Definition and assessment of reference values for PMU calibration in static and transient conditions

The calibration of Phasor Measurement Units (PMUs) consists of comparing Coordinated Universal Time (UTC) time-stamped phasors (synchrophasors) estimated by the PMU under test, against reference synchrophasors generated through a PMU calibrator. The IEEE Standard C37.118-2011 and its amendment (IEEE Std) describe compliance tests for static and dynamic conditions, and indicate the relative limits in terms of accuracy. In this context, the paper focuses on the definition and accuracy assessment of the reference synchrophasors in the test conditions dictated by the above IEEE Std. In the first part of the paper, we describe the characterization of a nonlinear least-squares (NL-LSQ) fitting algorithm used to determine the parameters of the reference synchrophasors. We analyse the uniqueness and robustness of the solution provided by the algorithm. We assess its accuracy within the whole range of static tests required by the IEEE Std. In the second part, we discuss the appropriateness of synchrophasor model to evaluate the PMU performance in step test conditions. We compare the proposed algorithm against two synchrophasor estimation algorithms. Finally, we propose a time domain process for the better evaluation of PMU performances in transient conditions

Synchrophasors: Multilevel Assessment and Data Quality Improvement for Enhanced System Reliability

. This study presents a comprehensive framework for testing and evaluation of Phasor Measurement Units (PMUs) and synchrophasor systems under normal power system operating conditions, as well as during disturbances such as faults and transients. The proposed framework suggests a performance assessment to be conducted in three steps: (a) type testing: conducted in the synchrophasor calibration laboratory according to accepted industrial standards; (b) application testing: conducted to evaluate the performance of the PMUs under faults, transients, and other disturbances in power systems; (c) end-to-end system testing: conducted to assess the risk and quantify the impact of measurement errors on the applications of interest. The suggested calibration toolset (type testing) enables performance characterization of different design alternatives in a standalone PMU (e.g., length of phasor estimation windows, filtering windows, reporting rates, etc.). In conjunction with the standard performance requirements, this work defines new metrics for PMU performance evaluations under any static and dynamic conditions that may unfold in the grid. The new metrics offer a more realistic understanding of the overall PMU performance and help users choose the appropriate device/settings for the target applications. Furthermore, the proposed probabilistic techniques quantify the PMU accuracy to various test performance thresholds specified by corresponding IEEE standards, rather than having only the pass/fail test outcome, as well as the probability of specific failures to meet the standard requirements defined in terms of the phasor, frequency, and rate of change of frequency accuracy. Application testing analysis encompasses PMU performance evaluation under faults and other prevailing conditions, and offers a realistic assessment of the PMU measurement errors in real-world field scenarios and reveals additional performance characteristics that are crucial for the overall application evaluation. End-to-end system tests quantify the impact of synchrophasor estimation errors and their propagation from the PMU towards the end-use applications and evaluate the associated risk. In this work, extensive experimental results demonstrate the advantages of the proposed framework and its applicability is verified through two synchrophasor applications, namely: Fault Location and Modal Analysis. Finally, a data-driven technique (Principal Component Pursuit) is proposed for the correction and completion of the synchrophasor data blocks, and its application and effectiveness is validated in modal analyzes

PMU-Based Estimation of Dynamic State Jacobian Matrix

In this paper, a hybrid measurement- and model-based method is proposed which can estimate the dynamic state Jacobian matrix in near real-time. The proposed method is computationally efficient and robust to the variation of network topology. A numerical example is given to show that the proposed method is able to provide good estimation for the dynamic state Jacobian matrix and is superior to the model-based method under undetectable network topology change. The proposed method may also help identify big discrepancy in the assumed network model.Comment: IEEE International Conference on Circuits and Systems (ISCAS) 201

Synchrophasors: Multilevel Assessment and Data Quality Improvement for Enhanced System Reliability

. This study presents a comprehensive framework for testing and evaluation of Phasor Measurement Units (PMUs) and synchrophasor systems under normal power system operating conditions, as well as during disturbances such as faults and transients. The proposed framework suggests a performance assessment to be conducted in three steps: (a) type testing: conducted in the synchrophasor calibration laboratory according to accepted industrial standards; (b) application testing: conducted to evaluate the performance of the PMUs under faults, transients, and other disturbances in power systems; (c) end-to-end system testing: conducted to assess the risk and quantify the impact of measurement errors on the applications of interest. The suggested calibration toolset (type testing) enables performance characterization of different design alternatives in a standalone PMU (e.g., length of phasor estimation windows, filtering windows, reporting rates, etc.). In conjunction with the standard performance requirements, this work defines new metrics for PMU performance evaluations under any static and dynamic conditions that may unfold in the grid. The new metrics offer a more realistic understanding of the overall PMU performance and help users choose the appropriate device/settings for the target applications. Furthermore, the proposed probabilistic techniques quantify the PMU accuracy to various test performance thresholds specified by corresponding IEEE standards, rather than having only the pass/fail test outcome, as well as the probability of specific failures to meet the standard requirements defined in terms of the phasor, frequency, and rate of change of frequency accuracy. Application testing analysis encompasses PMU performance evaluation under faults and other prevailing conditions, and offers a realistic assessment of the PMU measurement errors in real-world field scenarios and reveals additional performance characteristics that are crucial for the overall application evaluation. End-to-end system tests quantify the impact of synchrophasor estimation errors and their propagation from the PMU towards the end-use applications and evaluate the associated risk. In this work, extensive experimental results demonstrate the advantages of the proposed framework and its applicability is verified through two synchrophasor applications, namely: Fault Location and Modal Analysis. Finally, a data-driven technique (Principal Component Pursuit) is proposed for the correction and completion of the synchrophasor data blocks, and its application and effectiveness is validated in modal analyzes

Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community

Using Effective Generator Impedance for Forced Oscillation Source Location

Locating the sources of forced low-frequency oscillations in power systems is an important problem. A number of proposed methods demonstrate their practical usefulness, but many of them rely on strong modeling assumptions and provide poor performance in certain cases for reasons still not well understood. This paper proposes a systematic method for locating the source of a forced oscillation by considering a generator's response to fluctuations of its terminal voltages and currents. It is shown that a generator can be represented as an effective admittance matrix with respect to low-frequency oscillations, and an explicit form for this matrix, for various generator models, is derived. Furthermore, it is shown that a source generator, in addition to its effective admittance, is characterized by the presence of an effective current source thus giving a natural qualitative distinction between source and nonsource generators. Detailed descriptions are given of a source detection procedure based on this developed representation, and the method's effectiveness is confirmed by simulations on the recommended testbeds (eg. WECC 179-bus system). This method is free of strong modeling assumptions and is also shown to be robust in the presence of measurement noise and generator parameter uncertainty.Comment: 13 page

Measurement of dynamic voltage variation effect on instrument transformers for power grid applications

Within the framework of distribution and transmission grids, the knowledge of Instrument Transformers (ITs) behavior in distorted conditions is a topic of great interest. Its relevance stems from the ITs wide use in metering, protection, monitoring and control applications, where their role is to reduce voltage and current to levels compatible with measuring instrument inputs. In force standards require that the performance of measuring instruments is assessed under realistic conditions. On the contrary, performance tests of ITs are generally carried out only at rated conditions, so that their behavior under actual waveforms is not fully known. To cover this gap, a suitable setup for the traceable test of Voltage instrument Transformers (VTs) under a quite large set of static and time-varying test waveforms is developed. The paper, after a short description of the setup, shows the performance of two commercial VTs under some power quality events, that are amplitude and phase modulations and voltage dips

On power system automation: a Digital Twin-centric framework for the next generation of energy management systems

The ubiquitous digital transformation also influences power system operation. Emerging real-time applications in information (IT) and operational technology (OT) provide new opportunities to address the increasingly demanding power system operation imposed by the progressing energy transition. This IT/OT convergence is epitomised by the novel Digital Twin (DT) concept. By integrating sensor data into analytical models and aligning the model states with the observed system, a power system DT can be created. As a result, a validated high-fidelity model is derived, which can be applied within the next generation of energy management systems (EMS) to support power system operation. By providing a consistent and maintainable data model, the modular DT-centric EMS proposed in this work addresses several key requirements of modern EMS architectures. It increases the situation awareness in the control room, enables the implementation of model maintenance routines, and facilitates automation approaches, while raising the confidence into operational decisions deduced from the validated model. This gain in trust contributes to the digital transformation and enables a higher degree of power system automation. By considering operational planning and power system operation processes, a direct link to practice is ensured. The feasibility of the concept is examined by numerical case studies.The electrical power system is in the process of an extensive transformation. Driven by the energy transition towards renewable energy resources, many conventional power plants in Germany have already been decommissioned or will be decommissioned within the next decade. Among other things, these changes lead to an increased utilisation of power transmission equipment, and an increasing number of complex dynamic phenomena. The resulting system operation closer to physical boundaries leads to an increased susceptibility to disturbances, and to a reduced time span to react to critical contingencies and perturbations. In consequence, the task to operate the power system will become increasingly demanding. As some reactions to disturbances may be required within timeframes that exceed human capabilities, these developments are intrinsic drivers to enable a higher degree of automation in power system operation. This thesis proposes a framework to create a modular Digital Twin-centric energy management system. It enables the provision of validated and trustworthy models built from knowledge about the power system derived from physical laws, and process data. As the interaction of information and operational technologies is combined in the concept of the Digital Twin, it can serve as a framework for future energy management systems including novel applications for power system monitoring and control, which consider power system dynamics. To provide a validated high-fidelity dynamic power system model, time-synchronised phasor measurements of high-resolution are applied for validation and parameter estimation. This increases the trust into the underlying power system model as well as the confidence into operational decisions derived from advanced analytic applications such as online dynamic security assessment. By providing an appropriate, consistent, and maintainable data model, the framework addresses several key requirements of modern energy management system architectures, while enabling the implementation of advanced automation routines and control approaches. Future energy management systems can provide an increased observability based on the proposed architecture, whereby the situational awareness of human operators in the control room can be improved. In further development stages, cognitive systems can be applied that are able to learn from the data provided, e.g., machine learning based analytical functions. Thus, the framework enables a higher degree of power system automation, as well as the deployment of assistance and decision support functions for power system operation pointing towards a higher degree of automation in power system operation. The framework represents a contribution to the digital transformation of power system operation and facilitates a successful energy transition. The feasibility of the concept is examined by case studies in form of numerical simulations to provide a proof of concept.Das elektrische Energiesystem befindet sich in einem umfangreichen Transformations-prozess. Durch die voranschreitende Energiewende und den zunehmenden Einsatz erneuerbarer Energieträger sind in Deutschland viele konventionelle Kraftwerke bereits stillgelegt worden oder werden in den nächsten Jahren stillgelegt. Diese Veränderungen führen unter anderem zu einer erhöhten Betriebsmittelauslastung sowie zu einer verringerten Systemträgheit und somit zu einer zunehmenden Anzahl komplexer dynamischer Phänomene im elektrischen Energiesystem. Der Betrieb des Systems näher an den physikalischen Grenzen führt des Weiteren zu einer erhöhten Störanfälligkeit und zu einer verkürzten Zeitspanne, um auf kritische Ereignisse und Störungen zu reagieren. Infolgedessen wird die Aufgabe, das Stromnetz zu betreiben anspruchsvoller. Insbesondere dort wo Reaktionszeiten erforderlich sind, welche die menschlichen Fähigkeiten übersteigen sind die zuvor genannten Veränderungen intrinsische Treiber hin zu einem höheren Automatisierungsgrad in der Netzbetriebs- und Systemführung. Aufkommende Echtzeitanwendungen in den Informations- und Betriebstechnologien und eine zunehmende Menge an hochauflösenden Sensordaten ermöglichen neue Ansätze für den Entwurf und den Betrieb von cyber-physikalischen Systemen. Ein vielversprechender Ansatz, der in jüngster Zeit in diesem Zusammenhang diskutiert wurde, ist das Konzept des so genannten Digitalen Zwillings. Da das Zusammenspiel von Informations- und Betriebstechnologien im Konzept des Digitalen Zwillings vereint wird, kann es als Grundlage für eine zukünftige Leitsystemarchitektur und neuartige Anwendungen der Leittechnik herangezogen werden. In der vorliegenden Arbeit wird ein Framework entwickelt, welches einen Digitalen Zwilling in einer neuartigen modularen Leitsystemarchitektur für die Aufgabe der Überwachung und Steuerung zukünftiger Energiesysteme zweckdienlich einsetzbar macht. In Ergänzung zu den bereits vorhandenen Funktionen moderner Netzführungssysteme unterstützt das Konzept die Abbildung der Netzdynamik auf Basis eines dynamischen Netzmodells. Um eine realitätsgetreue Abbildung der Netzdynamik zu ermöglichen, werden zeitsynchrone Raumzeigermessungen für die Modellvalidierung und Modellparameterschätzung herangezogen. Dies erhöht die Aussagekraft von Sicherheitsanalysen, sowie das Vertrauen in die Modelle mit denen operative Entscheidungen generiert werden. Durch die Bereitstellung eines validierten, konsistenten und wartbaren Datenmodells auf der Grundlage von physikalischen Gesetzmäßigkeiten und während des Betriebs gewonnener Prozessdaten, adressiert der vorgestellte Architekturentwurf mehrere Schlüsselan-forderungen an moderne Netzleitsysteme. So ermöglicht das Framework einen höheren Automatisierungsgrad des Stromnetzbetriebs sowie den Einsatz von Entscheidungs-unterstützungsfunktionen bis hin zu vertrauenswürdigen Assistenzsystemen auf Basis kognitiver Systeme. Diese Funktionen können die Betriebssicherheit erhöhen und stellen einen wichtigen Beitrag zur Umsetzung der digitalen Transformation des Stromnetzbetriebs, sowie zur erfolgreichen Umsetzung der Energiewende dar. Das vorgestellte Konzept wird auf der Grundlage numerischer Simulationen untersucht, wobei die grundsätzliche Machbarkeit anhand von Fallstudien nachgewiesen wird