line parameters, power distribution systems (DSs), random errors, synchrophasor measurements, systematic errors, voltage transformers (VTs).

Estimation of Line Parameters, Tap Changer Ratios, and Systematic Measurement Errors Based on Synchronized Measurements and a General Model of Tap-Changing Transformers

IEEE Open Journal of Instrumentation and Measurement

A primary requirement for the transmission system operator is an accurate knowledge of grid param... more A primary requirement for the transmission system operator is an accurate knowledge of grid parameters. Moreover, the availability of effective and accurate monitoring tools allows the proper operation of power transmission grids. However, in spite of the now widespread possibility of having monitoring systems based on synchronized measurements, the monitoring applications can be affected not only by the inevitable uncertainty sources but also by the simplified or incomplete modeling of the network components. For this reason, the impact on power system monitoring and control applications of tap-changing transformer models is a key point. In this scenario, this article presents a method to estimate simultaneously line parameters, tap changer ratios, and systematic measurement errors associated with the instrument transformers. The method exploits a flexible model of the tap-changing transformer based on a parameter representing the ratio between the two winding impedances of the transformer. The proposal is based also on the suitable modeling of the measurement chain and on the constraints introduced by the equations of involved transmissions lines and transformers. The validation has been carried out by means of tests performed on the IEEE 14 Bus Test Case. INDEX TERMS Current measurement, instrument transformers, measurement errors, parameter estimation, phasor measurement units (PMUs), power transmission lines, tap changers, voltage measurement. I. INTRODUCTION A CCURATE modeling of network components is increasingly in demand for modern power systems. In this context, the models of power transformers and particularly of tap-changing transformers can be critical. Two are the most used tap-changing transformer models for power system studies (see, [1], [2], [3]), considered not only in the literature but also in software packages implementation. These two models represent the tap-changing transformer as a π-branch assuming that the transformer short circuit impedance is provided either by nominal winding or by the tapped winding. The values for the model parameters can be obtained from the nameplate data provided by manufacturers, reporting, for example, the short circuit impedance. Nevertheless, it is important to highlight that, commonly, the nameplate data do not provide detailed data on the nominal and tapped windings [4], because manufacturers are not compelled by regulations to make this information available to customers. These models have been largely applied in studies concerning power systems: in [5], a single-phase estimator of both power system state and transformer tap positions is

Effect of Unbalance on Positive-Sequence Synchrophasor, Frequency, and ROCOF Estimations

IEEE Transactions on Instrumentation and Measurement, 2018

An IoT architecture for wide area measurement systems: A virtualized PMU based approach

2016 IEEE International Energy Conference (ENERGYCON), 2016

Internet of Things (IoT) technologies are pervading different application domains by relying on s... more Internet of Things (IoT) technologies are pervading different application domains by relying on sensing and actuating devices that share, process and present meaningful real-world information. One of the most important of these domains is certainly the Smart Grid (SG), where the use of advanced measurement and control equipment and the diffusion of communication technologies are making an adaptive, reliable, and efficient management of the energy possible, with several new applications. In this scenario, this paper focuses on one of the major IoT features, which is the virtualization, and proposes an IoT solution for wide area measurement systems where virtualized phasor measurement resources are introduced. Such a solution is intended to make a programmable and smart environment fostering interoperability, reusability and flexibility of SG services. The performance of the system is evaluated for both the traffic generated and the latency to understand which scenarios can benefit from its deployment.

IoT cloud-based distribution system state estimation: Virtual objects and context-awareness

2016 IEEE International Conference on Communications (ICC), 2016

This paper presents an IoT cloud-based state estimation system for distribution networks in which... more This paper presents an IoT cloud-based state estimation system for distribution networks in which the PMUs (Phasor Measurement Units) are virtualized with respect to the physical devices. In the considered system only application level entities are put in the cloud, whereas virtualized PMUs are running in the communication network edge (i.e. closer to the physical objects) in order to have a certain degree of local logic, which allows to implement a bandwidth-efficient and smart data transmission to the involved applications in the cloud. The major contributions of the paper are the following: we demonstrate that a cloud-based architecture is capable of achieving the QoS level required by the specific state estimation application; we show that implementing a certain local logic for data transmission in the cloud, the result of the state estimation is not degraded with respect to the case of an estimation that takes place frequently at fixed intervals; we show the results in terms of latency and reduced network load for a reference smart grid network.

Adaptive PMU-based distribution system state estimation exploiting the cloud-based IoT paradigm

2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016

This paper presents an adaptive Distribution System State Estimation (DSSE) which relies on a Clo... more This paper presents an adaptive Distribution System State Estimation (DSSE) which relies on a Cloud-based IoT paradigm. The methodology is adaptive in terms of the rate of execution of the estimation process which varies depending on the indications of the distributed measurement system. The system is composed, in particular, of Phasor Measurement Units (PMUs). PMUs are virtualized with respect to the physical devices and the corresponding virtualizing modules run in the communication network edge (i.e. closer to the physical objects). PMUs are set at a higher measurement rate, while the estimation process works at a given slower rate, for example once per second, in normal operative conditions. A local decision algorithm implemented in the virtualized module, monitors the measured quantities in order to detect and address possible unexpected dynamics. In particular, different metrics can be applied: the variations and the trend of variation of the rms voltage values, but also the Rate Of Change Of Frequency (ROCOF) of the monitored signals can be used to trigger rate variation in the DSSE. In case dynamics are detected, the measurement data is sent to the DSSE at higher rates and the estimation process runs consequently on a finer time scale. In the considered system only application level entities are located in the Cloud, thus allowing to obtain a bandwidth-efficient and smart data transmission. The results obtained on a 13-bus systems prove the goodness of the proposed methodologies.

Bayesian Approach for Distribution System State Estimation With Non-Gaussian Uncertainty Models

IEEE Transactions on Instrumentation and Measurement, 2017

To deal with the increasing complexity of distribution networks that are experiencing important c... more To deal with the increasing complexity of distribution networks that are experiencing important changes, due to the widespread installation of Distributed Generation and the expected penetration of new energy resources, modern control applications must rely on an accurate picture of the grid status, given by the Distribution System State Estimator (DSSE). DSSE is required to integrate all the available information on loads and generators power exchanges (pseudomeasurements) with the realtime measurements available from the field. In most cases the statistical behavior of the measured and pseudomeasured quantities cannot be approximated by a Gaussian distribution. For this reason, it is necessary to design estimators that are able to use measurements and forecast data on power flows that can show a non-Gaussian behavior. In this paper, a DSSE algorithm based on Bayes's rule, conceived to perfectly match the uncertainty description of the available input information, is presented. The method is able to correctly handle the measurement uncertainty of conventional and synchronized measurements and to include possible correlation existing between the pseudomeasurements. Its applicability to medium voltage distribution networks and its advantages, in terms of accuracy of both estimated quantities and uncertainty intervals, is demonstrated.

Monitoring and Automation of Complex Power Systems

Energies

This Special Issue aims at collecting new research contributions and perspectives on the topic of... more

Space Vector Taylor–Fourier Models for Synchrophasor, Frequency, and ROCOF Measurements in Three-Phase Systems

IEEE Transactions on Instrumentation and Measurement, 2019

Taylor-Fourier (TF) filters represent a powerful tool to design PMU algorithms able to estimate s... more Taylor-Fourier (TF) filters represent a powerful tool to design PMU algorithms able to estimate synchrophasor, frequency and rate of change of frequency (ROCOF). The resulting techniques are based on dynamic representations of the synchrophasor, hence they are particularly suitable to track the evolution of its parameters during time-varying conditions. Electrical quantities in power systems are typically three-phase and weakly unbalanced, but most PMU measurement techniques are developed by considering them as a set of three singlephase signals; on the contrary, this peculiarity can be favorably exploited to improve accuracy and reduce the computational cost. In this respect, the present paper proposes to directly perform the TF expansion of the space vector (SV) samples obtained from three-phase measurements. A new paradigm allows to independently estimate positive and negative sequence synchrophasors along with system frequency and ROCOF, leveraging the threephase characteristics. Performance of the proposed technique is assessed by using test signals inspired by standard IEEE C37.118.1-2011, including noise as well as magnitude and phase unbalance. Achieved results highlight the flexibility of the enhanced SV-based approach, which is capable to combine excellent dynamic performance together with accurate estimation of both positive and negative sequence components.

A New Kalman Filter Approach Including System Frequency for an Effective PMU-based Power System State Estimation

2019 IEEE 10th International Workshop on Applied Measurements for Power Systems (AMPS), 2019

This paper presents a new PMU-based Kalman Filter approach for Power System State Estimation, in ... more This paper presents a new PMU-based Kalman Filter approach for Power System State Estimation, in which an estimator model is proposed to include the system frequency and exploit synchronized frequency measurements. The performance of this new estimator is evaluated in comparison to different state estimation methodologies, in order to assess the impact and potential benefits given by the integration of the frequency input. The improvement in the estimation accuracy achievable for the quantities of interest (node voltages and branch currents) thanks to the proposed approach is assessed under realistic operating conditions, taking into account, in particular, the possible occurrence of off-nominal frequency conditions. The main findings and results obtained by means of simulations performed on a standard IEEE network are presented and discussed.

Fast multi-area approach for distribution system state estimation

2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016

This paper presents the application of a fast twostep multi-area approach for state estimation in... more This paper presents the application of a fast twostep multi-area approach for state estimation in wide-area distribution systems. In a previous paper [10], the authors have assessed the possibility to perform Distribution System State Estimation (DSSE) in a multi-area framework, designing the methodology according to the configuration of the measurement infrastructure. In this paper, constraints associated to the measurement placement are removed and the methodology proposed in [10] has been generalized to deal with every possible measurement system. A new second step procedure has been also designed to obtain a more computationally efficient refinement of the voltage profile. The proposed multi-area method can be performed in a decentralized way and with parallel processing, relying on limited data communication. Test results, obtained on the 123-bus IEEE test network, are presented and discussed.

Low-Latency, Three-Phase PMU Algorithms: Review and Performance Comparison

Phasor Measurement Units are the most advanced instruments for power network monitoring, since th... more Phasor Measurement Units are the most advanced instruments for power network monitoring, since they allow phasors, frequency and rate of change of frequency (ROCOF) to be measured in predetermined time instants with respect to an absolute time reference. The employed estimation algorithm plays a key role in overall performance under off-nominal conditions; the challenge to be faced is combining high steady-state accuracy with fast responsiveness in dynamic conditions, small reporting latency and reduced computational burden. Under regular operation, AC power networks are weakly unbalanced three-phase systems. Based on this consideration, the recent literature has proposed native three-phase estimation algorithms that effectively exploit this property to accurately identify the positive sequence synchrophasor, frequency and ROCOF. In this respect, the present paper describes three among the most promising three-phase algorithms based on the Space Vector transformation. By means of nu...

An Efficient and Accurate Solution for Distribution System State Estimation with Multiarea Architecture

IEEE Transactions on Instrumentation and Measurement, 2017

Distribution System State Estimation (DSSE) is an essential tool for the management and control o... more Distribution System State Estimation (DSSE) is an essential tool for the management and control of future distribution networks. Distribution grids are usually characterized by a very large number of nodes and different voltage levels. Moreover, different portions of the system can be operated by different Distribution System Operators. In this context, multiarea approaches are key tools to efficiently perform DSSE. This paper presents a novel approach for Multi-Area State Estimation in distribution systems. The proposed algorithm is based on a twostep procedure, where the first-step local estimations are refined through a newly designed second step that allows the integration of the measurement information available in the adjacent areas. The main novelty in this paper is the mathematical analysis of the impact brought by possible measurements shared among different areas, which drives the design of a new efficient Weighted Least Squares formulation of the second step to maximize the achievable estimation accuracy. Tests performed on the unbalanced IEEE 123-bus network prove the goodness of the new multiarea estimator proposed and show the accuracy and efficiency enhancements obtainable with respect to previous literature.

Bayesian distribution system state estimation in presence of non-Gaussian pseudo-measurements

2016 IEEE International Workshop on Applied Measurements for Power Systems (AMPS), 2016

Distribution System State Estimation (DSSE) is nowadays essential to enable the smart management ... more Distribution System State Estimation (DSSE) is nowadays essential to enable the smart management of medium and low voltage grids. Due to the lack of a suitable measurement infrastructure, DSSE usually relies on the use of power injection pseudo-measurements derived from the knowledge of the historical and statistical behaviour of loads and generators. The uncertainty of these pseudo-measurements could not fit with the normal distribution typically considered in DSSE. For this reason, suitable approaches have to be designed both to model the pseudo-measurements uncertainty and to duly consider it in the DSSE process. This paper proposes a DSSE algorithm based on the Bayesian theory able to properly handle pseudomeasurements with any uncertainty distribution. The procedure used to cluster different categories of prosumers and to generate the pseudo-measurement parameters provided as input to the DSSE is also presented. Tests on a low voltage network show the applicability of the proposed approach and the associated benefits.

Uncertainty of Voltage Profile in PMU-Based Distribution System State Estimation

IEEE Transactions on Instrumentation and Measurement, 2016

Distribution System State Estimation (DSSE) tools are required to estimate the real operating con... more Distribution System State Estimation (DSSE) tools are required to estimate the real operating conditions of power distribution networks. The accuracy of the quantities estimated through DSSE plays a key role for the effectiveness of the management and controls functions. The paper presents a comprehensive mathematical analysis, aimed at highlighting the most important factors affecting the accuracy of the voltage profile obtained by means of Weighted Least Squares (WLS) estimators. The proposed analysis shows the way in which the uncertainty components of the voltage estimations depends on the measurement system available on the field. In particular, this paper considers synchrophasors measurements provided by Phasor Measurement Units (PMUs) and hybrid measurements systems presenting also conventional devices. Tests performed on a 95-bus network prove the validity of the theoretical analysis and show the importance of the results also in a meter placement perspective, emphasizing the requirements needed to achieve specific accuracy targets.

Multi-source neural networks based on fixed and multiple resolution analysis for speech recognition

IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222), 2001

Multi Source Neural Networks ... is practically feasible thanks to the use of a NN architecture d... more

Compressive Sensing of a Taylor-Fourier Multifrequency Model for Synchrophasor Estimation

IEEE Transactions on Instrumentation and Measurement, 2015

Synchrophasor measurements, performed by phasor measurement units (PMUs), are becoming increasing... more Synchrophasor measurements, performed by phasor measurement units (PMUs), are becoming increasingly important for power system network monitoring. Synchrophasor standards define test signals for verification of PMU compliance, and set acceptance limits in each test condition for two performance classes (P and M). Several PMU algorithms have been proposed to deal with steady-state and dynamic operating conditions identified by the standard. Research and discussion arising from design, implementation, testing and characterization of PMUs evidenced that some disturbances, such as interharmonic interfering signals, can seriously degrade synchrophasor measurement accuracy. In this paper, a new Compressive Sensing (CS) approach is introduced and applied to synchrophasor measurements using a Taylor-Fourier multifrequency model (CSTFM). The aim is to exploit, in a joint method, the properties of CS and the Taylor-Fourier transform to identify the most relevant components of the signal, even under dynamic conditions, and to model them in the estimation procedure, thus limiting the impact of harmonic and interhamonic interferences. The CSTFM approach is verified using composite tests derived from the test conditions of the synchrophasor standard and simulation results are presented to show its potentialities.

E-learning in instrumentation and measurement courses

Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510)

E-learning is the one possible evolution of traditional teaching techniques and is becoming a mat... more E-learning is the one possible evolution of traditional teaching techniques and is becoming a mature technology. Several commercial suites are available to author multimedia courses either to be distributed in physical form (e.g. on CD or DVD) or to be used on-line. However the application of these suites to the instrumentation and measurement courses and in general to courses that

Platform independent architectures for cooperative remote control of automated test laboratories

Proceedings AUTOTESTCON 2003. IEEE Systems Readiness Technology Conference.

Compressive sensing plus Taylor-Fourier Transform for synchrophasor estimation

2014 IEEE International Workshop on Applied Measurements for Power Systems Proceedings (AMPS), 2014

The synchrophasor Standard IEEE C37.118.1, along with its amendment, defines two compliance class... more The synchrophasor Standard IEEE C37.118.1, along with its amendment, defines two compliance classes for phasor measurement units (PMUs), the different test signals to be adopted for verification and the limits that should be respected for each test condition. In recent years, many synchrophasor estimation algorithms have been proposed to deal with the operative conditions identified by the standard, that can be both steady state and dynamic. The research has shown that some disturbances, such as interharmonic interfering signals, can seriously degrade synchrophasor measurement accuracy. In this work, a new two-stage approach, relying on Compressive Sensing (CS) and Taylor Fourier Transform (TFT), is proposed to identify the most relevant interfering components in the signal spectrum and to limit their impact on synchrophasor estimation. Simulation results are reported to confirm the algorithm efficiency.