A Software-based Low-Jitter Servo Clock for Inexpensive Phasor Measurement Units

This paper presents the design and the implementation of a servo-clock (SC) for low-cost Phasor Measurement Units (PMUs). The SC relies on a classic Proportional Integral (PI) controller, which has been properly tuned to minimize the synchronization error due to the local oscillator triggering the on-board timer. The SC has been implemented into a PMU prototype developed within the OpenPMU project using a BeagleBone Black (BBB) board. The distinctive feature of the proposed solution is its ability to track an input Pulse-Per-Second (PPS) reference with good long-term stability and with no need for specific on-board synchronization circuitry. Indeed, the SC implementation relies only on one co-processor for real-time application and requires just an input PPS signal that could be distributed from a single substation clock

Smart Grid State Estimation with PMUs Time Synchronization Errors

We consider the problem of PMU-based state estimation combining information coming from ubiquitous power demand time series and only a limited number of PMUs. Conversely to recent literature in which synchrophasor devices are often assumed perfectly synchronized with the Coordinated Universal Time (UTC), we explicitly consider the presence of time-synchronization errors in the measurements due to different non-ideal causes such as imperfect satellite localization and internal clock inaccuracy. We propose a recursive Kalman-based algorithm which allows for the explicit offline computation of the expected performance and for the real-time compensation of possible frequency mismatches among different PMUs. Based on the IEEE C37.118.1 standard on PMUs, we test the proposed solution and compare it with alternative approaches on both synthetic data from the IEEE 123 node standard distribution feeder and real-field data from a small medium voltage distribution feeder located inside the EPFL campus in Lausanne.Comment: 10 page, 7 figure

Development and application of synchronized wide-area power grid measurement

Phasor measurement units (PMUs) provide an innovative technology for real-time monitoring of the operational state of entire power systems and significantly improve power grid dynamic observability. This dissertation focuses on development and application of synchronized power grid measurements. The contributions of this dissertation are as followed:First, a novel method for successive approximation register analog to digital converter control in PMUs is developed to compensate for the sampling time error caused by the division remainder between the desirable sampling rate and the oscillator frequency. A variable sampling interval control method is presented by interlacing two integers under a proposed criterion. The frequency of the onboard oscillator is monitored in using the PPS from GPS.Second, the prevalence of GPS signal loss (GSL) on PMUs is first investigated using real PMU data. The correlation between GSL and time, spatial location, solar activity are explored via comprehensive statistical analysis. Furthermore, the impact of GSL on phasor measurement accuracy has been studied via experiments. Several potential solutions to mitigate the impact of GSL on PMUs are discussed and compared.Third, PMU integrated the novel sensors are presented. First, two innovative designs for non-contact PMUs presented. Compared with conventional synchrophasors, non-contact PMUs are more flexible and have lower costs. Moreover, to address nonlinear issues in conventional CT and PT, an optical sensor is used for signal acquisition in PMU. This is the first time the utilization of an optical sensor in PMUs has ever been reported.Fourth, the development of power grid phasor measurement function on an Android based mobile device is developed. The proposed device has the advantages of flexibility, easy installation, lower cost, data visualization and built-in communication channels, compared with conventional PMUs.Fifth, an identification method combining a wavelet-based signature extraction and artificial neural network based machine learning, is presented to identify the location of unsourced measurements. Experiments at multiple geographic scales are performed to validate the effectiveness of the proposed method using ambient frequency measurements. Identification accuracy is presented and the factors that affect identification performance are discussed

Performance Improvement of Wide-Area-Monitoring-System (WAMS) and Applications Development

Wide area monitoring system (WAMS), as an application of situation awareness, provides essential information for power system monitoring, planning, operation, and control. To fully utilize WAMS in smart grid, it is important to investigate and improve its performance, and develop advanced applications based on the data from WAMS. In this dissertation, the work on improving the WAMS performance and developing advanced applications are introduced.To improve the performance of WAMS, the work includes investigation of the impacts of measurement error and the requirements of system based on WAMS, and the solutions. PMU is one of the main sensors for WAMS. The phasor and frequency estimation algorithms implemented highly influence the performance of PMUs, and therefore the WAMS. The algorithms of PMUs are reviewed in Chapter 2. To understand how the errors impact WAMS application, different applications are investigated in Chapter 3, and their requirements of accuracy are given. In chapter 4, the error model of PMUs are developed, regarding different parameters of input signals and PMU operation conditions. The factors influence of accuracy of PMUs are analyzed in Chapter 5, including both internal and external error sources. Specifically, the impacts of increase renewables are analyzed. Based on the analysis above, a novel PMU is developed in Chapter 6, including algorithm and realization. This PMU is able to provide high accurate and fast responding measurements during both steady and dynamic state. It is potential to improve the performance of WAMS. To improve the interoperability, the C37.118.2 based data communication protocol is curtailed and realized for single-phase distribution-level PMUs, which are presented in Chapter 7.WAMS-based applications are developed and introduced in Chapter 8-10. The first application is to use the spatial and temporal characterization of power system frequency for data authentication, location estimation and the detection of cyber-attack. The second application is to detect the GPS attack on the synchronized time interval. The third application is to detect the geomagnetically induced currents (GIC) resulted from GMD and EMP-E3. These applications, benefited from the novel PMU proposed in Chapter 6, can be used to enhance the security and robust of power system

On the calculation of time alignment errors in data management platforms for distribution grid data

The operation and planning of distribution grids require the joint processing of measurements from different grid locations. Since measurement devices in low- and medium-voltage grids lack precise clock synchronization, it is important for data management platforms of distribution system operators to be able to account for the impact of nonideal clocks on measurement data. This paper formally introduces a metric termed Additive Alignment Error to capture the impact of misaligned averaging intervals of electrical measurements. A trace-driven approach for retrieval of this metric would be computationally costly for measurement devices, and therefore, it requires an online estimation procedure in the data collection platform. To overcome the need of transmission of high-resolution measurement data, this paper proposes and assesses an extension of a Markov-modulated process to model electrical traces, from which a closed-form matrix analytic formula for the Additive Alignment Error is derived. A trace-driven assessment confirms the accuracy of the model-based approach. In addition, the paper describes practical settings where the model can be utilized in data management platforms with significant reductions in computational demands on measurement devices

Security Analysis of Phasor Measurement Units in Smart Grid Communication Infrastructures

Phasor Measurement Units (PMUs), or synchrophasors, are rapidly being deployed in the smart grid with the goal of measuring phasor quantities concurrently from wide area distribution substations. By utilizing GPS receivers, PMUs can take a wide area snapshot of power systems. Thus, the possibility of blackouts in the smart grid, the next generation power grid, will be reduced. As the main enabler of Wide Area Measurement Systems (WAMS), PMUs transmit measured values to Phasor Data Concentrators (PDCs) by the synchrophasor standard IEEE C37.118. IEC 61850 and IEC 62351 are the communication protocols for the substation automation system and the security standard for the communication protocol of IEC 61850, respectively. According to the aforementioned communication and security protocols, as well as the implementation constraints of different platforms, HMAC-SHA1 was suggested by the TC 57 WG group in October 2009. The hash-based Message Authentication Code (MAC) is an algorithm for verifying both message integrity and authentication by using an iterative hash function and a supplied secret key. There are a variety of security attacks on the PMU communications infrastructure. Timing Side Channel Attack (SCA) is one of these possible attacks. In this thesis, timing side channel vulnerability against execution time of the HMAC-SHA1 authentication algorithm is studied. Both linear and negative binomial regression are used to model some security features of the stored key, e.g., its length and Hamming weight. The goal is to reveal secret-related information based on leakage models. The results would mitigate the cryptanalysis process of an attacker. Adviser: Yi Qia

DFT-based Synchrophasor Estimation Algorithms and their Integration in Advanced Phasor Measurement Units for the Real-time Monitoring of Active Distribution Networks

The increasing penetration of Distributed Energy Resources (DERs) at the low and medium-voltage levels is determining major changes in the operational procedures of distribution networks (DNs) that are evolving from passive to active power grids. Such evolution is causing non-negligible problems to DN operators (DNOs) and calls for advanced monitoring infrastructures composed by distributed sensing devices capable of monitoring voltage and current variations in real-time. In this respect, Phasor Measurement Units (PMUs) definitely represent one of the most promising technologies. Their higher accuracy and reporting rates compared to standard monitoring devices, together with the possibility of reporting time-tagged measurements of voltage and current phasors, enable the possibility to obtain frequent and accurate snapshots of the status of the monitored grid. Nevertheless, the applicability of such technology to DNs has not been demonstrated yet since PMUs where originally conceived for transmission network applications. Within this context, this thesis first discusses and derives the requirements for PMUs expected to operate at power distribution level. This study is carried out by analyzing typical operating conditions of Active Distribution Networks (ADNs). Then, based on these considerations, an advanced synchrophasor estimation algorithm capable of matching the accuracy requirements of ADNs is formulated. The algorithm, called iterative-interpolated DFT (i-IpDFT) improves the performances of the Interpolated-DFT (IpDFT) method by iteratively compensating the effects of the spectral interference produced by the negative image of the spectrum and at the same time allows to reduce the window length up to two periods of a signal at the nominal frequency of the power system. In order to demonstrate the low computational complexity of such an approach, the developed algorithm has been subsequently optimized to be deployed into a dedicated FPGA-based PMU prototype. The influence of the PMU hardware components and particularly the effects of the stability and reliability of the adopted UTC-time synchronization technology have been verified. The PMU prototype has been metrologically characterized with respect to the previously defined operating conditions of ADNs using a dedicated PMU calibrator developed in collaboration with the Swiss Federal Institute of Metrology (METAS). The experimental validation has verified the PMU compliance with the class-P requirements defined in the IEEE Std. C37.118 and with most of the accuracy requirements defined for class-M PMUs with the exception of out of band interference tests

Design and Implementation of a Centralized Disturbance Detection System for Smart Microgrids

RÉSUMÉ L’excursion de fréquence et de tension sont parmi les défis nombreux qui se posent aux microréseaux. La détection des perturbations peut être effectuée par le système de surveillance centralisé de micro-réseaux qui utilise des données de synchrophasor rapportées à partir de différents noeuds. Les réseaux de communication de synchrophasor présentent des retards et des Pertes de paquets qui peuvent détériorer l’intégrité des données et donc compromettre la fiabilité des systèmes de surveillance et de contrôle des micro-réseaux intelligents. Ce mémoire présente un nouveau concentrateur de données de vecteurs de phase avancé (APDC) capable de contrer les manques de la communication et d’améliorer la qualité des ressources de la production décentralisée (DER) dans les micro-réseaux. L’APDC proposé utilise un système de compensation adaptatif pour obtenir une estimation efficace des éléments de données manquants. L’estimateur adaptatif utilise le taux de changement d’éléments de données pour choisir entre l’estimateur LMMSE et un estimateur basé sur les dérivés pour prédire les valeurs futures des éléments de données. Si, à un instant donné, les éléments de données synchrophasors de certaines unités de mesure de phasor (PMU) manquent, les valeurs estimées sont utilisées pour compenser les données manquantes. En outre, une unité de surveillance est proposée pour détecter de manière fiable les excursions en fréquence et identifier les DERs affectés par les îlotages. L’unité de surveillance utilise un algorithme de détection centralisé élaboré qui traite les données de fréquence pour distinguer entre l’îlotage possible des DERs et les perturbations du réseau de distribution. L’APDC proposé est développé sur la plate-forme OpenPDC en temps réel et sa performance est évaluée à l’aide d’une configuration expérimentale comprenant trois PMUs, un réseau de télécommunications, des interrupteurs, et un concentrateur de données de vecteurs de phase classique (PDC). Les résultats expérimentaux confirment une intégrité des données de haut niveau dans les conditions normales et perturbées des micro- réseaux. Des études sur l’effet du bruit de mesure montrent que l’APDC proposé est même efficace en présence de bruits sévères. De plus, une détection rapide et fiable des événements d’îlotage est obtenue en raison de l’amélioration considérable du temps de détection même en cas de pertes de données sévères et de bruit de mesure. Enfin, la performance de l’APDC proposé est comparée à une méthode d’estimation existante. Les résultats montrent l’avantage important de l’APDC, en particulier dans des conditions perturbées.----------ABSTRACT Microgrids are subject to various disturbances such as voltage transients and frequency excursions. Disturbance detection can be performed by a microgrid centralized monitoring system that employs synchrophasor data reported from different nodes within the microgrid. Synchrophasor communication networks exhibit delays and packet dropout that can undermine the data integrity and hence compromise the reliability of the monitoring and control systems of the smart microgrids. In this thesis, an advanced phasor data concentrators (APDC) is proposed that is capable of counteracting the communication impairments and improving the quality of monitoring of distributed energy resources (DERs) in microgrids. The proposed APDC utilizes an adaptive compensation scheme to achieve an efficient estimate of missing data elements. The adaptive estimator employs the rate of change of data elements to choose between the vector linear minimum mean square error (LMMSE) and the derivative-based estimators to predict the future values of data elements. Whenever the synchrophasor data elements of some phasor measurement units (PMU) are missing, the estimated values are used to compensate for the missing data. Moreover, a monitoring unit is proposed to reliably detect frequency excursions and identify the DERs affected by islanding events. The monitoring unit utilizes an elaborate centralized detection algorithm that processes frequency data to distinguish between possible islanding of DERs and disturbances occurred within the host grid. The proposed APDC is developed on a real-time OpenPDC platform and its performance is evaluated using an experimental setup including three PMUs, communication links, switches, and a conventional phasor data concentrator (PDC). The experimental results confirm a high-level data integrity under both normal and disturbed conditions. Studies on the effect of measurement noise show that the proposed APDC is even efficient in the presence of noise. Moreover, fast and reliable detection of islanding events is achieved even under severe data losses and measurement noise. Finally, the performance of the proposed APDC is compared with a recently proposed estimation method that shows the significant advantage of the APDC, especially under disturbed conditions