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.

Alexander H. Levis [et al.]. / Prepared for Air Force [Office] of Scientific Research, Bolling Air Force Base, Washington, D.C. Contract AFOSR - 80-0229. / Description based on: July 1981/June 1982.

Orientador: Fernando de Azevedo Silva / Banca: Erick Siqueira Guidi / Banca: Rosinei Batista Ribeiro / Resumo: Esta dissertação tem como objetivo desenvolver uma ferramenta paramétrica em linguagem de programação de software ANSYS (linguagem APDL) para se calcular a estrutura de um pórtico rolante de vigas centrais e reduzir o tempo gasto em horas de cálculo. Neste trabalho primeiro são apresentados os principais tipos de equipamentos bem como os próprios pórticos rolantes e para estes últimos descreve quais são seus tipos e quais os componentes compõem sua estrutura Descreve sobre a parametrização em linguagem APDL, sobre as principais solicitações atuantes que devem ser levadas em consideração durante o dimensionamento da estrutura, de acordo com as especificações da norma NBR8400. Apresenta como foi desenvolvida a ferramenta, quais são suas interfaces com o operador e qual o esquema de operação da mesma. Ao final relata sobre o ganho na economia de tempo ao se utilizar o programa e analisa os resultados, de tensão e deslocamento, obtidos com a simulação de um modelo gerado / Abstract: This dissertation aims to develop a parametric tool in ANSYS software programming language (APDL language) to calculate the structure of a gantry crane of central beams and reduce the time spent in hours of calculation. This paper first presents the main types of equipment as well as the own gantry cranes, and for this latter describes what are their types and what components make up its structure. Describes about the parameterization in APDL language, about the main solicitations that should be taken into consideration during the dimensioning of the structure, according to the specifications of the standard NBR8400. Present show it was developed the tool, what are their interfaces with the operator and how it works. At the end relates about gaining in saving time when using the program and analyzes the results, of tension and displacement, obtained with the simulation of a generated model / Mestre

Made available in DSpace on 2015-07-13T12:10:08Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-02-13. Added 1 bitstream(s) on 2015-07-13T12:25:43Z : No. of bitstreams: 1 000832525.pdf: 2129764 bytes, checksum: d2af9e6ba5e35d31cc21884b21d7aa31 (MD5) / Esta dissertação tem como objetivo desenvolver uma ferramenta paramétrica em linguagem de programação de software ANSYS (linguagem APDL) para se calcular a estrutura de um pórtico rolante de vigas centrais e reduzir o tempo gasto em horas de cálculo. Neste trabalho primeiro são apresentados os principais tipos de equipamentos bem como os próprios pórticos rolantes e para estes últimos descreve quais são seus tipos e quais os componentes compõem sua estrutura Descreve sobre a parametrização em linguagem APDL, sobre as principais solicitações atuantes que devem ser levadas em consideração durante o dimensionamento da estrutura, de acordo com as especificações da norma NBR8400. Apresenta como foi desenvolvida a ferramenta, quais são suas interfaces com o operador e qual o esquema de operação da mesma. Ao final relata sobre o ganho na economia de tempo ao se utilizar o programa e analisa os resultados, de tensão e deslocamento, obtidos com a simulação de um modelo gerado / This dissertation aims to develop a parametric tool in ANSYS software programming language (APDL language) to calculate the structure of a gantry crane of central beams and reduce the time spent in hours of calculation. This paper first presents the main types of equipment as well as the own gantry cranes, and for this latter describes what are their types and what components make up its structure. Describes about the parameterization in APDL language, about the main solicitations that should be taken into consideration during the dimensioning of the structure, according to the specifications of the standard NBR8400. Present show it was developed the tool, what are their interfaces with the operator and how it works. At the end relates about gaining in saving time when using the program and analyzes the results, of tension and displacement, obtained with the simulation of a generated model

abstract: With the growing importance of underground power systems and the need for greater reliability of the power supply, cable monitoring and accurate fault location detection has become an increasingly important issue. The presence of inherent random fluctuations in power system signals can be used to extract valuable information about the condition of system equipment. One such component is the power cable, which is the primary focus of this research. This thesis investigates a unique methodology that allows online monitoring of an underground power cable. The methodology analyzes conventional power signals in the frequency domain to monitor the condition of a power cable. First, the proposed approach is analyzed theoretically with the help of mathematical computations. Frequency domain analysis techniques are then used to compute the power spectral density (PSD) of the system signals. The importance of inherent noise in the system, a key requirement of this methodology, is also explained. The behavior of resonant frequencies, which are unique to every system, are then analyzed under different system conditions with the help of mathematical expressions. Another important aspect of this methodology is its ability to accurately estimate cable fault location. The process is online and hence does not require the system to be disconnected from the grid. A single line to ground fault case is considered and the trend followed by the resonant frequencies for different fault positions is observed. The approach is initially explained using theoretical calculations followed by simulations in MATLAB/Simulink. The validity of this technique is proved by comparing the results obtained from theory and simulation to actual measurement data. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2016

Ao empregar a teoria de controle para a dinâmica de uma estrutura, é possível projetar um observador potencialmente complexo que a partir da leitura de apenas um sensor estime o estado do sistema e determine os modos de vibração presentes. Este trabalho, no entanto, estuda o uso de filtros modais em controle de vibrações, com a motivação de que essa estratégia dependa de menos componentes eletrônicos. O objetivo é encontrar um filtro modal que possua alto desempenho em malha fechada mesmo com um número reduzido de sensores. Primeiramente foi desenvolvido o modelo dinâmico do sistema em malha aberta, com posterior otimização do filtro modal por meio do método do ponto interior. Depois, foi desenvolvido o modelo dinâmico do sistema em malha fechada. A seguir, um algoritmo genético otimizou o sistema de controle de vibrações seguindo duas metodologias. A primeira considera apenas as posições dos sensores como variáveis de otimização, enquanto a segunda leva em consideração não só as posições dos sensores como também os ganhos do filtro modal e o ganho de retroalimentação de velocidade. Os resultados do estudo do sistema em malha aberta mostram que se trata se um problema de otimização não-convexa, mas todas as tentativas levaram a crer que o mínimo global tenha sido encontrado para a função objetivo proposta, baseada no desvio quadrático da função de resposta em frequência do filtro modal com relação a uma referência pré-estabelecida. Os resultados do estudo do sistema em malha fechada mostram que considerar as posições e os ganhos como variáveis de otimização levam a um filtro modal mais conveniente do que o que é obtido levando-se em consideração apenas as posições. Finalmente, a partir da interpretação dos resultados, conclui-se que mesmo com um filtro modal composto por 5 sensores é possível ainda desenvolver um sistema de controle de vibrações que seja de fase mínima. Apesar de existir spillover de observação do ponto de vista de um filtro modal, nota-se que todos os modos estão em fase, o que acaba por ser até benéfico para o sistema de controle de vibrações. / The control systems theory may be applied to structural dynamics in order to design a potentially complex observer which is able to estimate the system\'s state from the readings of a sole sensor. This work, though, focused on the application of modal filters in vibration control based on the premise that this strategy will require a simpler hardware. The main target consists of finding a modal filter which can deliver high performance in vibration control despite being composed of a reduced number of sensors. In the first step, a dynamic model of a modal filter on a cantilever beam was developed, followed by an optimization carried on with the interior-point method. Then, the dynamic model of the closed-loop cantilever beam was developed aftwerwards. However, this time a genetic algorithm was used as the optimization method instead, with two methodologies being employed. While the first one considered only the placement of the sensors, the second one also takes into consideration the modal filter gains and the negative velocity feedback gain. The results yielded by the open-loop cantilever beam analysis showed that it is a non-convex optimization problem. However, all of the attempts support the belief that the global minimum has been found in the sense of the proposed objective function, which was based on the quadratic error between the frequency response function (FRF) of the modal filter and an idealized FRF used as reference. The results yielded by the closed-loop system optimization showed that it is more convenient to consider as optimization variables not only the placement of the sensors, but also their gains and the negative velocity feedback gain. Finally, after pondering over the obtained results, it has been concluded that the observation spillover resulting from a modal filter composed of a reduced number of sensors may be turned to the vibration control system\'s favour by means of optimization. The minimal-phase modal filter composed of 5 sensors found in this work stands out as the most notable example in this work, being able to guarantee stability for the first 12 modes since all of them are in-phase.

Identifying the parameters with the largest influence on the predicted outputs of a model revealswhich parameters need to be known more precisely to reduce the overall uncertainty on themodel output. A large improvement of such models would result when uncertainties in the keymodel parameters are reduced. To achieve this, new experiments could be very helpful,especially if the measurements are taken at the spatio-temporal locations that allow estimate the parameters in an optimal way. After evaluating the methodologies available for optimal sensor location, a few observations were drawn. The method based on the Gram determinant evolution can report results not according to what should be expected. This method is strongly dependent of the sensitivity coefficients behaviour. The approach based on the maximum angle between subspaces, in some cases, produced more that one optimal solution. It was observed that this method depends on the magnitude of outputs values and report the measurement positions where the outputs reached their extrema values. The D-optimal design method produces number and locations of the optimal measurements and it depends strongly of the sensitivity coefficients, but mostly of their behaviours. In general it was observed that the measurements should be taken at the locations where the extrema values (sensitivity coefficients, POD modes and/or outputs values) are reached. Further improvements can be obtained when a reduced model of the system is employed. This is computationally less expensive and the best estimation of the parameter is obtained, even with experimental data contaminated with noise. A new approach to calculate the time coefficients belonging to an empirical approximator based on the POD-modes derived from experimental data is introduced. Additionally, an artificial neural network can be used to calculate the derivatives but only for systems without complex nonlinear behaviour. The latter two approximations are very valuable and useful especially if the model of the system is unknown.

Infinite-Dimensional Systems (IDSs) which have been made possible by recent advances in mathematical and computational tools can be used to model complex real phenomena. However, due to physical, economic, or stringent non-invasive constraints on real systems, the underlying characteristics for mathematical models in general (and IDSs in particular) are often missing or subject to uncertainty. Therefore, developing efficient estimation techniques to extract missing pieces of information from available measurements is essential. The human brain is an example of IDSs with severe constraints on information collection from controlled experiments and invasive sensors. Investigating the intriguing modeling potential of the brain is, in fact, the main motivation for this work. Here, we will characterize the hemodynamic behavior of the brain using functional magnetic resonance imaging data. In this regard, we propose efficient estimation methods for two classes of IDSs, namely Partial Differential Equations (PDEs) and Fractional Differential Equations (FDEs). This work is divided into two parts. The first part addresses the joint estimation problem of the state, parameters, and input for a coupled second-order hyperbolic PDE and an infinite-dimensional ordinary differential equation using sampled-in-space measurements. Two estimation techniques are proposed: a Kalman-based algorithm that relies on a reduced finite-dimensional model of the IDS, and an infinite-dimensional adaptive estimator whose convergence proof is based on the Lyapunov approach. We study and discuss the identifiability of the unknown variables for both cases. The second part contributes to the development of estimation methods for FDEs where major challenges arise in estimating fractional differentiation orders and non-smooth pointwise inputs. First, we propose a fractional high-order sliding mode observer to jointly estimate the pseudo-state and input of commensurate FDEs. Second, we propose a modulating function-based algorithm for the joint estimation of the parameters and fractional differentiation orders of non-commensurate FDEs. Sufficient conditions ensuring the local convergence of the proposed algorithm are provided. Subsequently, we extend the latter technique to estimate smooth and non-smooth pointwise inputs. The performance of the proposed estimation techniques is illustrated on a neurovascular-hemodynamic response model. However, the formulations are efficiently generic to be applied to a wide set of additional applications.

The studies in this dissertation address the issue of variability in runoff generation and pollutant concentration in urban areas, and specifically in the catchments of stormwater control measures. There is an imperfect correlation between runoff volumes and the capture area and land uses of urban catchments. Variable capture areas and uncertainty in urban runoff sources complicate stormwater control measure design and urban stream assessment. Four stormwater control measures in upstream suburban Philadelphia, ranging in capture area from 0.11 ha to 32 ha, were monitored, sampled, and modeled. Sampling was conducted in the watersheds of Wissahickon Creek, Tookany Creek, and Pennypack Creek. The approaches discussed below have the goal of better understanding runoff and the movement of associated contaminants into stormwater retention basins and streams. Rather than viewing runoff generation and contaminant transport as a static process, this work proposes that the amount of runoff contributed from different areas of a catchment changes during and between storm events, and that the origin and concentration of contaminants change as a result. Linking source areas to runoff volumes through natural and modeled tracers could improve predictions of water quality and quantity in stormwater control measures in urban streams. Nitrate (NO3–) isotope ratios were used as tracer of flow from different urban land uses. Time series samples of stormwater runoff entering two stormwater control measures (a constructed wetland and a small bioretention basin) were collected and analyzed to distinguish sources of NO3– by samples’ δ15N and δ18O ratios. A Bayesian mixing model was used to determine that NO3– sources were a mix of soil nitrogen (N) and atmospheric deposition across six storm events. Furthermore, atmospheric versus soil N sources varied throughout the storms. The large catchment of the constructed wetland had more NO3– source variability between samples compared to the small catchment of the bioretention basin. Thus, the NO3– isotopes suggest more distinct flow paths in the large catchment and more mixing of flow across land uses in the small catchment. Quantifying flow path variability from storm to storm and between different catchments can improve design and placement of urban stormwater control measures. A distributed hydrologic model, GSSHA, was used to simulate overland runoff from impervious and semi-pervious land covers in the catchment of a stormwater control measure. The positions of low vegetation and impervious land uses over the catchment were rearranged to create hypothetical catchments during four storm events. Fluctuating source proportions over time suggested that grab samples might not be adequate for capturing average overland runoff chemistry. It was also found that the portion of total runoff volume from impervious areas varied from 50 to 75% while the relative proportion of impervious cover remained constant at 54%. Land use percentages averaged over capture areas are frequently used to estimate runoff amounts and pollutant concentrations, but this model disrupts the assumption that urban hydrologic responses can be predicted from imperviousness alone. Overland runoff was measured and modeled before and after the installation of two stormwater control measures, a berm and a bioswale. Discharge in the stream was modeled for 9 storms ranging in size from 14 to 54 mm. We found that during 4 of the modeled storms there was no decrease in stream discharge and decreases in discharge were generally only observed for low intensity storms. Furthermore, only 5% of the stream catchment was captured by SCMs. Modeled tracers, used to track runoff contributions from areas upslope of the SCMs found that the size of upslope contributing areas did not predict the proportion of runoff generated in each area. Field data to support the models included water level loggers and samples of overland runoff collected in subsurface stormwater casing. After the SCMs were installed, less water was captured in downslope sampling bottles, but new flow paths developed. Furthermore, significant variation was observed in upslope concentrations of dissolved nutrients and total suspended solids, casting doubt on whether point samples of urban overland runoff geochemistry can be representative given variable runoff generation and heterogeneous land uses. This study points out the challenges in evaluating stormwater control measures and reveals that source areas’ contribution to stream flow varies independently of their size. Therefore, modeling before stormwater control measure installation is recommended to determine the factors that influence a capture area’s contribution to urban streamflow. / Geoscience

There is often freedom in choosing the location of actuators on systems governed by partial differential equations. The actuator locations should be selected in order to optimize the performance criterion of interest. The main focus of this thesis is to consider H-∞-performance with state-feedback. That is, both the controller and the actuator locations are chosen to minimize the effect of disturbances on the output of a full-information plant. Optimal H-∞-disturbance attenuation as a function of actuator location is used as the cost function. It is shown that the corresponding actuator location problem is well-posed. In practice, approximations are used to determine the optimal actuator location. Conditions for the convergence of optimal performance and the corresponding actuator location to the exact performance and location are provided. Examples are provided to illustrate that convergence may fail when these conditions are not satisfied. Systems of large model order arise in a number of situations; including approximation of partial differential equation models and power systems. The system descriptions are sparse when given in descriptor form but not when converted to standard first-order form. Numerical calculation of H-∞-attenuation involves iteratively solving large H-∞-algebraic Riccati equations (H-∞-AREs) given in the descriptor form. An iterative algorithm that preserves the sparsity of the system description to calculate the solutions of large H-∞-AREs is proposed. It is shown that the performance of our proposed algorithm is similar to a Schur method in many cases. However, on several examples, our algorithm is both faster and more accurate than other methods. The calculation of H-∞-optimal actuator locations is an additional layer of optimization over the calculation of optimal attenuation. An optimization algorithm to calculate H-∞-optimal actuator locations using a derivative-free method is proposed. The results are illustrated using several examples motivated by partial differential equation models that arise in control of vibration and diffusion.