Este trabalho tem por objetivo apresentar o desenvolvimento e a implementação, em uma rotina computacional, de um algoritmo para localização de faltas em linhas de transmissão com compensação série baseado em método heurístico. O algoritmo de localização de faltas proposto neste trabalho é capaz de identificar o ponto de ocorrência da falta utilizando informações sobre os parâmetros da linha de transmissão, os sinais de tensões e correntes registrados nos terminais dessa linha, bem como as características das unidades de compensação série empregadas. O algoritmo desenvolvido no âmbito desta pesquisa foi codificado no ambiente Matrix Laboratory (MATLAB), bem como o método heurístico escolhido (pattern search) e a sua validação foi conduzida a partir de simulações computacionais utilizando modelos de rede implementados no Alternate Transient Program (ATP). / This work aims to describe the development and implementation in a computational routine, an algorithm to locate faults in series-compensated transmission lines based on an heuristic method. The fault location algorithm proposed in this work is capable of identifying the fault point using information about the parameters of the transmission line, voltages and currents signals recorded at the line terminals, as well as the characteristics of the series compensation units. The optimization method used for objective functions was pattern search. The algorithm developed during this research was coded using MATLAB, as well as the heuristic method chosen (pattern search) and its validation was based on computer simulations using network models implemented in ATP.

Orientador: José Alfredo Covolan Ulson / Banca: Rogério Andrade Flauzino / Banca: Mario Eduardo Bordon / Resumo: O sistema de distribuiçã de energia elétrica no Brasil é constituído, na grande maioria, de alimentadores aéreos na classe 15 kV sujeitos a muitos tipos de defeitos. Embora existam muitos trabalhos propondo técnicas para a identificação e a localização das faltas, a maioria deles foi desenvolvida objetivando as redes de transmissão pouco ramificadas. Em se tratando de redes muito ramificadas e extensas, características princiapais de redes de distribuição elétrica, esses métodos não apresentam alta confiabilidade e segurança em termos de detecção, dificultando a localização das faltas. Este trabalho tem como objetivo descrever o desenvolvimento de um sistema de medição de baixo custo voltado para a monitoração de alimentadores aéreosm de distribuição de energia elétrica, que possibilite a identificação e a localização de faltas bem como a avaliação da qualidade da energia elétrica fornecida. Para tal, uma rede de sensores sem fio no padrão IEEE 802.15.4 é utilizada para adquirir os dados de tensão e corrente de cada frase e, a partir do processamento dessas informações, possibilitar a identificação de um ramal sob falta e a determinação do seu tipo. Com a instação de mediadores em pontos onde a rede de distribuição se ramifica, o ramal sob falta pode ser localizado, reduzindo assim o tempo de desligamento e os custos de manutenção / Abstract: The system of eletrecity distribution in Brazil is made mostly of air handlers in the class 15 kV, subject to many kinds of defects. Although there are many papers proposing techniques for the identification and location of faults, most of them were developed aiming at the broadcast networks little branched. In terms of networks very extensive and branched, like in distribution networks, these methods have low reliability and safety in terms of detection, makind the location of faults difficult. This paper aims to describe the development of a measurment system focused on low-cost monitoring of overhead distribution feeders of electricity, allowing for the identification and location of faults and the quality of power supplied. For this purpose, a network of wireless sensors on the IEEE 208.15.4 is used for data acquisition of each phase voltage and current and from the processing of such information is possible to determine a faulted extension and identification of its type. With the installation of meters at points where the distribution networks branches, the faulted extension can be located, thereby reducing the shutdown time and maintenance costs / Mestre

The emergence of complex and autonomous systems, such as modern aircraft, unmanned aerial vehicles (UAVs) and automated industrial processes is driving the development and implementation of new control technologies aimed at accommodating incipient failures to maintain system operation during an emergency. The motivation for this research began in the area of avionics and flight control systems for the purpose to improve aircraft safety. A prognostics health management (PHM) based fault-tolerant control architecture can increase safety and reliability by detecting and accommodating impending failures thereby minimizing the occurrence of unexpected, costly and possibly life-threatening mission failures; reduce unnecessary maintenance actions; and extend system availability / reliability. Recent developments in failure prognosis and fault tolerant control (FTC) provide a basis for a prognosis based reconfigurable control framework. Key work in this area considers: (1) long-term lifetime predictions as a design constraint using optimal control; (2) the use of model predictive control to retrofit existing controllers with real-time fault detection and diagnosis routines; (3) hybrid hierarchical approaches to FTC taking advantage of control reconfiguration at multiple levels, or layers, enabling the possibility of set-point reconfiguration, system restructuring and path / mission re-planning. Combining these control elements in a hierarchical structure allows for the development of a comprehensive framework for prognosis based FTC. First, the PHM-based reconfigurable controls framework presented in this thesis is given as one approach to a much larger hierarchical control scheme. This begins with a brief overview of a much broader three-tier hierarchical control architecture defined as having three layers: supervisory, intermediate, and low-level. The supervisory layer manages high-level objectives. The intermediate layer redistributes component loads among multiple sub-systems. The low-level layer reconfigures the set-points used by the local production controller thereby trading-off system performance for an increase in remaining useful life (RUL). Next, a low-level reconfigurable controller is defined as a time-varying multi-objective criterion function and appropriate constraints to determine optimal set-point reconfiguration. A set of necessary conditions are established to ensure the stability and boundedness of the composite system. In addition, the error bounds corresponding to long-term state-space prediction are examined. From these error bounds, the point estimate and corresponding uncertainty boundaries for the RUL estimate can be obtained. Also, the computational efficiency of the controller is examined by using the number of average floating point operations per iteration as a standard metric of comparison. Finally, results are obtained for an avionics grade triplex-redundant electro-mechanical actuator with a specific fault mode; insulation breakdown between winding turns in a brushless DC motor is used as a test case for the fault-mode. A prognostic model is developed relating motor operating conditions to RUL. Standard metrics for determining the feasibility of RUL reconfiguration are defined and used to study the performance of the reconfigured system; more specifically, the effects of the prediction horizon, model uncertainty, operating conditions and load disturbance on the RUL during reconfiguration are simulated using MATLAB and Simulink. Contributions of this work include defining a control architecture, proving stability and boundedness, deriving the control algorithm and demonstrating feasibility with an example.

The focus of this research is on identification, location, interruption, characterization and overall management of faults in conventional AC distribution systems as well as isolated MVDC power systems. The primary focus in AC distributions systems is on identifying and locating underground cable faults using voltage and current waveforms as the input data. Cable failure process is gradual and is characterized by a series of single-phase sub-cycle incipient faults with high arc voltage. They often go undetected and eventually result in a permanent fault in the same phase. In order to locate such incipient cable faults, a robust yet practical algorithm is developed taking into account the fault arc voltage. The algorithm is implemented in the time-domain and utilizes power quality monitor data to estimate the distance to the fault in terms of the line impedance. It can be applied to locate both sub-cycle as well as permanent faults. The proposed algorithm is evaluated and proved out using field data collected from utility distribution circuits. Furthermore, this algorithm is extended to locate evolving faults on overhead distribution lines. Evolving faults are faults beginning in one phase of a distribution circuit and spreading to another phase after a few cycles. The algorithm is divided into two parts, namely, the single line-to-ground portion of the fault and the line-to-line-to-ground portion of the fault. For the single line-to-ground portion of the fault, the distance to the fault is estimated in terms of the loop or self-reactance between the monitor and the fault. On the other hand, for the line-to-line-to-ground and line-to-line portion of the fault the distance is estimated in terms of the positive-sequence reactance. The secondary focus of fault management in AC distribution systems is on identifying fault cause employing voltage and current waveform data as well as meteorological information. As the first step, unique characteristics of cable faults are examined along with methods to identify such faults with suitable accuracy. These characteristics are also used to distinguish underground cable faults from other overhead distribution line faults. The overhead line faults include tree contact, animal contact and lightning induced faults. Waveform signature analysis, wavelet transforms and arc voltages during the fault event are used for fault cause identification and classification. A statistical based classification methodology to identify fault cause is developed by utilizing promising characteristics. Unlike the AC system infrastructure which is already in place, the DC system considered in this document is that of a notional electric ship. The nature of DC current, with the absence of a current zero as well as the presence of power electronic devices influencing the current behavior, makes interrupting DC fault currents challenging. As a part of this research an innovative DC fault interruption scheme is proposed for rectifier- fed MVDC systems. A fault at the terminals of a phase-controlled rectifier results in a high magnitude current impulse caused by the filter capacitor discharging into the fault resistance. It is proposed to use a series inductor to limit the magnitude of this current impulse. The addition of the inductor results in an underdamped series RLC circuit at the output terminals of the rectifier which causes the fault current to oscillate about zero. Furthermore, it is proposed to utilize a conventional AC circuit breaker to interrupt this fault current by exploiting the zero crossings resulting from the oscillations. Using the proposed scheme for the example case, the peak fault current magnitude as well as the interruption time is significantly reduced. / text

M. Tech. Electrical Engineering / Investigates the reasons behind the poor performance of distance relays on series compensated lines. In order to achieve this objective, a case study will be established in a power system software (DigSilent Power Factory). Furthermore, a practical incident that occurred on Eskom's compensated network will be examined. However, prior to investigating the performance of the distance relay on transmission lines, there are some other critical aspects that have to be thoroughly understood. These aspects include amongst others: transmission line modelling ; numeric relay algorithms ; distance protection philosophies ; series compensation phenomena ; analysis of distance relays performance on both compensated and uncompensated lines and the action and influence of the MOV. The study will provide a better understanding regarding the dynamic behaviour of the impedance protection relay under fault conditions on series compensated lines and the behaviour of the MOV during a fault.

M. Tech. Electrical Engineering. / This dissertation presents an effective method to determine current/voltage harmonic emission levels caused by various devices in the network. The method is implemented based on the existing power monitoring devices installed in power generation plants. The Digital Fault Recorders (DFRs) are used in this work as the monitoring devices. Due to the advancement of data processing and communication capabilities of such devices, a large amount of information generated by DFRs is concentrated in the utilitys head office. This data is archived for permanent storage and analysis. The presented work aims to assist the power utilities in harmonic invigilation problems based on DFRs.

Electric power systems have been in existence for over a century. Electric power transmission line systems play an important role in carrying electrical power to customers everywhere. The number of transmission lines in power systems is increasing as global demand for power has increased. Parallel transmission lines are widely used in the modern transmission system for higher reliability. The parallel lines method has economic and environmental advantages over single circuit. A fault that occurs on a power transmission line will cause long outage time if the fault location is not located as quickly as possible. The faster the fault location is found, the sooner the system can be restored and outage time can be reduced. The main focus of this research is to develop a new accurate fault location algorithm for parallel transmission lines to identify the fault location for long double-circuit transmission lines, taking into consideration mutual coupling impedance, mutual coupling admittance, and shunt capacitance of the line. In this research, the equivalent PI circuit based on a distributed parameter line model for positive, negative, and zero sequence networks have been constructed for system analysis during the fault. The new method uses only the voltage and current from one end of parallel lines to calculate the fault distance. This research approaches the problem by derivation all equations from positive sequence, negative sequence, and zero sequence network by using KVL and KCL. Then, the fault location is obtained by solving these equations. EMTP has been utilized to generate fault cases under various fault conditions with different fault locations, fault types and fault resistances. Then the algorithm is evaluated using the simulated data. The results have shown that the developed algorithm can achieve highly accurate estimates and is promising for practical applications.

This research develops a fault diagnosis method for complex systems in the presence of uncertainties and possibility of multiple solutions. Fault diagnosis is a challenging problem because data used in diagnosis contain random errors and often systematic errors as well. Furthermore, fault diagnosis is basically an inverse problem so that it inherits unfavorable characteristics of inverse problems: The existence and uniqueness of an inverse solution are not guaranteed and the solution may be unstable. The weighted least squares method and its variations are traditionally used for solving inverse problems. However, the existing algorithms often fail to identify multiple solutions if they are present. In addition, the existing algorithms are not capable of selecting variables systematically so that they generally use the full model in which may contain unnecessary variables as well as necessary variables. Ignoring this model uncertainty often gives rise to, so called, the smearing effect in solutions, because of which unnecessary variables are overestimated and necessary variables are underestimated. The proposed method solves the inverse problem using Bayesian inference. An engineering system can be parameterized using state variables. The probability of each state variable is inferred from observations made on the system. A bias in an observation is treated as a variable, and the probability of the bias variable is inferred as well. To take the uncertainty of model structure into account, multiple Bayesian models are created with various combinations of the state variables and the bias variables. The results from all models are averaged according to how likely each model is. Gibbs sampling is used for approximating updated probabilities. The method is demonstrated for two applications: the status matching of a turbojet engine and the fault diagnosis of an industrial gas turbine. In the status matching application only physical faults in the components of a turbojet engine are considered whereas in the fault diagnosis application sensor biases are considered as well as physical faults. The proposed method is tested in various faulty conditions using simulated measurements. Results show that the proposed method identifies physical faults and sensor biases simultaneously. It is also demonstrated that multiple solutions can be identified. Overall, there is a clear improvement in ability to identify correct solutions over the full model that contains all state and bias variables.

This dissertation presents a model-based reasoning architecture with a two fold purpose: to detect and classify component faults from observable system behavior, and to generate fault propagation models so as to make a more accurate estimation of current operational risks. It incorporates a novel approach to system level diagnostics by addressing the need to reason about low-level inaccessible components from observable high-level system behavior. In the field of complex system maintenance it can be invaluable as an aid to human operators. The first step is the compilation of the database of functional descriptions and associated fault-specific features for each of the system components. The system is then analyzed to extract structural information, which, in addition to the functional database, is used to create the structural and functional models. A fault-symptom matrix is constructed from the functional model and the features database. The fault threshold levels for these symptoms are founded on the nominal baseline data. Based on the fault-symptom matrix and these thresholds, a diagnostic decision tree is formulated in order to intelligently query about the system health. For each faulty candidate, a fault propagation tree is generated from the structural model. Finally, the overall system health status report includes both the faulty components and the associated at risk components, as predicted by the fault propagation model.

Thesis (Ph. D.)--Missouri University of Science and Technology, 2008. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed May 27, 2008) Includes bibliographical references.