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

Pregled različitih tehnologija upravljanja naprednim mrežama za povećanje fleksibilnosti elektroenergetskih sustava i omogućavanje masovne integracije obnovljivih izvora energije

Over the last 15 years, major changes have taken place in the electricity sector. A significant increase in the share of renewable energy sources (RES) with variable generation, followed by the decommissioning of conventional power plants based on fossil fuels, has dramatically changed the way of the power system (EPS) operation. During this time, there has been inadequate and untimely investment in the transmission infrastructure. This occurred partly due to the lack of funding, and partly due to the climate change and the rising environmental awareness, as well as the influence of green activists making it difficult to obtain permits to build electrical grid facilities. Additionally, electricity consumption is steadily increasing due to population growth in the undeveloped and developing countries, and due to the rising living standard in the developed countries. Therefore, global electricity consumption is expected to triple by 2050. To meet the new demands, Transmission System Operators (TSOs) are deploying advanced transmission technologies based on a comprehensive application of information and communication solutions. These technologies increase the capacity, efficiency, and reliability of both the existing and new elements of the transmission system. These solutions applied vary from system to system and depend on many influencing factors. The application of these advanced technologies is particularly important for congestion management, as the power system operates closer and closer to stability limits, increasing the risk of collapse. The paper describes the technologies that transform the existing network into smart grids, primarily from the point of view of increasing the capacity of the existing infrastructure through different smart grid investments.U posljednjih 15 godina u elektroenergetskom sektoru dogodile su se velike promjene. Značajno povećanje udjela obnovljivih izvora energije (OIE) s varijabilnom proizvodnjom, praćeno gašenjem konvencionalnih elektrana na fosilna goriva, dramatično je promijenilo način rada elektroenergetskog sustava (EES). Tijekom tog vremena bilo je neodgovarajućih i nepravovremenih ulaganja u prijenosnu infrastrukturu. To se dogodilo dijelom zbog nedostatka financijskih sredstava, a dijelom zbog klimatskih promjena i porasta ekološke svijesti, kao i utjecaja zelenih aktivista koji su otežali dobivanje dozvola za izgradnju energetskih objekata. Osim toga, potrošnja električne energije u stalnom je porastu zbog rasta stanovništva u nerazvijenim zemljama i zemljama u razvoju te zbog povećanja životnog standarda u razvijenim zemljama. Stoga se očekuje da će se globalna potrošnja električne energije utrostručiti do 2050. Kako bi zadovoljili nove zahtjeve, operatori prijenosnih sustava (TSO) uvode napredne tehnologije prijenosa temeljene na sveobuhvatnoj primjeni informacijskih i komunikacijskih rješenja. Ove tehnologije povećavaju kapacitet, učinkovitost i pouzdanost postojećih i novih elemenata prijenosnog sustava. Ova primijenjena rješenja razlikuju se od sustava do sustava i ovise o mnogim utjecajnim čimbenicima. Primjena ovih naprednih tehnologija posebno je važna za upravljanje zagušenjima jer elektroenergetski sustav radi sve bliže i bliže granicama stabilnosti, povećavajući rizik od njegovog sloma. U radu su opisane tehnologije koje transformiraju postojeću mrežu u napredne elektroenergetske mreže, prvenstveno sa stajališta povećanja kapaciteta postojeće infrastrukture kroz različite investicije u napredne tehnologije

Wireless synchronisation for low cost wireless sensor networks using DCF77

Wireless Sensor Networks (WSN) consist out of multiple end nodes containing sensors and one or more coordinator nodes which poll and command the end nodes. WSN can prove very efficient in distributed energy data acquisition, e.g. for phasor or power measurements. These types of measurements however require relatively tight synchronisation, which is sometimes difficult to achieve for low-cost WSN. This paper explores the possibility of a low-cost wireless synchronization system using the DCF77 long wave time signal to achieve sub-millisecond synchronisation accuracy. The results are compared to conventional GPS based synchronisation. As a practical example, the implementation of the described synchronisation method is proposed for a non-contact electrical phase identifier, which uses synchronised current measurements to distinguishing between the different phases in an unmarked electrical distribution grid

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

Robust Design of FACTS Wide-Area Damping Controller Considering Signal Delay for Stability Enhancement of Power System

制度:新 ; 報告番号:甲3426号 ; 学位の種類:博士(工学) ; 授与年月日:2011/9/15 ; 早大学位記番号:新575

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

Algorithms to Improve Performance of Wide Area Measurement Systems of Electric Power Systems

Power system operation has become increasingly complex due to high load growth and increasing market pressure. The occurrence of major blackouts in many power systems around the world has necessitated the use of synchrophasor based Wide Area Measurement Systems (WAMS) for grid monitoring. Synchrophasor technology is comparatively new in the area of power systems. Phasor measurement units (PMUs) and phasor data concentrators (PDCs) are new to the substations and control centers. Even though PMUs have been installed in many power grids, the number of installed PMUs is still low with respect to the number of buses or lines. Currently, WAMS systems face many challenges. This thesis is an attempt towards solving some of the technical problems faced by the WAMS systems. This thesis addresses four problems related to synchrophasor estimation, synchrophasor quality detection, synchrophasor communication and synchrophasor application. In the first part, a synchrophasor estimation algorithm has been proposed. The proposed algorithm is simple, requires lesser computations, and satisfies all the steady state and dynamic performance criteria of the IEEE Standard C37.118.1-2011 and also suitable for protection applications. The proposed algorithm performs satisfactorily during system faults and it has lower response time during larger disturbances. In the second part, areas of synchrophasor communication which can be improved by applying compressive sampling (CS) are identified. It is shown that CS can reduce bandwidth requirements for WAMS networks. It is also shown that CS can successfully reconstruct system dynamics at higher rates using synchrophasors reported at sub-Nyquist rate. Many synchrophasor applications are not designed to use fault/switching transient synchrophasors. In this thesis, an algorithm has been proposed to detect fault/switching transient synchrophasors. The proposed algorithm works satisfactorily during smaller and larger step changes, oscillations and missing data. Fault transient synchrophasors are not usable in WAMS applications as they represent a combination of fault and no-fault scenario. In the fourth part, two algorithms have been proposed to extract fault synchrophasor from fault transient synchrophasor in PDC. The proposed algorithms extract fault synchrophasors accurately in presence of noise, off-nominal frequencies, harmonics, and frequency estimation errors

On-line power system inertia calculation using wide area measurements

Future developments in power systems, e.g. relatively larger generator sets, the virtual power plant and synthetic inertia concept and connection of generation assets over inverters, will cause the system inertia to vary significantly. During system operation, if the inertia of the system is significantly lower than anticipated at the planning stage, then the existing, deterministic protection and control may fail to ensure system stability. Therefore, the ability to accurately determine the inertia of individual system areas, and the system as a whole, online would be very useful. In this paper, an Inertia Calculation Application (ICA), which could be implemented as part of a Wide Area Monitoring Protection and Control scheme, is presented. The necessary wide area measurements must be processed during large disturbances to the active power balance of the system. The ICA has been validated by using computer simulations, under laboratory conditions and by using real-life data recorded by a transmission system operator

Synchronized measurement data conditioning and real-time applications

Phasor measurement units (PMU), measuring voltage and current phasor with synchronized timestamps, is the fundamental component in wide-area monitoring systems (WAMS) and reveals complex dynamic behaviors of large power systems. The synchronized measurements collected from power grid may degrade due to many factors and impacts of the distorted synchronized measurement data are significant to WAMS. This dissertation focus on developing and improving applications with distorted synchronized measurements from power grid. The contributions of this dissertation are summarized below. In Chapter 2, synchronized frequency measurements of 13 power grids over the world, including both mainland and island systems, are retrieved from Frequency Monitoring Network (FNET/GridEye) and the statistical analysis of the typical power grids are presented. The probability functions of the power grid frequency based on the measurements are calculated and categorized. Developments of generation trip/load shedding and line outage events detection and localization based on high-density PMU measurements are investigated in Chapters 3 and 4 respectively. Four different types of abnormal synchronized measurements are identified from the PMU measurements of a power grid. The impacts of the abnormal synchronized measurements on generation trip/load shedding events detection and localization are evaluated. A line outage localization method based on power flow measurements is proposed to improve the accuracy of line outage events location estimation. A deep learning model is developed to detect abnormal synchronized measurements in Chapter 5. The performance of the model is evaluated with abnormal synchronized measurements from a power grid under normal operation status. Some types of abnormal synchronized measurements in the testing cases are recently observed and reported. An extensive study of hyper-parameters in the model is conducted and evaluation metrics of the model performance are presented. A non-contact synchronized measurements study using electric field strength is investigated in Chapter 6. The theoretical foundation and equation derivations are presented. The calculation process for a single circuit AC transmission line and a double circuit AC transmission line are derived. The derived method is implemented with Matlab and tested in simulation cases