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Congestion is always a serious problem in power system. In order to solve the kind of thorny problem, experts employ various methods for relieving congested difficulties. There are many new power-electronics-based devices using to solve the difficult problems recently. Unified Power Flow Controller (UPFC) is the most powerful device of these devices. The UPFC is capable of providing not only active and reactive control but also adaptive voltage amplitude control. By way of UPFC, power flow in power system is changed. Congestion problems are solved easily. A new model is proposed in this thesis to improve existing power-based model by using the Norton Equivalent Theorem. The proposed model can be integrated with the Equivalent Current Injection (ECI) power flow model easily. By ECI algorithm, it is much quickly and precisely to implement power flow calculations. By making use of Genetic algorithm (GA), the optimal location of UPFC in power system will be obtained. In the solution process, GA will be integrated with the nonlinear interior point OPF to select the optimal control parameters and UPFC sitting to solve congestion problems. Tests under MATLAB (The Math Works, Inc.) will be used to show the effectiveness of the proposed algorithms in solving a modified OPF problem for real congestion control under deregulation.

The integration of distributed generators (DGs) into the distribution grid has exacerbated voltage unbalance issues leading to greater risks of reducing equipment lifetime, equipment damages, and increased ohmic losses. Most approaches to regulating voltage in distribution systems only focus on voltage magnitude and neglect phasor discrepancies and do little to remedy voltage unbalance. To combat this, a novel Optimal Power Flow (OPF) is designed to help operate these resources in a manner that curtails voltage unbalance using the reactive power compensation capabilities of inverters. The OPF was run for a wide variety of loading conditions on a pair of systems using MATLAB and was shown to improve the voltage profile of the system in addition to minimizing losses in most cases. However, it is noted that the OPF loses exactness in highly stressed conditions and is unable to provide meaningful solutions / Master of Science / With the power grid getting greener and smarter by the day, a slew of new challenges arise to overcome. Distributed sources of energy like solar panels and batteries are being added to the grid right from the household level. While they are desirable for reducing our need for traditional sources of energy, the addition of these resources has been shown to cause issues in the quality of the power grid. This is particularly observed at the low-voltage domestic part of the grid where the resources cause issues with the voltage quality. The distribution grid is unbalanced by nature and adding these resources only amplifies this problem. To help mitigate voltage quality issues grid operators are starting to require voltage regulation capabilities from resources to be connected to the grid and a lot of work has been conducted to find the optimal strategies for operating these resources. However, existing paradigms for these sources only focus on fixing the voltage magnitude part of the power quality and neglect phasor relationships. This thesis aims to bridge this gap by developing a method to determine the optimal operation of these resources by using the voltage regulation capability to address both voltage magnitude and voltage unbalance issues in addition to optimal operation.

Neste trabalho, buscou-se compreender a morfologia e os componentes do sinal da deglutição. Na busca desse entendimento diversas técnicas foram empregadas. No intuito de fazer marcações fidedignas em trechos específicos do sinal, o qual foi analisado simultaneamente com a imagem da videofluoroscopia da deglutição, considerado o melhor método atual na avaliação da dinâmica da deglutição. Os parâmetros numéricos utilizados para análise também foram abrangentes e com base em técnicas atuais de processamento de sinais, como emprego de transformada Wavelet. Quanto à classificação dos sinais, foram utilizados classificadores modernos como floresta de caminhos ótimos, máquinas de vetores de suporte, redes neurais artificiais e classificador Bayesiano, dando maior ênfase ao primeiro, por possuir um custo computacional bem menor quando comparado aos outros 3, e consequentemente convergindo mais rapidamente ao resultado. Foram avaliados 84 sinais, divididos em 2 grupos separados pela consistência do bolo alimentar oferecido (líquido e pastoso). Na distinção e/ou caracterização desses tipos foi definido um subconjunto com 4 variáveis que proporcionou uma boa acurácia na separação das classes representantes de cada tipo de bolo alimentar. / This work proposes to understand the morphology and the components of the swallowing signal. In pursuit of this understanding, a variety of techniques were employed. In order to make reliable markings on specific portions of the signal, the signal was examined simultaneously with videofluoroscopic swallowing, which is considered the best method in the evaluation of swallowing dynamics. The parameters used for numerical analysis were based on current signal processing techniques, such as: Wavelet transform, Optimum path forest, Support vector machines, Artificial neural networks and Bayesian classifier, emphasizing the first technique, due to a much lower computational cost when compared to the previous, and, consequently, the results converged much faster. Eighty four signals, divided into 2 groups separated by the consistency of food bolus offered (liquid and thickened), were evaluated. For distinction and/or characterization of such types, a subset with 4 variables was defined, providing a good accuracy in the separation of these classes representing each type of consistency of the food bolus.

Neste trabalho, buscou-se compreender a morfologia e os componentes do sinal da deglutição. Na busca desse entendimento diversas técnicas foram empregadas. No intuito de fazer marcações fidedignas em trechos específicos do sinal, o qual foi analisado simultaneamente com a imagem da videofluoroscopia da deglutição, considerado o melhor método atual na avaliação da dinâmica da deglutição. Os parâmetros numéricos utilizados para análise também foram abrangentes e com base em técnicas atuais de processamento de sinais, como emprego de transformada Wavelet. Quanto à classificação dos sinais, foram utilizados classificadores modernos como floresta de caminhos ótimos, máquinas de vetores de suporte, redes neurais artificiais e classificador Bayesiano, dando maior ênfase ao primeiro, por possuir um custo computacional bem menor quando comparado aos outros 3, e consequentemente convergindo mais rapidamente ao resultado. Foram avaliados 84 sinais, divididos em 2 grupos separados pela consistência do bolo alimentar oferecido (líquido e pastoso). Na distinção e/ou caracterização desses tipos foi definido um subconjunto com 4 variáveis que proporcionou uma boa acurácia na separação das classes representantes de cada tipo de bolo alimentar. / This work proposes to understand the morphology and the components of the swallowing signal. In pursuit of this understanding, a variety of techniques were employed. In order to make reliable markings on specific portions of the signal, the signal was examined simultaneously with videofluoroscopic swallowing, which is considered the best method in the evaluation of swallowing dynamics. The parameters used for numerical analysis were based on current signal processing techniques, such as: Wavelet transform, Optimum path forest, Support vector machines, Artificial neural networks and Bayesian classifier, emphasizing the first technique, due to a much lower computational cost when compared to the previous, and, consequently, the results converged much faster. Eighty four signals, divided into 2 groups separated by the consistency of food bolus offered (liquid and thickened), were evaluated. For distinction and/or characterization of such types, a subset with 4 variables was defined, providing a good accuracy in the separation of these classes representing each type of consistency of the food bolus.

In a deregulated power market financial transmission rights (FTR) serve as a mechanism for protecting market participants from price variation resulting from network congestion. Possession of FTRs allows participants to recover congestion related losses resulting from unequal locational marginal prices that arise from out of merit dispatch. There exists different strategies for allocating FTR which are in use in the deregulated market. Designing a comprehensive framework for market specific FTR allocation that includes factors like unbalanced FTR, FTR for losses and AC-OPF is currently a major research issue in the deregulated power industry. This thesis develops a method for allocation of financial transmission rights that maximizes revenue while satisfying the system security constraints of alternating current (AC) networks and the revenue adequacy constraint of the financial market. Both the maximization of the FTR revenue and maintaining the constraints are accomplished through solving a modified version of the optimal power flow program. The methodology developed here considers allocation of both balanced and unbalanced point to point FTR obligations. The design of the framework is centered around three main scenarios that arise in the allocation of FTR. In the first scenario the total FTR bid quantity is much less than the total generation quantity available in the network. To maximize revenue the ISO will allocate the entire quantity and needs to only determine the loss quantity associated with the FTR quantity. In the second scenario the total FTR bid quantity is much greater than the total generation quantity available in the network. The ISO is required to determine the maximum allocatable FTR bid per bus in the network for the given generation limit in the network. A novel adaptation of the OPF program that maximizes the total FTR quantity allocated is run in this case to determine the maximum allocatable bid quantities. The third scenario is when the total FTR bid quantity is less than the total generation quantity available in the network but when the losses stipulated by the FTR quantity are added to the bid quantity the total generation capacity is exceeded. Here the novel adaptation of the OPF program is run to determine the maximum allocatable FTR bid quantity per bus (ceiling values). The original FTR bid quantities are then allocated upto the ceiling values determined. When multiple FTR bids are offered on a point-to-point node pair, allocation of FTRs among the bidders for that node pair is done through an auction process. Various auction strategies such as first price uniform, discriminatory auction, and second price uniform auction are considered. The performance of the FTR allocation process is evaluated for the above auction strategies through sample IEEE networks with 9 and 32 buses, available in the MATPOWER software.

Increase in energy demand is one of the major challenges that utilities are faced with, thus resulting in an increase in environmental pollution and global warming. The transport sector has a significant share of the energy demand and is a major contribution of emissions to the environment. In Canada, almost 35% of the total energy demand is from the transport sector and it is the second largest source of greenhouse gas (GHG) emissions. The government of Ontario has aimed to move toward a green energy economy, thus resulting in increased penetration of renewable energy sources as well as Plug-in hybrid electric vehicle (PHEV) technology. Penetration of renewable energy sources into microgrids are gradually being recognized as important alternatives in supply side planning. This thesis focuses on the optimal design, planning, sizing and operation of a hybrid, renewable energy based microgrid with the goal of minimizing the lifecycle cost, while taking into account environmental emissions. Four different configurations including a diesel-only, a fully renewable-based, a diesel-renewable mixed, and an external-grid connected microgrid are designed, to compare and evaluate their economics, operational performance and environmental emissions. Analysis is also carried out to determine the break-even economics for a grid-connected microgrid. The well-known energy modeling software for hybrid renewable energy systems, HOMER, is used in the studies reported in this thesis. An optimal power flow (OPF) based optimization framework considering two different objectives, minimizing feeder losses and PHEV charging cost, are presented to understand the impact of PHEV charging on distribution networks. Three different charging periods are considered and the impact of the Ontario Time-of-Use (TOU) tariff on PHEV charging schedules is examined. The impact of PHEV charging on distribution systems in the presence of renewable energy sources is discussed by extending the developed OPF based model to include the contribution of renewable energy sources. The proposed model is evaluated under a variety of scenarios.

Increase in energy demand is one of the major challenges that utilities are faced with, thus resulting in an increase in environmental pollution and global warming. The transport sector has a significant share of the energy demand and is a major contribution of emissions to the environment. In Canada, almost 35% of the total energy demand is from the transport sector and it is the second largest source of greenhouse gas (GHG) emissions. The government of Ontario has aimed to move toward a green energy economy, thus resulting in increased penetration of renewable energy sources as well as Plug-in hybrid electric vehicle (PHEV) technology. Penetration of renewable energy sources into microgrids are gradually being recognized as important alternatives in supply side planning. This thesis focuses on the optimal design, planning, sizing and operation of a hybrid, renewable energy based microgrid with the goal of minimizing the lifecycle cost, while taking into account environmental emissions. Four different configurations including a diesel-only, a fully renewable-based, a diesel-renewable mixed, and an external-grid connected microgrid are designed, to compare and evaluate their economics, operational performance and environmental emissions. Analysis is also carried out to determine the break-even economics for a grid-connected microgrid. The well-known energy modeling software for hybrid renewable energy systems, HOMER, is used in the studies reported in this thesis. An optimal power flow (OPF) based optimization framework considering two different objectives, minimizing feeder losses and PHEV charging cost, are presented to understand the impact of PHEV charging on distribution networks. Three different charging periods are considered and the impact of the Ontario Time-of-Use (TOU) tariff on PHEV charging schedules is examined. The impact of PHEV charging on distribution systems in the presence of renewable energy sources is discussed by extending the developed OPF based model to include the contribution of renewable energy sources. The proposed model is evaluated under a variety of scenarios.

Cette thèse porte sur la construction des algorithmes distribués pour l’optimisation de la production et du partage de ressources au sein d’un réseau de large dimension. Notamment, on se concentre sur les réseaux électriques et les réseaux cellulaires 5G. On considère dans le cas des réseaux électriques le problème OPF (Optimal Power Flow) dans lequel on vise à faire la gestion et l’optimisation de la production de l’énergie électrique d’une manière distribuée. On se concentre sur une version linéarisée du problème, la DC-OPF (Direct-Current Optimal Power Flow). Comme le problème d’optimisation est convexe dans ce cas, on vise à minimiser le coût de production de l’énergie tout en respectant les limites des lignes de transmission et les contraintes caractéristiques du système. Dans le cas des réseaux cellulaires, on formule un problème de Caching. On a pour but de réduire l’utilisation du backhaul liant les stations de base et le contrôleur du réseau. Les stations de base sont équipées d’une capacité de stockage limitée. Ils visent à trouver d’une manière optimale les fichiers à stocker dans le but de réduire une certaine fonction de coût sur l’utilisation du backhaul et sur le partage des fichiers avec les autres stations de base. L’approche adoptée dans cette thèse consiste à appliquer l’ADMM (Alternating Direction Method of Multipliers), une méthode d’optimisation de manière itérative, à un problème d’optimisation que l’on a préalablement reformulée de façon adéquate. Ce problème permet à la fois de décrire le DC-OPF et le problème de Caching. On démontre la convergence de cette méthode quand elle est appliquée noeud par noeudd’une manière totalement distribuée. Ainsi que dans le cas où le réseau est divisé en plusieurs zones. Ces zones peuvent se chevaucher mais aussi elles peuvent être séparées ou indépendantes. De plus, dans le contexte d’un réseau à zones, on démontre que l’application de l’ADMM d’une manière aléatoire par une seule zone converge aussi vers la solution optimale du problème. / This thesis focuses on the construction of distributed algorithms for optimizing resource production in a large interconnected system. In particular, it focuses on power grid and 5G cellular networks. In the case of power grid networks, we consider the OPF (Optimal Power Flow) problem in which one seeks to manage and optimize the production of electrical energy in a distributed manner. We focus on a linearized version of the problem, the DC-OPF (Direct- Current Optimal Power Flow) problem. This optimization problem is convex; the aim is to minimize the cost of energy generation while respecting the limits of the transmission line and the power flow constraints. In the case of 5G cellular networks, we formulate a caching problem. We aim to offload the backhaul link usage connecting the small bases stations (SBSs) to the central scheduler (CS). The SBSs are equipped with a limited storage capacity. We seek to find the optimal way to store files so as to reduce the cost on the use of backhaul and sharing files with other SBSs. The approach adopted in this thesis is to apply the ADMM (Alternating Direction Method of Multipliers), an optimization method that is applied iteratively, to an optimization problem that we adequately formulated previously. This problem can both describe the DC-OPF problem and the Caching problem. We prove the convergence of the method when applied node by node in a fully distributed manner. Additionally, we prove its convergence in the case where the network is divided into multiple areas or nations that may or may not overlap. Furthermore, in the context of a network with multiple areas, we show that the application of ADMM in a random manner by a single randomly chosen area also converges to the optimal solution of the problem.

Ingeniero Civil Eléctrico / El constante aumento de la demanda de energía eléctrica ha supuesto un gran desafío para los operadores de sistemas eléctricos, puesto que deben proveer energía a través del sistema de forma económica y confiable. Por suministro confiable se entenderá que éste sea continuo, independiente de si el sistema se encuentra en su estado intacto (planificado) o con fallas. Actualmente existen dos grandes criterios de seguridad para operar sistemas eléctricos, el criterio probabilístico y el determinístico. El criterio probabilístico minimiza costos de operación, de acciones de control y de demanda no suministrada en base a todos los estados posibles del sistema. El criterio determinístico por otro lado, define un conjunto de fallas creíbles que no afectan al sistema (no generan demanda no suministrada) para luego operar bajo este paradigma. Ninguno de estos modelos incorpora una medida de riesgo para la operación, existiendo por ende una incertidumbre respecto a la vulnerabilidad que presentaría el sistema frente a posibles fallas, razón por la cual se propone abordar esta deficiencia. Una métrica comúnmente usada como medida de riesgo es el Valor en Riesgo Condicional. Esta medida considera eventos en la cola de la curva de probabilidad, es decir, aquellos eventos que tienen una muy baja probabilidad de ocurrencia pero alto impacto. Esta memoria examina los modelos determinísticos y probabilísticos clásicos, para luego proponer un modelo que considera la energía no suministrada como índice de riesgo mediante un Valor en Riesgo Condicional. El Valor en Riesgo Condicional considera eventos en la cola de la curva de probabilidad, que si bien tienen una baja probabilidad de ocurrencia, pueden tener un alto impacto en la operación del sistema. Con esto se le exige un mínimo de confiabilidad a la operación, limitando el riesgo asociado a los eventos catastróficos (i.e. de baja probabilidad y alto impacto). Se evaluará la confiabilidad que aportan las restricciones de límites de riesgo a nivel sistémico (disminuir el riesgo de demanda no suministrada del sistema como conjunto) y límite de riesgo a nivel nodal (disminuir el riesgo de demanda no suministrada por nodo). Los resultados confirman que la integración de estas restricciones permite operar el sistema de una manera más segura y confiable. El modelo propuesto disminuye sustancialmente el efecto de los eventos catastróficos. La versión de limitaciones de riesgo nodal, muestra que el corte de demanda equitativo (corte que se realiza nodo a nodo en proporción a la demanda conectada) se puede lograr en base a una correcta administración post-falla. Asimismo, los tiempos de cómputo son extremadamente bajos por lo que el modelo puede ser aplicado en sistemas complejos.