This thesis primarily focuses on studying the impact of Distributed Generation (DG) on the electromechanical transients in the electric grid (distribution, transmission or combined transmission and distribution (TandD) systems) using a Three Phase Dynamics Analyzer (hereafter referred to as TPDA). TPDA includes dynamic models for electric machines, their controllers, and a three-phase model of the electric grid, and performs three-phase dynamic simulations without assuming a positive sequence network model. As a result, TPDA can be used for more accurate investigation of electromechanical transients in the electric grid in the presence of imbalances. At present, the Electromagnetic Transient Program (EMTP) software can be used to perform three-phase dynamic simulations. This software models the differential equations of the entire electric network along with those of the machines. This calls for solving differential equations with time constants in the order of milliseconds (representing the fast electric network) in tandem with differential equations with time constants in the order of seconds (representing the slower electromechanical machines). This results in a stiff set of differential equations, making such an analysis extremely time consuming. For the purpose of electromechanical transient analysis, TPDA exploits the difference in the order of time constants and adopts phasor analysis of the electric network, solving differential equations only for the equipment whose dynamics are much slower than those of the electric network. Power Flow equations are solved using a graph trace analysis based approach which, along with the explicit partitioned method adopted in TPDA, can eventually lead to the use of distributed computing that will further enhance the speed of TPDA and perhaps enable it to perform dynamic simulation in real time . In the work presented here, first an overview of the methodology behind TPDA is provided. A description of the object oriented implementation of TPDA in C++/C# is included. Subsequently, TPDA is shown to accurately simulate power system dynamics of balanced networks by comparing its results against those obtained using GE-PSLF®. This is followed by an analysis that demonstrates the advantages of using TPDA by highlighting the differences in results when the same problem is analyzed using a three-phase network model with unbalances and the positive sequence network model as used in GE-PSLF®. Finally, the impact of rapidly varying DG generation is analyzed, and it is shown that as the penetration level of DG increases, the current and voltage oscillations throughout the transmission network increase as well. Further, rotor speed deviations are shown to grow proportionally with increasing DG penetration. / Master of Science

[pt] Para simular, prever e controlar os sistemas de energia elétrica, engenheiros precisam de ferramentas computacionais para modelar os componentes dessa rede interconectada altamente complexa. Muitos esforços ao longo do século passado foram dedicados a desenvolver modelos matemáticos para geradores, linhas de transmissão, compensadores de potência reativa, transformadores e assim por diante. Os principais componentes dos sistemas de potência são representados precisamente através de modelos matemáticos, mas as cargas ainda são uma fonte de incerteza nas simulações, devido à sua característica de aleatoriedade. Modelos de carga conservadores superestimam a resposta de potência a desvios de tensão, enquanto modelos de carga excessivamente otimistas podem subestimar as margens de estabilidade, deixando o sistema muito próximo do seu limite operacional. É preciso estabelecer representações de cargas tão próximas da realidade quanto possível, a fim de explorar os recursos de rede de modo mais eficiente. Este trabalho fornece uma metodologia para modelagem de carga, investigando e resumindo as etapas do processo, que podem ser implementadas de diversas maneiras. O tratamento de dados, a escolha de uma representação matemática do modelo de carga e sua estimação de parâmetros são apresentados através de estudos de caso reais, tanto para uma aplicação focada na dinâmica do sistema elétrica, quanto para uma aplicação em regime permanente. Discute-se como otimização e conceitos de inferência estatística podem ser ferramentas efetivas para alcançar melhores aproximações sobre como a carga responderá a perturbações causadas por variações de tensão, sejam estas variações espontâneas, ou devido a ações de controle, ou causadas por curtos-circuitos. / [en] To simulate, predict and control Electric Power Systems (EPS), engineers need tools to model the components of this highly complex interconnected network. Many efforts over the past century were dedicated to develop mathematical models for generators, transmission lines, reactive power compensators, transformers and so on. The main components of the power systems are precisely represented by mathematical models, but the loads are still a source of uncertainty in the simulations, due to their random characteristics. It is well known that conservative load models super estimate power response to voltage deviations, and, on the other hand, over-optimistic load models may underestimate stability margins, leading a system to operate too close to its limit. It is necessary to stablish load representations as close to reality as possible, in order to fully exploit grid resources. This work provides a methodology for load modeling, investigating and summarizing the steps of the process, whose can be implemented in a wide variety of ways. Data treatment, the choice of a load model representation and their parameters estimation are presented through real case studies, both for dynamic simulation and a steady state application. It is discussed how optimization and statistical inference concepts can be effective tools to reach better approximations on how load will respond to disturbances caused by voltage variations, whether these were spontaneous, due to control actions, or caused by short-circuits.