Este trabalho propõe uma avaliação quantitativa do efeito do desequilíbrio nos índices de operação do sistema de distribuição de energia elétrica. Os cenários apresentados contemplam os desequilíbrios existentes nos circuitos de média tensão e, também, os desequilíbrios na carga. Os desequilíbrios da rede consideram os efeitos da assimetria dos circuitos que provocam acoplamentos diferenciados entre os condutores. Para tanto, foram empregados dois sistemas, sendo um deles teórico e constituído por apenas um circuito e outro uma rede de distribuição padrão do IEEE. A primeira etapa da avaliação é realizada utilizando um modelo que reproduz um trecho fictício de linha de distribuição aérea trifásica com geometria e condutores típicos de redes de distribuição de energia de média tensão a cinco condutores, sendo um deles o condutor fictício de retorno pela terra. Os desequilíbrios de carga foram gerados aleatoriamente através do método de Monte Carlo, considerando variados índices de desequilíbrio. O desequilíbrio das correntes e as perdas do sistema foram determinados com o objetivo de quantificar o impacto das variações realizadas no trecho de linha. Para o sistema teste IEEE 34 Node Test Feeder, foram avaliados os erros decorrentes da consideração do acoplamento médio no cálculo das perdas de potência ativa e reativa, bem como os desequilíbrios de corrente, com o uso do software OpenDSS. Chega-se à conclusão de que o modelo que considera o acoplamento médio é capaz de determinar com muita fidelidade o desequilíbrio das correntes e das perdas para um circuito típico de distribuição em média tensão, não sendo necessária a representação exata das assimetrias dos condutores. / This Master Thesis proposes a quantitative evaluation of the effect of unbalance in the operational indexes of distribution networks. The scenarios comprehend the unbalance of medium voltage circuits and the unbalance in the load. The unbalances consider the effects of the asymmetry of circuits, that cause different couplings between the conductors. Therefore, two systems were implemented, one theoretical and the other a distribution network following the IEEE standard. The first stage of the evaluation is performed using a model that reproduces a fictitious section of a three-phase aerial distribution power line with five conductors considering earth return path, with geometry and typical conductors used in medium voltage energy distribution. The load unbalances were randomly produced using the Monte Carlo method, considering different unbalance rates. The current unbalance factor and the system losses were determined to quantify the impact of the variations in the line section. For the IEEE 34 Node Test Feeder system, the errors from considering the average coupling in the calculation of active and reactive power losses were evaluated, as well as the current unbalance factor. In conclusion, the model that considers the average coupling can successfully determine with a high degree of accuracy the imbalance of currents and the losses for a typical medium-voltage distribution circuit without the need of an exact representation of the asymmetries of the conductors.

Made available in DSpace on 2017-07-21T14:19:33Z (GMT). No. of bitstreams: 1 AlisonWeber.pdf: 1901250 bytes, checksum: c554c4802feb0647c03048f60b92b2a9 (MD5) Previous issue date: 2012-08-01 / Data regression problems are common in the literature, therein it is desired to infer the relationship between the dependent (output) and independent variable (input) from a dataset. Infer the relationship between variables is not a simple task, many times there is a high non-linearity and noise in the data inside them. Two machine learning techniques that are able to work with this type of information are investigated, the Genetic Programming and Artificial Neural Networks. Still, in many cases the machine learning technique cannot find a satisfactory solution due to the unbalance of the database. Therefore, the aim of this study was to apply machine learning techniques in regression of unbalanced data, evaluating and comparing the results obtained with different approaches. The balancing method used is summarized in constructing weights to the data set, one for each sample, which represents the importance of example during the learning process model. This problem of unbalanced data modeling applies in a real agronomic data modeling, specifically in the study of white mold disease caused by the fungus Sclerotinia sclerotiorum (Lib.) de Bary. Due to the high destructive power of the disease to crops, knowledge of the presence of resistance structures called sclerotia in an area is of paramount importance so that appropriate actions are taken to treat the disease. In this case study, the task is to use learning techniques to build a predictive model of sclerotia from meteorological characteristics and location of the sample to the state of Paraná, using a set of unbalanced data. Different approaches to the techniques and the balancing method was employed for constructing the model. The Artificial Neural Networks with resilient propagation learning algorithm achieved better performance in creating the model for prediction of sclerotia able to predict the actual outcome with a correlation of 0.763 and a mean absolute error of 24.35. To identify if the employee balancing method improved the results we applied the Kruskal-Wallis test. The test showed that there is a statistically significant improvement between genetic programming with and without balancing technique. However the technique that showed the best results was the neural network with resilient propagation learning algorithm, the data set of white mold and in some cases experimental. / Problemas de regressão de dados são comuns na literatura, neles deseja-se inferir a relação entre variáveis dependentes (saída) e variáveis independentes (entrada) a partir de um conjunto de dados. Inferir esta relação entre as variáveis não é uma tarefa simples, por muitas vezes existirem uma alta não linearidade nos dados e pelo ruído existente neles. Duas técnicas de aprendizagem de máquina que são capazes de trabalhar com este tipo de informação são investigadas, a Programação Genética e as Redes Neurais Artificiais. Ainda assim, em muitos casos a técnica de aprendizado de máquina não consegue encontrar uma solução satisfatória, devido ao desbalanceamento da base de dados. Portanto, o objetivo deste trabalho foi aplicar técnicas de aprendizagem de máquina na regressão de dados desbalanceados, avaliando e comparando os resultados obtidos com diferentes abordagens. O método de balanceamento empregado resume-se em construir pesos para o conjunto de dados, um para cada exemplo, que representa a importância do exemplo durante o processo de aprendizagem do modelo. Este problema de modelagem em dados desbalanceados aplica-se em um caso real de modelagem de dados agronômicos, mais especificamente no estudo da doença mofo branco, causada pelo fungo Sclerotinia sclerotiorum (Lib.) de Bary. Devido ao alto poder destrutivo da doença para as culturas, o conhecimento da presença das estruturas de resistência chamadas de escleródios em uma área é de suma importância para que se tomem atitudes adequadas para o tratamento da doença. Neste estudo de caso, a tarefa é utilizar as técnicas de aprendizagem para a construção de um modelo de previsão de escleródios a partir de características meteorológicas e do local da amostra para o estado do Paraná, utilizando um conjunto de dados desbalanceados. Diferentes abordagens com as técnicas e com o método de balanceamento foram empregadas na construção do modelo. As Redes Neurais Artificiais com o algoritmo de aprendizagem resilient propagation obtiveram um melhor desempenho na criação do modelo para previsão de escleródios, conseguindo prever o resultado real com uma correlação de 0,763 e um erro médio absoluto de 24,35. Para identificar se o método de balanceamento empregado melhorou os resultados obtidos foi aplicado o teste de Kruskal-Wallis. O teste mostrou que existe uma melhora estatisticamente significativa entre a programação genética com e sem a técnica de balanceamento. Porem a técnica que apresentou melhores resultados foi a Rede Neural com o algoritmo de aprendizagem resilient propagation, no conjunto de dados do mofo branco e em alguns casos experimentais.

The analysis of unbalanced power system problems using the method of phase co-ordinates by which the phase quantities are preserved has obvious practical advantages over the transformation methods requiring the phase quantities to be substituted by, for example, symmetrical component and d-q quantities. Since the physical identity of the system is maintained in the phase frame of reference, the matematical models of the system can be subjected to actual operating constraints enabling a unified approach to be adopted in the study of both symmetrical and unsymmetrical conditions. In this thesis the bond graph techniques are used to model power system components in terms of their phase co-ordinates. The bond graph structure, which is based on energy continuity and power balance, classifies system and sub-systems, with respect to the number of energy ports through which energy or power is exchanged with the environment as well as in terms of the particular internal energy transformations involved. The use of bond graphs for the analysis of non-linear electromagnetic systems has resulted in the evolution of a uniform diagramatic structure which, represents in a single diagram the basic field properties such as the magneto-motive force and the flux linkages together with the conjugate circuit power variables, voltage and current. As an extension of this ideal the general n-port electromagnetic and electrostatic field systems are derived in bond graph notations. A very desirable feature of this method of presentation is that there exists a one-to-one-correspondence between the bond graph and a computation structure which may be used for the purpose of simulation by either analogue or digital computers. The general n-port electromagnetic and electrostatic field systems form the basis for the effective modelling of power system components such as rotating machines, transformers and transmission lines. In the investigations of earth faults, these models are simplified in accordance with the need of the particular study but are sufficiently accurate representations to allow predictions on the overall system behaviours. The bond graph approach is ideally suited to expedite the modelling of dynamic interacting energy systems and when used in conjunction with the computation structure can provide the simulation technique required to model accurately the non-linear behaviours of multiport electromechanical energy converters. The effects of magnetic saturation in synchronous generators are presented in detail.

O preço atual do minério de ferro obrigou as empresas a reduzirem os custos operacionais na fase mina. O carregamento e transporte de materiais com utilização de escavadeiras e caminhões grande porte representam grande parcela do custo total, particularmente com pneus, diesel, manutenção e mão de obra. Metas de movimentação anual são divididas durante os meses e as condições climáticas podem influenciar na produtividade e desempenho dos equipamentos. O banco de dados da movimentação mensal está condicionado com a capacidade de cada caminhão. Cada frota possui o payload característico e este representa a capacidade de transporte, sendo o valor da massa transportada o único parâmetro extraído em cada ciclo, sem considerar o posicionamento do material sobre a caçamba dos equipamentos. Forças de cisalhamento e torção são aplicadas constantemente no chassi e pneus dos caminhões e, quando as cargas estão descentralizadas, potencializam estes eventos. O transporte de cargas descentralizadas agride os pneus diminuindo a vida útil causando danos como deslocamento da banda de rodagem e separação do flanco. Este trabalho teve como objetivo diminuir as ocorrências de cargas descentralizadas e os custos operacionais. Para incrementar o posicionamento do material sobre as caçambas, a telemetria foi a ferramenta utilizada. Análises de pressões de suspensões indicam o posicionamento das cargas e através desses valores foi criado um banco de dados. Este banco de dados pode indicar qual operador de carga precisa de reciclagem, contribuindo para a redução de cargas descentralizadas e custos, uma vez que cargas deste perfil sucateiam precocemente pneus e suspensões. O estudo foi realizado em Itabira, em uma mina de minério de ferro a céu aberto. A metodologia comprovou ser capaz diminuir as ocorrências de cargas descentralizadas assim como aumentar a vida útil de pneus. Uma possível economia foi apresentada para ano de 2014, período em que a média das horas trabalhadas de pneus ficou abaixo da meta aumentando os custos fase mina. / The actual iron ore price forces the companies to reduce costs in all production steps of the mining operation. Loading and hauling materials using shovel-truck system represents the highest mining costs, particularly tires, diesel, maintenance and workforce. Annual goals of materials movement are split by months were weather conditions can affect productivity and performance of the fleet. The data file of the monthly material movement is based on the scale of each truck. Every fleet has a payload and it represents the capacity of hauling, being the value of loading a unique input extracted in each duty cycle, without taking into account the position of the material over the truck’s dump. Shear forces and torsion are applied all time at the frames trucks and, when the truckloads are unbalanced, increases the forces over the frame and tires. Transport unbalanced truckloads into long distances attack the tires and decrease its end of life, causing damages like displacement of tread and flank separation. The objective of this study is to propose a methodology to decrease unbalanced truck loads reducing the mining costs. In this mission of incorporating a material position on the truck´s dump, the telemetry was taking into consideration. The analysis of the suspension pressures data values shows the truckloads positions and with this data was created a databank. This databank indicates that the operators need truck load training to reduce unbalanced loads and truck costs in the mining operation, since unbalanced loads leads to early tires and suspensions scrap. The case study was carried out at Itabira Iron Ore Mine Complex, Brazil. This methodology was able to reduce the number of unbalanced truck loads as well as the tires life was increased. An economic saving estimate is presented based on 2014 scrapped tires data bank, in this year the tires life cycle was underneath, burdening operational costs.

Wind energy has been the fastest emerging renewable energy source over the last decade. The overriding provisos to minimise greenhouse emissions and increasing concerns regarding energy security have been the major inducements for many countries to make a resolute transition to new and non-conventional power sources. Direct-drive systems for wind turbines are potentially a more reliable alternative to gearbox driven systems. Gearboxes are liable to significant accumulated fatigue torque loading with relatively high maintenance costs. It is with this in mind that the primary focus of this research is on direct-drive wind turbines. Generators in direct-drive wind turbines tend to be of large diameter and heavier due to the support structure required to maintain as small air-gap as possible between the stationary and rotating parts of the generator. Permanent magnet generators (PMGs) are the most common type to be used within direct-drive wind turbines nowadays. Generators and other drive-train components in wind turbines experience significant varying loads, which may lead to a bearing failure. These varying loads can lead to misalignment within the drivetrain producing eccentricity between the generator rotor and stator. Rotor eccentricity generates a magnetic force referred to as Unbalanced Magnetic Pull (UMP). The induced UMP for the same rotor eccentricity is much higher in PMGs than induction generators because of the higher permanent magnet magnetic field. UMP is an important issue requiring further research. A part of this study provides a more detailed treatment of UMP under varying rotor eccentricity regimes for various permanent magnet machine topologies. The effect of UMP in direct-drive PMGs on the lifetime of the main bearing is a topic that requires more research aimed at proposing design improvements and solutions. The hope being that the availability of such solutions can be applied to practical reductions in operating costs. In brief, identification of the root causes of failure and impacts on component lifetime remain a subject of research. Establishing analytical tools for studying the impact of UMP on component lifetime in direct drive wind turbines and identifying the prospects for air gap winding machines using single bearing configuration are the two key areas for further research. Firstly, this research aims to establish the relationship between bearing forces and different types of eccentricities and UMP in direct drive machines. It is intended to use such models for predicting bearing wear and fatigue. Secondly, this research aims to establish the analytical tools for studying static, dynamic and tilting eccentricity in air-gap winding direct drive generators. Such tools are used to increase the understanding of the dynamics of direct drive PM generators. The final step of this study is using a multi-body simulation software (SIMPACK) to initiate investigations and comparison by providing assessments of electromagnetic interaction and internal drive-train loading for four possible designs for a proposed 5MW direct-drive wind turbine in response to the loads normally seen by a wind turbine. The four designs include: (a) iron-cored PM direct-drive generator supported by two main bearings, (b) airgap winding PM direct-drive generator supported by two main bearings, (c) iron-cored PM direct-drive generator supported by a single main bearing, (d) airgap winding PM direct-drive generator supported by a single main bearing. An aero-elastic simulation code (HAWC2) is used to extract the hub loads for different wind speeds corresponding to the normal operation of the wind turbine. The dynamic eccentricity and its influence on the electromagnetic interaction and consequential effects on bearing loading for all four designs is examined to determine the most optimal support structural configuration for a direct-drive system. In summary, the main aim of this thesis is studying the effect of different types of rotor eccentricities in different types of direct drive PMGs on the main bearing arrangements. The results show that static rotor eccentricity has the maximum impact compared to the other types of eccentricities. The main result of an eccentricity is the induced UMP which applies directly as an extra force on the bearings. The influence of UMP on bearing wear is studied. This influence is found to be significant in PM machines and should be considered when designing the bearing stiffness. A 20% static rotor eccentricity in a PM machine is found to induce an UMP that roughly equals third the total weight of the machine. A single bearing design for a direct-drive wind turbine is proposed and compared with a conventional two-bearing design. The results show that the Iron-cored PM direct-drive generator supported by two main bearings design and airgap winding PM direct-drive generator supported by a single main bearing design have advantages over the other two designs in this study.

Esta dissertação compreende um estudo da eficiência de estimadores dos parâmetros no modelo funcional com erro nas variáveis, com repetições para contornar o problema de falta de identificação. Nela, discute-se os procedimentos baseados nos métodos de máxima verossimilhança e escore corrigido. As estimativas obtidas pelos dois métodos levam a resultados similares. / This work is concerned with a study on the efficiency of parameter estimates in the functional linear relashionship with constant variances. Where the lack of identification is resolved of by considering replications. Estimation is dealt with by using maximum likelihood and the corrected score approach. Comparisons between the approaches are illustrated by using simulated data.

Esta dissertação compreende um estudo da eficiência de estimadores dos parâmetros no modelo funcional com erro nas variáveis, com repetições para contornar o problema de falta de identificação. Nela, discute-se os procedimentos baseados nos métodos de máxima verossimilhança e escore corrigido. As estimativas obtidas pelos dois métodos levam a resultados similares. / This work is concerned with a study on the efficiency of parameter estimates in the functional linear relashionship with constant variances. Where the lack of identification is resolved of by considering replications. Estimation is dealt with by using maximum likelihood and the corrected score approach. Comparisons between the approaches are illustrated by using simulated data.

abstract: 摘要 当前中国农村集体经济呈现出后劲不足、区域失衡等问题。在此背景下，如何破解集体经济发展困境、实现其从梯度到均衡的演进成为学术领域关注的热点。本文梳理总结了国内外集体经济的相关研究成果，阐述了主要涉及的基础概念、理论和方法模型；以2008~2015年无锡市滨湖区92个村为研究样本，分析了该区域集体经济的发展现状和演变进程；构建面板回归模型，探索了该区域集体经济发展的驱动因素与分布不平衡性；并从空间关联视角切入，探索了驱动因素的溢出效应；最后基于研究结果提出对策建议。主要结论如下： （1）2008~2015年，92个村的村级集体经济发展整体呈现上升趋势，但地区间的贫富差距明显；2008年、2011年和2015年92个村按村级集体经济总收入可划分为高、中、低3类，并且在不同时段，各等级间的村级集体单位会相互迁移；集体经济收入呈现明显的右偏分布，尖峰厚尾的特征显著。随着时间的推移，集体经济发展出现了“双峰趋同”的现象。 （2）普通面板回归显示，物质资本、经济工作能力、科技进步对于村级集体经济发展有正向的依次减弱的影响，人口数量的影响为负；面板分位数回归显示，随着分位数水平的提高，物质资本系数先上升、后下降再上升；经济工作能力系数逐渐减小；人口规模系数先下降后上升；科技进步系数波动上升。 （3）空间计量结果显示，各变量对于村级集体经济发展具有一定的溢出效应，其中，物质资本的溢出效应为正（不显著），经济工作能力的溢出效应为正（显著），人口因素的溢出效应为负（不显著），科技进步的溢出效应为正（显著）。 本文的创新之处在于使用较难获取的2008-2015年92个村面板数据进行回归，相比于截面数据，更准确地测度了各要素对集体经济的真实影响；将空间关联因素纳入研究视域，探究了村级集体经济驱动因素的空间溢出效应。 / Dissertation/Thesis / Doctoral Dissertation Business Administration 2019

<p>The Kappa coefficient is widely used in assessing categorical agreement between two raters or two methods. It can also be extended to more than two raters (methods).  When using Kappa, the shortcomings of this coefficient should be not neglected.  Bias and prevalence effects lead to paradoxes of Kappa. These problems can be avoided by using some other indexes together, but the solutions of the Kappa problems are not satisfactory. This paper gives a critical survey concerning the Kappa coefficient and gives a real life example. A useful alternative statistical approach, the Rank-invariant method is also introduced, and applied to analyze the disagreement between two raters.</p>

The Kappa coefficient is widely used in assessing categorical agreement between two raters or two methods. It can also be extended to more than two raters (methods).  When using Kappa, the shortcomings of this coefficient should be not neglected.  Bias and prevalence effects lead to paradoxes of Kappa. These problems can be avoided by using some other indexes together, but the solutions of the Kappa problems are not satisfactory. This paper gives a critical survey concerning the Kappa coefficient and gives a real life example. A useful alternative statistical approach, the Rank-invariant method is also introduced, and applied to analyze the disagreement between two raters.