Recent major electrical disturbances highlight the extent to which modern societies depend on a reliable power infrastructure and the impact of these undesirable events on the economy and society. Numerous blackout models have been developed in the last decades that capture effectively the cascade mechanism leading to a partial or complete blackout. These models usually consider only the state of the electrical part of the system and investigate how failures or limitations in this system affect the probability and severity of a blackout.However, an analysis of the major disturbances that occurred during the last decade, such as the North America blackout of 2003 and the UCTE system disturbance of 2006, shows that failures or inadequacies in the Information and Communication Technology (ICT) infrastructure and also human errors had a significant impact on most of these blackouts.The aim of this thesis is to evaluate the contribution of these non-electrical events to the risk of power system blackouts. As the nature of these events is probabilistic and not deterministic, different probabilistic techniques have been developed to evaluate their impact on power systems reliability and operation.In particular, a method based on Monte Carlo simulation is proposed to assess the impact of an ICT failure on the operators’ situation awareness and consequently on their performance during an emergency. This thesis also describes a generic framework using Markov modeling for quantifying the impact of insufficient situation awareness on the probability of cascading electrical outages leading to a blackout. A procedure based on Markov modeling and fault tree analysis is also proposed for assessing the impact of ICT failures and human errors on the reliable operation of fast automatic protection actions, which are used to provide protection against fast-spreading electrical incidents. The impact of undesirable interactions and the uncoordinated operation of these protection schemes on power system reliability is also assessed in this thesis.The simulation results of these probabilistic methods show that a deterioration in the state of the ICT infrastructure and human errors affect significantly the probability and severity of power system blackouts. The conclusion of the work undertaken in this research is that failures in all the components of the power system, and not just the “heavy electrical” ones, must be considered when assessing the reliability of the electrical supply.

The diploma thesis deals with the assessment of the reliability of processes at the packaging center in the company CommScope Czech Republic s.r.o. The first part of the work is research about options for quality management using ISO 9000 standards, but also TQM approaches. At the same time, methods and analytical techniques are discussed, which will be further used in the practical part of this thesis. The following section introduces CommScope Inc. and its main product - optical fiber. The practical part contains an introduction to the packaging center and its processes, it also describes the analysis of the reliability of the original state and proposals for corrective measures that were designed within the Kaizen event. The rest of the work is then devoted to the implementation of the proposed changes and their economic assessment. Finally, an evaluation of the methods used, the results achieved and other recommendations are given.

In this paper, a new methodology is presented to estimate the lifetime impact of design changes, called Failure Likelihood Assessment (FLA). The discussion in this paper is on the fatigue lifetime prediction of axial piston units, especially after a design change. The demonstration object is an axial piston pump due to extreme environmental conditions and high specification demands, where the FLA is applied to a manufacturing change in an existing product and delivers an effect on the unit reliability. The resulted reliability imp rovement, if combined with typical calculation methods like Weibull analysis, delivers an increase in predicted lifetime considering the intended modification. As demonstration subje ct, a change of the manufacturing process of the cylinder block hub in an axial piston pump is used. The effect to the lifetime is predicted via the FLA-method and the results are calculated with test data and compared to theoretical results. The paper shows that the methodology delivers highly accurate results providing that the FLA is a powerful tool to analyze design changes as weil as new designs in regard to reliability and lifetime. The benefit for the user of this methodology will hence be more reliable products with optimized designs tobest fulfil customer's performance requirements.

No description available.

Разработан способ и программа для оценки исполнительных геодезических схем в камеральных условиях с целью обоснования принятия решения о необходимости проведения инструментального контроля планово-высотного положения строительных конструкций. / A method and program have been developed for evaluating executive geodetic schemes in office conditions in order to justify the decision on the need for instrumental control of the planned-altitude position of building structures.

[pt] Fontes renováveis são importantes recursos a serem agregados aos sistemas de energia elétrica em prol da descentralização da geração. Discussões acerca dos efeitos ambientais direcionam os estudos em busca de alternativas que possibilitem minimizar a emissão de gases poluentes e diversifiquem a matriz elétrica. Nesse contexto, a geração distribuída (GD) de natureza renovável vem se mostrando cada vez mais presente, alterando a estrutura clássica do sistema e conferindo um maior protagonismo do consumidor. Assim, torna-se essencial avaliar o desempenho dessas novas redes de distribuição no atendimento à demanda, de modo a estabelecer padrões adequados e monitorá-los através das agências reguladoras. Há uma diversidade de métodos de avaliação do desempenho dessas redes, principalmente através dos conceitos de confiabilidade, para lidar com as falhas de equipamentos e os efeitos decorrentes. A presente tese tem como objetivo avaliar índices de confiabilidade de sistemas de distribuição na presença de GD. Para isso, são apresentadas três técnicas baseadas em simulação Monte Carlo (SMC). Uma clássica, denominada SMC sequencial, tem como objetivo modelar a natureza cronológica do problema bem como as incertezas provenientes da intermitência de fontes de GD. A segunda, baseada na SMC quase sequencial, caracteriza-se por sua simplicidade e capacidade em manter a flexibilidade da SMC sequencial, porém, com melhor desempenho em termos de precisão e tempo de processamento. Por último, uma SMC baseada nos conceitos de transição de estado do sistema de forma cronológica assegura também precisão e flexibilidade à técnica. Novas funções teste são propostas para alcançar tal objetivo. Dois sistemas com inserção de GD são utilizados para avaliar o desempenho dos conceitos e técnicas propostas: IEEE RBTS, rede acadêmica padrão amplamente utilizada na área de confiabilidade; e uma rede real. A discussão exaustiva dos resultados confirma que as propostas cumprem os objetivos estabelecidos. / [en] Renewable sources are important resources to be added to electrical energy systems in favor of decentralized generation. Discussions about environmental effects drive the studies in search of alternatives that make it possible to minimize the emission of polluting gases and diversify the electrical matrix. In this context, distributed generation (DG) of a renewable nature has been increasingly present, changing the classic structure of the system and giving greater engagement to the consumer. Therefore, it is essential to evaluate the performance of these new distribution grids in meeting the power demand, in order to establish appropriate standards and monitor them through the regulatory agencies. There is a diversity of methods for evaluating the performance of these networks, mainly through reliability concepts, to deal with equipment failures and the resulting effects. This thesis aims to evaluate reliability indices of distribution systems in the presence of DG. To this end, three techniques based on Monte Carlo simulation (MCS) are presented. A classic one, called sequential MCS, aims at modeling the chronological nature of the problem as well as the uncertainties arising from the intermittency of the DG sources. The second one, based on a quasi-sequential MCS, is characterized by its simplicity and ability to maintain the flexibility of sequential MCS, but with better performance in terms of precision and processing time. Finally, an MCS based on the concepts of chronological system state transition, also provides precision and flexibility to the reliability assessment. New test functions are proposed to achieve this goal. Two systems with DG insertion are used to evaluate the performance of the proposed concepts and techniques: IEEE RBTS, a standard academic network widely used in the reliability area; and another real network. The exhaustive discussion of the results confirms that both proposals meet the established objectives.

Abstract The goal of this research is to advance the state of the art in bulk power system reliability assessment. Bulk power system reliability assessment is an important procedure at both power system planning and operating stages to assure reliable and acceptable electricity service to customers. With the increase in the complexity of modern power systems and advances in the power industry toward restructuring, the system models and algorithms of traditional reliability assessment techniques are becoming obsolete as they suffer from nonrealistic system models and slow convergence (even non-convergence) when multi-level contingencies are considered and the system is overstressed. To allow more rigor in system modeling and higher computational efficiency in reliability evaluation procedures, this research proposes an analytically-based security-constrained adequacy evaluation (SCAE) methodology that performs bulk power system reliability assessment. The SCAE methodology adopts a single-phase quadratized power flow (SPQPF) model as a basis and encompasses three main steps: (1) critical contingency selection, (2) effects analysis, and (3) reliability index computations. In the critical contingency selection, an improved contingency selection method is developed using a wind-chime contingency enumeration scheme and a performance index approach based on the system state linearization technique, which can rank critical contingencies with high accuracy and efficiency. In the effects analysis for selected critical contingencies, a non-divergent optimal quadratized power flow (NDOQPF) algorithm is developed to (1) incorporate major system operating practices, security constraints, and remedial actions in a constrained optimization problem and (2) guarantee convergence and provide a solution under all conditions. This algorithm is also capable of efficiently solving the ISO/RTO operational mode in deregulated power systems. Based on the results of the effects analysis, reliability indices that provide a quantitative indication of the system reliability level are computed. In addition, this research extends the proposed SCAE framework to include the effects of protection system hidden failures on bulk power system reliability. The overall SCAE methodology is implemented and applied to IEEE reliability test systems, and evaluation results demonstrate the expected features of proposed advanced techniques. Finally, the contributions of this research are summarized and recommendations for future research are proposed.

'Independent component analysis' (ICA) ist ein Werkzeug der statistischen Datenanalyse und Signalverarbeitung, welches multivariate Signale in ihre Quellkomponenten zerlegen kann. Obwohl das klassische ICA Modell sehr nützlich ist, gibt es viele Anwendungen, die Erweiterungen von ICA erfordern. In dieser Dissertation präsentieren wir neue Verfahren, die die Funktionalität von ICA erweitern: (1) Zuverlässigkeitsanalyse und Gruppierung von unabhängigen Komponenten durch Hinzufügen von Rauschen, (2) robuste und überbestimmte ('over-complete') ICA durch Ausreissererkennung, und (3) nichtlineare ICA mit Kernmethoden. / Independent component analysis (ICA) is a tool for statistical data analysis and signal processing that is able to decompose multivariate signals into their underlying source components. Although the classical ICA model is highly useful, there are many real-world applications that require powerful extensions of ICA. This thesis presents new methods that extend the functionality of ICA: (1) reliability and grouping of independent components with noise injection, (2) robust and overcomplete ICA with inlier detection, and (3) nonlinear ICA with kernel methods.

The theoretical part of this master thesis lists all the necessary prerequisites which are needed in order to carry out a full and comprehensive reliability assessment of any given process. To do so it provides an overview of reliability in general, mathematical and statistical guidance together with a more detailed picture of the application and description of the process by quantifiable indicators. Furthermore it gives an overview of two important analysis tools, such as FTA and FMEA, accompanied by the basic principle and summary of the Six Sigma methodology and tools. The practical part of the thesis deals with the detailed description, quantification and goals of the process of safety helmet manufacturing and testing in order to be able to carry out a suitable assessment of the reliability by using the necessary set of tools and methods in order to identify the failures and their causes in the process by addressing them with suitable means of changes and corrective actions.

[pt] Em geral, as subestações são projetadas com transformadores em paralelo, operando a meia carga, para assegurar continuidade no fornecimento de energia mesmo que um transformador do grupo falhe. Contudo, essa prática implica em custos elevados, especialmente no que diz respeito ao arranjo de subestações. Uma solução alternativa é a utilização de estoques compartilhados de transformadores reservas e unidades de subestações móveis, que devem atender a um grupo de subestações com as mesmas características elétricas. Neste contexto, esta tese propõe a utilização temporária de unidades de subestações móveis, que devem atuar para atender à demanda de energia enquanto o transformador reserva é instalado. Essa estratégia aumenta a confiabilidade do sistema e reduz os custos operacionais e de investimento para as concessionárias de energia. No entanto, o sucesso dessa abordagem está intrinsecamente ligado ao dimensionamento e localização adequada dos estoques. Para que bons resultados sejam alcançados, é preciso dimensionar os estoques de forma que não haja investimento desnecessário ou um número insuficiente de equipamentos, e considerar pontos estratégicos de armazenamento, de forma que o tempo de deslocamento dos equipamentos sobressalentes até o ponto de falha garanta a minimização dos custos associados. Posto isso, esta tese apresenta duas metodologias de otimização baseadas em simulação Monte Carlo e Algoritmo Genético: uma para dimensionar o número de transformadores reservas e unidades de subestações móveis por ano; e outra para posicionar de forma adequada tais equipamentos em subestações com capacidade de armazenamento. Ambos os métodos foram aplicados a um grupo de transformadores de duas concessionárias reais, visando demonstrar a capacidade da metodologia de encontrar um conjunto de soluções factíveis do ponto de vista técnico e econômico. / [en] In general, substations are designed with transformers in parallel, operating at half load, to ensure continuity of power supply even if a transformer in the group fails. However, this practice involves high costs, especially with regard to the arrangement of substations. An alternative solution is the use of shared stocks of reserve transformers and mobile substation units, which must serve a group of substations with the same electrical characteristics. In this context, this thesis proposes the temporary use of mobile substation units, which must act to meet the energy demand while the reserve transformer is installed. This strategy increases system reliability and reduces operational and investment costs for electric utilities. However, the success of this approach is intrinsically linked to the proper sizing and location of stocks. For good results to be achieved, it is necessary to size stocks so that there is no unnecessary investment or an insufficient number of equipment, and consider strategic storage points, so that the time taken to move the spare equipment to the point of failure minimizes the associated costs. Thus, this thesis presents two optimization methodologies based on Monte Carlo simulation and Genetic Algorithm: one to size the number of spare transformers and mobile substation units per year; and another to properly locate such equipment in substations with storage capacity. Both methods were applied to a group of transformers from two real utilities, aiming at proving the method s ability to find a set of feasible solutions from a technical and economic point of view.