As our electric power distribution infrastructure has aged, considerable investment has been applied to modernizing the electrical power grid through weatherization and in deployment of real-time monitoring systems. A key question is whether or not these investments are reducing the number and duration of power outages, leading to improved reliability. Statistical methods are applied to analyze electrical disturbance data (from the Department of Energy, DOE) and reliability index data (from state utility public service commission regulators) to detect signs of improvement. The number of installed smart meters provided by several utilities is used to determine whether the number of smart meters correlate with a reduction in outage frequency. Indication emerged that the number of power outages may be decreasing over time. The magnitude of power loss has decreased from 2003 to 2007, and behaves cyclically from 2008 to 2014, with a few outlier points in both groups. The duration also appears to be decreasing between 2003-2014. Large blackout events exceeding 5 GW continue to be rare, and certain power outage events are seasonally dependent. There was a linear relationship between the number of customers and the magnitude of a power outage event. However, no relationship was found between the magnitude of power outages and time to restore power. The frequency of outages maybe decreasing as the number of installed smart meters has increased. Recommendations for inclusion of additional metrics, changes to formatting and semantics of datasets currently provided by federal and state regulators are made to help aid researchers in performing more effective analysis. Confounding variables and lack of information that has made the analysis diffcult is also discussed.

Indiana University-Purdue University Indianapolis (IUPUI) / The electrical disturbances in the power system have threatened the stability of the system. In the first step, it is necessary to detect these electrical disturbances or events. In the next step, a proper control should apply to the system to decrease the consequences of the disturbances. One-shot control is one of the effective methods for stabilizing the events. In this method, a proper amount of loads are increased or decreased to the electrical system. Determining the amounts of loads, and the location for shedding is crucial. Moreover, some control combinations are more effective for some events and less effective for some others. Therefore, this project is completed in two different sections. First, finding the effective control combinations, second, finding an algorithm for applying different control combinations to different contingencies in real-time. To find effective control combinations, sensitivity analysis is employed to locate the most effective loads in the system. Then to find the control combination commands, gradient descent, and PSO algorithm are used in this project. In the next step, a pattern recognition method is used to apply the appropriate control combination for every event. The decision tree is selected as the pattern recognition method. The three most effective control combinations found by sensitivity analysis and the PSO method are used in the remainder of this study. A decision tree is trained for each of the three control combinations, and their outputs are combined into an algorithm for selecting the best control in real-time. Finally, the algorithm is evaluated using a test set of contingencies. The final results reveal a 30\% improvement in comparison to the previous studies.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-05-11T18:00:15Z No. of bitstreams: 1 ederbarbozakapisch.pdf: 4847277 bytes, checksum: 139f0b67e25b637befdb231fd5402b98 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-05-17T15:19:44Z (GMT) No. of bitstreams: 1 ederbarbozakapisch.pdf: 4847277 bytes, checksum: 139f0b67e25b637befdb231fd5402b98 (MD5) / Made available in DSpace on 2017-05-17T15:19:44Z (GMT). No. of bitstreams: 1 ederbarbozakapisch.pdf: 4847277 bytes, checksum: 139f0b67e25b637befdb231fd5402b98 (MD5) Previous issue date: 2015-03-18 / CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico / A presente dissertação apresenta a implementação de um Sistema de Detecção e Compressão de Distúrbios Elétricos (SDCDE), com foco nas implementações baseadas em plataforma FPGA (Field-Programmable Gate Array). Inicialmente são abordados os algoritmos de compressão e detecção. Posteriormente são mostradas as sínteses na FPGA e um protótipo desenvolvido para testes. O sistema proposto é voltado para aplicações em Sistemas Elétricos de Potência (SEPs) e prevê a aquisição e o armazenamento dos distúrbios comumente encontrados nesse campo. A partir dos dados armazenados, é possível reconstruir inteiramente o sinal registrado, para possíveis análises de oscilográfia. O processo de compressão passa por três estágios: detecção de novidade, compressão com perdas, utilizando a Transformada Wavelet Discreta (DWT), e a Compressão em termos de bit. Esses três níveis de compressão permitem uma otimização do espaço de memória utilizado e garantem que longos períodos de registros possam ser armazenados em um cartão de memória. A abordagem das sínteses em FPGA visa avaliar, dentre outros fatores, o consumo de recursos de hardware utilizado, através da implementação de um processador embarcado, criado e idealizado para aplicações de Processamento Digital de Sinais (DSP). A partir do protótipo desenvolvido, alguns resultados de sínteses e estudos de casos com testes executados em ambientes reais, são apresentados. / This dissertation presents the implementation of a System of Detection and Compression of Electrical Disturbances (SDCDE), focusing on implementations based on FPGA platform (Field-Programmable Gate Array). Initially are discussed compression and detection algorithms. Subsequently the synthesis in FPGA and a prototype that was developed for testing are shown. The proposed system is aimed at applications in Electric Power Systems (SEPs) and provides for the acquisition and storage of the disturbances commonly found in this field. From the data stored, the recorded signal can be fully reconstructed for possible oscillographic analysis. The compression process involves three stages: novelty detection, lossy compression, using the Discrete Wavelet Transform (DWT), and a bit-level compression. These three levels of compression allow an optimization of used memory space and they ensure that long periods of records can be stored on a memory card. The approach of the synthesis on FPGA aims to evaluate, among other factors, the usage of hardware resources, through the implementation of an embedded processor, created and designed for digital signal processing applications. From the prototype developed, some results of synthesis and case studies with tests performed in real environments are presented.

Les énergies renouvelables, l’énergie sous la forme électrique et son transport à l’aide de réseaux électriques intelligents représentent aujourd’hui des enjeux majeurs car ils ont de grands impacts environnementaux et sociétaux. Ainsi, la production, le transport et la gestion de l’énergie électrique, continuent toujours à susciter un intérêt croissant. Pour atteindre ces objectifs, plusieurs verrous technologiques doivent être levés. Au-delà des questions liées aux architectures des réseaux électriques, aux modèles, aux outils de dimensionnement, à la formalisation de caractéristiques et d’indicateurs, aux contraintes et aux critères, à la gestion et à la production décentralisée, la qualité de la puissance électrique est centrale pour la fiabilité de l’ensemble du système de distribution. Les perturbations affectent la qualité des signaux électriques et peuvent provoquer des conséquences graves sur les autres équipements connectés au réseau. Les travaux de cette thèse s’inscrivent dans ce contexte et de fait ils sont orientés vers le développement de modèles, d’indicateurs et de méthodes de traitement des signaux dédiés à la surveillance en temps-réel des performances des réseaux de distribution électrique.Cette thèse analyse la qualité de la puissance électrique, en prenant en compte plusieurs caractéristiques bien connues ainsi que leur pertinence. Les modèles des systèmes électriques et les méthodes de traitement du signal pour estimer leurs paramètres sont étudiés pour des applications en temps-réel de surveillance, de diagnostic et de contrôle sous diverses conditions. Parmi tous, la fréquence fondamentale est l’un des paramètres les plus importants pour caractériser un système de distribution électrique. En effet, sa valeur qui est censée être une constante, varie en permanence et reflète la dynamique de l’énergie électrique disponible. La fréquence peut également être affectée par certaines productions d’énergie renouvelable et peut être influencée par des mauvaises synchronisations de certains équipements. En outre, la puissance absorbée par les charges ou produite par des sources est généralement différente d’une phase à l’autre. Évidemment, la plupart des installations électriques existantes avec plusieurs phases, qu’elles soient résidentielles ou industrielles, travaillent dans des conditions déséquilibrées. Identifier les composantes symétriques de tension est dans ce cas un moyen pertinent pour quantifier le déséquilibre entre les phases d’un système électrique.De nouvelles représentations de type espace d’état et modélisant des systèmes électriques sont proposées pour estimer la fréquence fondamentale et pour identifier les composantes symétriques de tension des systèmes électriques triphasés et déséquilibrés. Le premier modèle d’espace d’état proposé considère la fréquence fondamentale comme connue ou obtenue par un autre estimateur. En contrepartie, il fournit les autres paramètres caractérisant le système électrique. Un second modèle d’état-espace est introduit. Il est original dans le sens où il ne nécessite aucune connaissance de la fréquence fondamentale. Une de ses variables d’état est directement reliée à la fréquence et permet donc de la déduire. En outre, ce nouvel espace d’état est parfaitement capable de représenter des systèmes électriques à trois phases équilibrés et non équilibrés. [...] / Renewable energy, electricity and smart grids are core subjects as they have great environmental and societal impacts. Thus, generating, transporting and managing electric energy, i.e., power, still continue to drive a growing interest. In order to properly achieve these goals, several locks must be removed. Beyond issues related to the distribution architecture, the formalization of models, sizing tools, features and indicators, constraints and criteria, decentralized generation and energy management, power quality is central for the whole grid’s reliability. Disturbances affect the power quality and can cause serious impact on other equipment connected to the grid. The work of this thesis is part of this context and focuses on the development of models, indicators, and signal processing methods for power quality monitoring in time-varying power distribution systems.This thesis analyzes the power quality including several well-known features and their relevance. Power system models and signal processing methods for estimating their parameters are investigated for the purpose of real-time monitoring, diagnostic and control tasks under various operating conditions. Among all, the fundamental frequency is one of the most important parameters of a power distribution system. Indeed, its value which is supposed to be a constant varies continuously and reflects the dynamic availability of electric power. The fundamental frequency can also be affected by renewable energy generation and by nasty synchronization of some devices. Moreover, the power absorbed by loads or produced by sources is generally different from one phase to the other one. Obviously, most of the existing residential and industrial electrical installations with several phases work under unbalanced conditions. Identifying the symmetrical components is therefore an efficient way to quantify the imbalance between the phases of a grid. New state-space representations of power systems are proposed for estimating the fundamental frequency and for identifying the voltage symmetrical components of unbalanced three-phase power systems. A first state-space representation is developed by supposing the fundamental frequency to be known or to be calculated by another estimator. In return, it provides other parameters and characteristics from the power system. Another original state-space model is introduced which does not require the fundamental frequency. Here, one state variable is a function of the frequency which can thus be deduced. Furthermore this new state-space model is perfectly are able to represent a three-phase power system in both balanced and unbalanced conditions. This not the case of lots of existing models. The advantage of the proposed state-space representation is that it gives directly access to physical parameters of the system, like the frequency and the amplitude and phase values of the voltage symmetrical components. Power systems parameters can thus be estimated in real-time by using the new state-space with an online estimation process like an Extended Kalman Filter (EKF). The digital implementation of the proposed methods presents small computational requirement, elegant recursive properties, and optimal estimations with Gaussian error statistics.The methods have been implemented and validated through various tests respecting real technical constraints and operating conditions. The methods can be integrated in active power filtering schemes or load-frequency control strategies to monitor power systems and to compensate for electrical disturbances.