This thesis discusses the placement of conventional power flow controllers (namely the Fixed series capacitor (FSC), Phase Angle Regulating Transformer (PAR)) and Flexible AC Transmission System (FACTS) devices (namely the Thyristor Controlled Series Capacitor (TCSC), the Static Synchronous Series Compensator (SSSC), the Unified Power Flow Controllers (UPFC) and the Sen Transformer (ST)) in bulk power systems to minimize transmission losses in the entire system. This firstly resolves line overloading and improves the overall voltage profile of the entire system. Secondly the transmission losses are minimized and also help in reducing the generation, which results in additional dollar savings in terms of the fuel costs. The sizes of the FACTS devices used were small in order to keep the initial installation costs low for the utility. The reduced FACTS device ratings are mentioned as a benefit, but not included in the overall loss minimization calculations. Various types of FACTS devices were modeled and placed in the power system, and the economic benefits were discussed and compared for different power flow conditions. The FSC, PAR, and TCSC are the FACTS Devices commonly used in the electric utility industry. In addition to the previous devices, the SSSC and UPFC were also modeled in the popular PSS/E and PSAT software's. The Sen Transformer was modeled using an electromagnetic transient simulation program (PSCAD/EMTDC). A line stability index was used to find the optimum location for placing the FACTS device. This thesis also provides a quantified value for the overall losses with the different FACTS devices, which is not available in the previous research literature. The Sen Transformer is a new type of a FACTS device that was developed by a former Westinghouse engineer, Dr. Kalyan Sen in 2003. It is based on the same operating principle as a UPFC (i.e. provides independent active and reactive power control) but uses the proven transformer technology instead. The benefit of the SEN transformer is that it would cost approximately only 30% of the UPFC cost. This thesis studies the Sen Transformer for loss minimization. Since the Sen technology uses a mature transformer technology, its maintenance costs are going to be less and therefore the utilities would be more comfortable using such a device instead of UPFC. A 12 bus test system proposed by FACTS modeling working group was used for validating and testing the FACTS devices in this thesis. This test system is a composite model of Manitoba Hydro, North Dakota, Minnesota, and Chicago area subsystems. This test platform manifests number of operating problems, which the electric utilities typically face. This system has been used for congestion management, voltage support and stability improvement studies with the FACTS devices. The results show that compensating a short transmission line in this system is more effective in minimizing the overall losses and improving the voltage profile compared to a typical approach of compensating long lines. The results also show that the UPFC and Sen Transformer are the most effective in minimizing the overall losses with the Sen Transformer being the most cost effective solution.

Made available in DSpace on 2016-08-29T15:33:25Z (GMT). No. of bitstreams: 1 tese_9881_Ata de defesa.pdf: 679815 bytes, checksum: bd13283b6e7f400de68b79f04cf0b4a9 (MD5) Previous issue date: 2016-05-20 / The objective of this work is to present the effectiveness and efficiency of algorithms for solving the loss minimization problem in Multi-Label Classification (MLC). We first prove that a specific case of loss minimization in MLC isNP-complete for the loss functions Coverage and Search Length, and therefore,no efficient algorithm for solving such problems exists unless P=NP. Furthermore, we show a novel approach for evaluating multi-label algorithms that has the advantage of not being limited to some chosen base learners, such as K-neareast Neighbor and Support Vector Machine, by simulating the distribution of labels according to multiple Beta Distributions.

A reconfiguração de sistemas de distribuição de energia elétrica consiste em alterar a topologia das redes através da abertura ou fechamento das chaves de interconexão existentes nos alimentadores de distribuição primários, de forma a otimizar uma determinada função objetivo. Normalmente os objetivos são a minimização de perdas ativas, o isolamento de faltas, o balanceamento de cargas entre alimentadores e/ou a melhoria dos níveis de tensão. Neste trabalho considera-se a minimização da perda ativa total. As dificuldades do problema de reconfiguração de redes de distribuição resultam do tamanho dos sistemas reais, aos quais correspondem um número elevado de variáveis binárias que representam as chaves, e também da relação quadrática existente entre a perda elétrica e a corrente que flui nos elementos da rede. Este trabalho desenvolve algumas novas formulações para o problema de reconfiguração de redes de distribuição, utilizando Programação Não Linear Inteira Mista. Além disso, demonstra-se que a parte contínua de todas as formulações é convexa, o que garante a unicidade da solução ótima para um dado estado das chaves na rede. Esta propriedade permitiu a utilização do Método de Newton na resolução do problema contínuo, com as seguintes vantagens: impossibilidade de o método identificar mínimos locais em vez do mínimo global procurado, e convergência em apenas uma iteração, proporcionada pela natureza quadrática das formulações. As formulações desenvolvidas foram implementadas na forma de programas computacionais. O desempenho das formulações é descrito e analisado através de diversos casos de estudo. / The reconfiguration of electricity distribution systems is concerned with finding the state of switching and protective devices so as to optimize a given objective function, which is usually defined as minimization of total loss, fault isolation, load balancing among feeders, or improvement of voltage profile. In this work, the objective function is defined as the minimization of total active loss. The main difficulties associated with this problem arise from the high number of binary variables that represent the switching and protective devices, as well as the quadratic relationship between electric loss and currents flowing through the network branches. This work develops some new formulations for the distribution system reconfiguration problem, which are then solved through mixed-integer nonlinear programming. In addition, it is shown that the continuous part in all formulations is convex, which guarantees the uniqueness of the optimal solution for a given switch profile. This property allows using the Standard Newton Method for solving the continuous part of the problem, with the following advantages: impossibility of the Newton Method identifying a local minimum instead of the desired global minimum, and convergence in just one iteration owing to the quadratic nature of all formulations. The proposed formulations were implemented as computational programs and their performance was evaluated through various study cases.

A reconfiguração de sistemas de distribuição de energia elétrica consiste em alterar a topologia das redes através da abertura ou fechamento das chaves de interconexão existentes nos alimentadores de distribuição primários, de forma a otimizar uma determinada função objetivo. Normalmente os objetivos são a minimização de perdas ativas, o isolamento de faltas, o balanceamento de cargas entre alimentadores e/ou a melhoria dos níveis de tensão. Neste trabalho considera-se a minimização da perda ativa total. As dificuldades do problema de reconfiguração de redes de distribuição resultam do tamanho dos sistemas reais, aos quais correspondem um número elevado de variáveis binárias que representam as chaves, e também da relação quadrática existente entre a perda elétrica e a corrente que flui nos elementos da rede. Este trabalho desenvolve algumas novas formulações para o problema de reconfiguração de redes de distribuição, utilizando Programação Não Linear Inteira Mista. Além disso, demonstra-se que a parte contínua de todas as formulações é convexa, o que garante a unicidade da solução ótima para um dado estado das chaves na rede. Esta propriedade permitiu a utilização do Método de Newton na resolução do problema contínuo, com as seguintes vantagens: impossibilidade de o método identificar mínimos locais em vez do mínimo global procurado, e convergência em apenas uma iteração, proporcionada pela natureza quadrática das formulações. As formulações desenvolvidas foram implementadas na forma de programas computacionais. O desempenho das formulações é descrito e analisado através de diversos casos de estudo. / The reconfiguration of electricity distribution systems is concerned with finding the state of switching and protective devices so as to optimize a given objective function, which is usually defined as minimization of total loss, fault isolation, load balancing among feeders, or improvement of voltage profile. In this work, the objective function is defined as the minimization of total active loss. The main difficulties associated with this problem arise from the high number of binary variables that represent the switching and protective devices, as well as the quadratic relationship between electric loss and currents flowing through the network branches. This work develops some new formulations for the distribution system reconfiguration problem, which are then solved through mixed-integer nonlinear programming. In addition, it is shown that the continuous part in all formulations is convex, which guarantees the uniqueness of the optimal solution for a given switch profile. This property allows using the Standard Newton Method for solving the continuous part of the problem, with the following advantages: impossibility of the Newton Method identifying a local minimum instead of the desired global minimum, and convergence in just one iteration owing to the quadratic nature of all formulations. The proposed formulations were implemented as computational programs and their performance was evaluated through various study cases.

The electric power distribution system usually operates a radial configuration, with tie switches between circuits to provide alternate feeds. The losses would be minimized if all switches were closed, but this is not done because it complicates the system's protection against overcurrents. Whenever a component fails, some of the switches must be operated to restore power to as many customers as possible. As loads vary with time, switch operations may reduce losses in the system. Both of these are applications for reconfiguration. The problem is combinatorial, which precludes algorithms that guarantee a global optimum. Most existing reconfiguration algorithms fall into two categories. In the first, branch exchange, the system operates in a feasible radial configuration and the algorithm opens and closes candidate switches in pairs. In the second, loop cutting, the system is completely meshed and the algorithm opens candidate switches to reach a feasible radial configuration. Reconfiguration algorithms based on linearized transshipment, neural networks, heuristics, genetic algorithms, and simulated annealing have also been reported, but not widely used. These existing reconfiguration algorithms work with a simplified model of the power system, and they handle voltage and current constraints approximately, if at all. The algorithm described here is a constructive method, using a full nonlinear power system model that accurately handles constraints. The system starts with all switches open and all failed components isolated. An optional network power flow provides a lower bound on the losses. Then the algorithm closes one switch at a time to minimize the increase in a merit figure, which is the real loss divided by the apparent load served. The merit figure increases with each switch closing. This principle, called discrete ascent optimal programming (DAOP), has been applied to other power system problems, including economic dispatch and phase balancing. For reconfiguration, the DAOP method's greedy nature is mitigated with a backtracking algorithm. Approximate screening formulas have also been developed for efficient use with partial load flow solutions. This method's main advantage is the accurate treatment of voltage and current constraints, including the effect of control action. One example taken from the literature shows how the DAOP-based algorithm can reach an optimal solution, while adjusting line voltage regulators to satisfy the voltage constraints. / Ph. D.

This dissertation presents dynamic reactive power control of isolated power systems. Isolated systems include MicroGrids in islanded mode, shipboard power systems operating offshore, or any other power system operating in islanded mode intentionally or due to a fault. Isolated power systems experience fast transients due to lack of an infinite bus capable of dictating the voltage and frequency reference. This dissertation only focuses on reactive control of islanded MicroGrids and AC/DC shipboard power systems. The problem is tackled using a Model Predictive Control (MPC) method, which uses a simplified model of the system to predict the voltage behavior of the system in future. The MPC method minimizes the voltage deviation of the predicted bus voltage; therefore, it is inherently robust and stable. In other words, this method can easily predict the behavior of the system and take necessary control actions to avoid instability. Further, this method is capable of reaching a smooth voltage profile and rejecting possible disturbances in the system. The studied MicroGrids in this dissertation integrate intermittent distributed energy resources such as wind and solar generators. These non-dispatchable sources add to the uncertainty of the system and make voltage and reactive control more challenging. The model predictive controller uses the capability of these sources and coordinates them dynamically to achieve the voltage goals of the controller. The MPC controller is implemented online in a closed control loop, which means it is self-correcting with the feedback it receives from the system.

The diploma thesis deals with the simulation of induction motor control with respect to high efficiency. The theory of an induction motor is described here, with emphasis on its losses. Scalar and vector control are also described here. Vector control is optimized for higher efficiency. Subsequently, the creation of a model in the program đť‘€đť´đť‘‡ đťżđť´đťµâ’𝑆𝑖𝑚𝑢𝑙𝑖𝑛𝑠is described here, for the comparison of scalar and vector control with optimization.

The diploma thesis deals with the simulation of induction motor control with respect to high efficiency. The theory of an induction motor is described here, with emphasis on its losses. Scalar and vector control are also described here. Vector control is optimized for higher efficiency. Subsequently, the creation of a model in the program MATLAB - Simulink is described here, for the comparison of vector control with and without optimization.

Due to increasing penetration of solar power generation, distribution grids are facing a number of challenges. Frequent reverse active power flows can result in rapid fluctuations in voltage magnitudes. However, with the revised IEEE 1547 standard, smart inverters can actively control their reactive power injection to minimize voltage deviations and power losses in the grid. Reactive power control and globally optimal inverter coordination in real-time is computationally and communication-wise demanding, whereas the local Volt-VAR or Watt-VAR control rules are subpar for enhanced grid services. This thesis uses machine learning tools and poses reactive power control as a kernel-based regression task to learn policies and evaluate the reactive power injections in real-time. This novel approach performs inverter coordination through non-linear control policies centrally designed by the operator on a slower timescale using anticipated scenarios for load and generation. In real-time, the inverters feed locally and/or globally collected grid data to the customized control rules. The developed models are highly adjustable to the available computation and communication resources. The developed control scheme is tested on the IEEE 123-bus system and is seen to efficiently minimize losses and regulate voltage within the permissible limits. / Master of Science / The increasing integration of solar photovoltaic (PV) systems poses both opportunities and technical challenges for the electrical distribution grid. Although PV systems provide more power to the grid but, can also lead to problems in the operation of the grid like overvoltages and voltage fluctuations. These variations can lead to overheating and burning of electrical devices and equipment malfunction. Since the solar generation is highly dependent on weather and geographical location, they are uncertain in their output. The uncertainity in the solar irradiance can not be handled with the existing voltage control devices as they need to operate more frequently than usual which can cause recurring maintenance needs for these devices. Thus, to make solar PV more flexible and grid-friendly, smart inverters are being developed. Smart inverters have the capability of advanced sensing, communication, and controllability which can be utilized for voltage control. The research discusses how the inverters can be used to improve the grid profile by providing reactive power support to reduce the power losses and maintain voltages in their limits for a safer operation.

O objetivo deste trabalho é apresentar uma nova abordagem para obtenção de configurações para sistemas de distribuição de energia elétrica com o intuito de minimizar o valor de perdas ativas sem violar as restrições operacionais. Para isso, considera-se que os sistemas de distribuição estão operando em regime permanente e que suas fases estão equilibradas e simétricas, podendo o sistema ser representado por um diagrama unifilar. A reconfiguração é feita de forma a redistribuir os fluxos de corrente nas linhas, transferindo cargas entre os alimentadores e melhorando o perfil de tensão ao longo do sistema. O problema de reconfiguração do sistema pode ser formulado como um problema de programação não-linear inteiro misto. Devido à explosão combinatorial inerente a este tipo de problema, a resolução do mesmo por técnicas de otimização clássicas torna-se pouco atraente, dando espaço para técnicas heurísticas e metaheurísticas. Essas outras, mesmo não garantindo o ótimo global, são capazes de encontrar boas soluções em um espaço de tempo relativamente curto. Para a resolução do problema de reconfiguração, utilizou-se uma nova metodologia baseada no comportamento de colônias de formigas em busca de alimento na natureza. Nesta, formigas artificiais (agentes) exploram o meio ambiente (sistema de distribuição) e trocam informações para tentar encontrar a topologia que apresente os menores valores de perdas ativas. Para o cálculo das perdas, este trabalho também apresenta uma nova abordagem para resolução do problema de fluxo de potência (FP) em sistemas de distribuição radial. O fluxo de potência é uma ferramenta básica utilizada pelos centros de controle para determinar os estados e condições operacionais desses sistemas de potência. Basicamente, as metodologias empregadas para o cálculo do fluxo de potência são baseadas nos métodos clássicos de Newton ou Gauss. Mas em sistemas de distribuição de energia, devido a particularidades inerentes a estes, como a alta relação entre resistência e reatância das linhas (r/x) e a operação radial, estes métodos apresentam problemas de convergência e se tornam ineficientes na maioria das vezes. A abordagem consiste na associação dos métodos da função penalidade e de Newton. O mal-condicionamento da matriz Jacobiana de Newton é resolvido pela associação com o método da função penalidade. São apresentados testes realizados em sistemas de 5 barras, 16 barras, 33 barras, 69 barras e 136 barras para avaliar a potencialidade das técnicas propostas. Os resultados são considerados bons ou muito bons quando comparado com as técnicas existentes atualmente. / The objective of this work is to present a novel methodology for obtaining new configurations of the distribution system in order to minimize the active power losses without violating operational constraints. For this, it is considered that any distribution system is operating in a steady state and that it is balanced, therefore it can be represented by a one-line diagram. The reconfiguration is done in order to redistribute de current flows on the distribution power lines, transferring loads among the feeders and improving the voltage profile along the system. Such problem can be formulated as a mixed integer nonlinear programming problem. Due to its inherent combinatorial characteristic and since its solution by classic optimization techniques is not appealing, heuristic and metaheuristic techniques are thus better suited for its solution. Although these latter do not guarantee a global optimum, they are able to find good solutions in a relatively short time. The solution of the reconfiguration problem in this approach makes use of a novel methodology based on ant colony behavior, when these search for victuals in nature. In this technique, the artificial ants (agents) explore the environment (distribution system) and exchange information among them in order to find the topology that provides the smallest active losses. For the active losses calculation, this work also presents a novel approach for the solution of the power flow problem for radial distribution systems. The solution of the power flow problem is used by system operators in order to determine the state and operational conditions of power systems. Basically, the most common techniques used in the power flow solution are based on either Newton\'s or Gauss\' approaches. However, due to particular characteristics of distribution systems such as the high ratio of r/x and the radial topology, these methods present convergence problems and are not efficient in most of the cases. Thus, this novel technique consists in associating Newton\'s and the penalty function approaches. The matter of the ill-conditioned Jacobian matrix in Newton\'s method is overcome with the penalty function method. Some tests performed in different systems are then presented in order to assess the effectiveness of both proposed techniques.