O presente trabalho visa a investigação e o desenvolvimento de estratégias de otimização contínua e discreta para problemas de Fluxo de Potência Ótimo com Restrições de Segurança (FPORS) Multiobjetivo, incorporando variáveis de controle associadas a taps de transformadores em fase, chaveamentos de bancos de capacitores e reatores shunt. Um modelo Problema de Otimização Multiobjetivo (POM) é formulado segundo a soma ponderada, cujos objetivos são a minimização de perdas ativas nas linhas de transmissão e de um termo adicional que proporciona uma maior margem de reativos ao sistema. Investiga-se a incorporação de controles associados a taps e shunts como grandezas fixas, ou variáveis contínuas e discretas, sendo neste último caso aplicadas funções auxiliares do tipo polinomial e senoidal, para fins de discretização. O problema completo é resolvido via meta-heurísticas Evolutionary Particle Swarm Optimization (EPSO) e Differential Evolutionary Particle Swarm Optimization (DEEPSO). Os algoritmos foram desenvolvidos utilizando o software MatLab R2013a, sendo a metodologia aplicada aos sistemas IEEE de 14, 30, 57, 118 e 300 barras e validada sob os prismas diversidade e qualidade das soluções geradas e complexidade computacional. Os resultados obtidos demonstram o potencial do modelo e estratégias de resolução propostas como ferramentas auxiliares ao processo de tomada de decisão em Análise de Segurança de redes elétricas, maximizando as possibilidades de ação visando a redução de emergências pós-contingência. / The goal of the present work is to investigate and develop continuous and discrete optimization strategies for SCOPF problems, also taking into account control variables related to in-phase transformers, capacitor banks and shunt reactors. Multiobjective optimization model is formulated under a weighted sum criteria whose objectives are the minimization of active power losses and an additional term that yields a greater reactive support to the system. Controls associated with taps and shunts are modeled either as fixed quantities, or continuous and discrete variables, in which case auxiliary functions of polynomial and sinusoidal types are applied for discretization purposes. The complete model is solved via EPSO and DEEPSO metaheuristics. Routines coded in Matlab were applied to the IEEE 14,30, 57, 118 and 300-bus test systems, where the method was validated in terms of diversity and quality of solutions and computational complexity. The results demonstrate the robustness of the model and solution approaches and uphold it as an effective support tool for the decision-making process in Power Systems Security Analysis, maximizing preventive actions in order to avoid insecure operating conditions.

O presente trabalho visa a investigação e o desenvolvimento de estratégias de otimização contínua e discreta para problemas de Fluxo de Potência Ótimo com Restrições de Segurança (FPORS) Multiobjetivo, incorporando variáveis de controle associadas a taps de transformadores em fase, chaveamentos de bancos de capacitores e reatores shunt. Um modelo Problema de Otimização Multiobjetivo (POM) é formulado segundo a soma ponderada, cujos objetivos são a minimização de perdas ativas nas linhas de transmissão e de um termo adicional que proporciona uma maior margem de reativos ao sistema. Investiga-se a incorporação de controles associados a taps e shunts como grandezas fixas, ou variáveis contínuas e discretas, sendo neste último caso aplicadas funções auxiliares do tipo polinomial e senoidal, para fins de discretização. O problema completo é resolvido via meta-heurísticas Evolutionary Particle Swarm Optimization (EPSO) e Differential Evolutionary Particle Swarm Optimization (DEEPSO). Os algoritmos foram desenvolvidos utilizando o software MatLab R2013a, sendo a metodologia aplicada aos sistemas IEEE de 14, 30, 57, 118 e 300 barras e validada sob os prismas diversidade e qualidade das soluções geradas e complexidade computacional. Os resultados obtidos demonstram o potencial do modelo e estratégias de resolução propostas como ferramentas auxiliares ao processo de tomada de decisão em Análise de Segurança de redes elétricas, maximizando as possibilidades de ação visando a redução de emergências pós-contingência. / The goal of the present work is to investigate and develop continuous and discrete optimization strategies for SCOPF problems, also taking into account control variables related to in-phase transformers, capacitor banks and shunt reactors. Multiobjective optimization model is formulated under a weighted sum criteria whose objectives are the minimization of active power losses and an additional term that yields a greater reactive support to the system. Controls associated with taps and shunts are modeled either as fixed quantities, or continuous and discrete variables, in which case auxiliary functions of polynomial and sinusoidal types are applied for discretization purposes. The complete model is solved via EPSO and DEEPSO metaheuristics. Routines coded in Matlab were applied to the IEEE 14,30, 57, 118 and 300-bus test systems, where the method was validated in terms of diversity and quality of solutions and computational complexity. The results demonstrate the robustness of the model and solution approaches and uphold it as an effective support tool for the decision-making process in Power Systems Security Analysis, maximizing preventive actions in order to avoid insecure operating conditions.

Notre société étant plus dépendante que jamais au vecteur électrique, la moindre perturbation du transport ou de l’acheminement de l’électricité a un impact social et économique important. La fiabilité et la sécurité des réseaux électriques sont donc cruciales pour les gestionnaires de réseaux, en plus des aspects économiques. De plus, les réseaux de transport sont interconnectés pour réduire les coûts des opérations et pour améliorer la sécurité. Un des plus grand défis des gestionnaires des réseaux de transport est ainsi de se coordonner avec les réseaux voisins, ce qui soulève des problèmes liés à la taille du problème, à l’interopérabilité et à la confidentialité des données.Cette thèse se focalise principalement sur la sécurité des opérations sur les réseaux électriques, c’est pourquoi l’évolution des principales caractéristiques des blackouts, qui sont des échecs de la sécurité des réseaux, sont étudiés sur la période 2005-2016. L’approche de cette étude consiste à déterminer quelles sont les principales caractéristiques des incidents de ces 10 dernières années, afin d’identifier ce qui devrait être intégré pour réduire le risque que ces incidents se reproduisent. L’évolution a été étudiée et comparé avec les caractéristiques des blackouts qui se sont produit avant 2005. L’étude se focalise sur les préconditions qui ont mené à ces blackouts et sur les cascades, et particulièrement sur le rôle de la vitesse des cascades. Les caractéristiques importante sont extraites et intégrées dans la suite de notre travail.Un algorithme résolvant un problème préventif d’Optimal Power Flow avec contraintes de sécurité (SCOPF) de manière distribuée est ainsi développé. Ce problème consiste en l’ajout de contraintes qui assure qu’après la perte de n’importe quel appareil d’importance, le nouveau point d’équilibre, atteint suite au réglage primaire en fréquence, respecte les contraintes du système. L’algorithme développé utilise une décomposition fine du problème et est implémenté sous le paradigme multi-agent, basé sur deux catégories d’agents : les appareils et les bus. Les agents sont coordonnés grâce à l’ « Alternating Direction Method of Multipliers (ADMM)» et grâce à un problème de consensus. Cette décomposition procure l’autonomie et la confidentialité nécessaire aux différents acteurs du système, mais aussi, un bon passage à l’échelle par rapport à la taille du problème. Cet algorithme a aussi pour avantage d’être robuste à n’importe quelle perturbation, incluant la séparation du système en plusieurs régions.Puis, pour prendre en compte l’incertitude sur la production créée par les erreurs de prédiction des fermes éoliennes, une approche distribuée à deux étapes est développée pour résoudre un problème d’Optimal Power Flow avec contraintes probabilistes (CCOPF), d’une manière complétement distribuée. Les erreurs de prédiction des fermes éoliennes sont modélisées par des lois normales indépendantes et les écarts par rapport aux plannings de production sont considérés compensés par le réglage primaire en fréquence. La première étape de l’algorithme a pour but de déterminer des paramètres de sensibilités nécessaires pour formuler le problème. Les résultats de cette étape sont ensuite des paramètres d’entrée de la seconde étape qui, elle, résout le problème de CCOPF. Une extension de cette formulation permet d’ajouter de la flexibilité au problème en permettant la réduction de la production éolienne. Cet algorithme est basé sur la même décomposition fine que précédemment où les agents sont également coordonnés par l’ADMM et grâce à un problème de consensus. En conclusion, cet algorithme en deux étapes garantit la confidentialité et l’autonomie des différents acteurs, et est parallèle et adaptée aux plateformes hautes performances. / Our societies are more dependent on electricity than ever, thus any disturbance in the power transmission and delivery has major economic and social impact. The reliability and security of power systems are then crucial to keep, for power system operators, in addition to minimizing the system operating cost. Moreover, transmission systems are interconnected to decrease the cost of operation and improve the system security. One of the main challenges for transmission system operators is therefore to coordinate with interconnected power systems, which raises scalability, interoperability and privacy issues. Hence, this thesis is concerned with how TSOs can operate their networks in a decentralized way but coordinating their operation with other neighboring TSOs to find a cost-effective scheduling that is globally secure.The main focus of this thesis is the security of power systems, this is why the evolution of the main characteristics of the blackouts that are failures in power system security, of the period 2005-2016 is studied. The approach consists in determining what the major characteristics of the incidents of the past 10 years are, to identify what should be taken into account to mitigate the risk of incidents. The evolution have been studied and compared with the characteristics of the blackouts before 2005. The study focuses on the pre-conditions that led to those blackouts and on the cascades, and especially the role of the cascade speed. Some important features are extracted and later integrated in our work.An algorithm that solve the preventive Security Constrained Optimal Power Flow (SCOPF) problem in a fully distributed manner, is thus developed. The preventive SCOPF problem consists in adding constraints that ensure that, after the loss of any major device of the system, the new steady-state reached, as a result of the primary frequency control, does not violate any constraint. The developed algorithm uses a fine-grained decomposition and is implemented under the multi-agent system paradigm based on two categories of agents: devices and buses. The agents are coordinated with the Alternating Direction method of multipliers in conjunction with a consensus problem. This decomposition provides the autonomy and privacy to the different actors of the system and the fine-grained decomposition allows to take the most of the decomposition and provides a good scalability regarding the size of the problem. This algorithm also have the advantage of being robust to any disturbance of the system, including the separation of the system into regions.Then, to account for the uncertainty of production brought by wind farms forecast error, a two-step distributed approach is developed to solve the Chance-Constrained Optimal Power Flow problem, in a fully distributed manner. The wind farms forecast errors are modeled by independent Gaussian distributions and the mismatches with the initials are assumed to be compensated by the primary frequency response of generators. The first step of this algorithm aims at determining the sensitivity factors of the system, needed to formulate the problem. The results of this first step are inputs of the second step that is the CCOPF. An extension of this formulation provides more flexibility to the problem and consists in including the possibility to curtail the wind farms. This algorithm relies on the same fine-grained decomposition where the agents are again coordinated by the ADMM and a consensus problem. In conclusion, this two-step algorithm ensures the privacy and autonomy of the different system actors and it is de facto parallel and adapted to high performance platforms.

Submitted by Augusto Cesar Pereira (augusto.pereira@feb.unesp.br) on 2017-12-20T09:42:45Z No. of bitstreams: 1 Dissertação_Augusto_Repositorio.pdf: 2651783 bytes, checksum: 084f19f166b7161411ec58baa4ecf206 (MD5) / Approved for entry into archive by Maria Marlene Zaniboni null (zaniboni@bauru.unesp.br) on 2017-12-20T10:54:46Z (GMT) No. of bitstreams: 1 pereira_ac_me_bauru.pdf: 2651783 bytes, checksum: 084f19f166b7161411ec58baa4ecf206 (MD5) / Made available in DSpace on 2017-12-20T10:54:46Z (GMT). No. of bitstreams: 1 pereira_ac_me_bauru.pdf: 2651783 bytes, checksum: 084f19f166b7161411ec58baa4ecf206 (MD5) Previous issue date: 2017-12-18 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Este trabalho propõe um modelo de Procedimento de Equilíbrio de Mercado com Restrições de Segurança Estocásticas (PEMRSE) que pode ser utilizado como um modelo de leilão de energia e reserva do dia seguinte por operadores de sistemas hidrotérmicos. O modelo de PEMRSE tem o objetivo de minimizar o custo esperado da operação, considerando os custos associados aos excedentes de geração e consumo, partidas, contratação de reservas e a penalização econômica associada aos cortes involuntários de carga. O PEMRSE considera vários aspectos que dificultam a resolução de problemas de leilão: i) representação detalhada dos sistemas de geração hidrelétrico e termelétrico; ii) perdas na transmissão; e iii) restrições de segurança pré e pós-contingência. São propostas técnicas de linearização que não demandam o uso de variáveis binárias para a função de produção hidráulica e para as funções de potência e engolimento máximo de geradores hidrelétricos. A estrutura estocástica permite cortes involuntários de carga, isto é, o operador pode optar por não contratar a totalidade das reservas necessárias para cobrir as falhas associadas às contingências, ponderando sua decisão pela probabilidade de ocorrência destas falhas e pelo valor da penalização econômica associada ao corte de carga. Propõe-se também uma técnica para a resolução de modelos de PEMRSE em tempos computacionais menores com relação à sua resolução direta. Simulações em um sistema-teste de três barras e no sistema IEEE de 24 barras evidenciam a eficiência do modelo, das técnicas de linearização e da técnica de resolução propostos. As simulações também mostram os impactos dos aspectos complicadores nos resultados do leilão e no tempo computacional de resolução. O modelo de PEMRSE proposto pode ser resolvido de maneira eficiente por meio de pacotes computacionais disponíveis comercialmente por meio da técnica de resolução proposta. / This work proposes a Market Clearing Procedure with Stochastic Security Constraints (MCPSSC) model that can be used as an energy and reserve day-ahead auction model by hydrothermal systems operators. The MCPSSC aims to minimize the expected cost of the operation, considering the costs associated with the generation and consumption surpluses, start-ups, contracting of reserves and the economic penalization associated with involuntary load shedding events. The MCPSSC model considers several aspects that complicate the resolution of auction problems: i) detailed representation of the hydrothermal generating systems; ii) transmission losses; and iii) pre- and post-contingency security constraints. We propose linearization techniques that does not require the use of binary variables for the hydro production function and for the maximum power output and maximum water discharge functions of hydro generators. The stochastic structure allows some load shedding, ie, the operator can choose not to contract the total reserve requirements to cover the failures associated with the contingencies, weighting its decision by the probability of occurrence of these failures and by the value of lost load. We also propose a technique for the resolution of MCPSSC models in lower computational times regarding its direct resolution. Simulations in a three-bus test system and in the IEEE 24-bus system show the efficiency of the model, the linearization techniques and the resolution technique proposed. The simulations also show the the impact of the complicating aspects in the auction outcomes and in the computational time. The proposed MCPSSC model can be efficiently solved by commercially available solvers by means of the proposed resolution technique.

Orientador: Edméa Cássia Baptista / Resumo: O problema de maximização da margem de carregamento operacional tem por finalidade determinar a maior demanda de carga em um sistema elétrico de potência que satisfaça todas as restrições operacionais do sistema e de equipamentos. Em linhas gerais, conhecer com precisão a máxima demanda de potência ativa e reativa suportada pelo sistema elétrico de potência para que o mesmo opere em condições satisfatórias é uma informação importante para a operação e planejamento do sistema. Muitos trabalhos, da literatura, formulam o problema de máximo carregamento através de um modelo de otimização contínuo, e mais recentemente, alguns trabalhos apresentam modelos que também passaram a levar em consideração o fator de potência da demanda das barras de carga. Neste trabalho propõe-se um modelo para o problema de máximo carregamento baseado no fator de potência de demanda ajustável e levando em consideração restrições de segurança. O problema de maximização da margem de carregamento operacional será formulado como um problema de programação não linear, não convexo de grande porte com variáveis contínuas e visa maximizar o somatório de potências ativas demandadas pelas barras de carga, respeitando um fator de potência mínimo pré-estabelecidos e restrições de segurança pós-contingência. Destaca-se que uma contribuição do trabalho é que o modelo encontre para o sistema um ponto de operação factível na presença de contingências pré-definidas, além disso, respeita os limites físicos e operacionai... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The problem of maximizing the operating load margin aims to determine the highest load demand in an electrical power system that satisfies all operational constraints of the system and equipment. In general, knowing precisely the maximum demand for active and reactive power supported by the electrical power system, in order that it operates in satisfactory conditions, is an important information for the operation and planning of the system. Many works in the literature formulate the problem of maximum loading through a continuous optimization model, and more recently, some works present models that also started to take into account the power factor of the load bars demand. This work proposes a model for the maximum load problem based on the adjustable demand power factor, taking into account security constraints. The problem of maximizing the operating load margin will be formulated as a non-linear, non-convex large programming problem with continuous variables and aims to maximize the sum of active powers demanded by the load bars, respecting an established minimum power factor and post-contingency security constraints. It is important to highlight that the model also ensures that the system finds a feasible operating point, even in the presence of predefined contingencies, besides; it respects the physical and operational limits provided for in the traditional Optimal Power Flow. The proposed model was tested for the IEEE 14, 30, 118 bus systems, simulated on the GAMS platf... (Complete abstract click electronic access below) / Doutor