Recently, the widespread use of power system controllers, such as PSS and FACTS controllers, has led to the analysis of their effect on the overall stability of power systems. Many studies have been conducted to allocate FACTS controllers so that they achieve optimal power flow conditions in the context of Optimal Power Flow (OPF) analysis. However, these studies usually do not examine the effect of these controllers on the voltage and angle stability of the entire system, considering that the types of these controllers and their control signals, such as reactive power, current, or voltage, have significant effect on the entire system stability. <br /><br /> Due to the recent transition from government controlled to deregulated electricity markets, the relationship between power system controllers and electricity markets has added a new dimension, as the effect of these controllers on the overall power system stability has to be seen from an economic point of view. Studying the effect of adding and tuning these controllers on the pricing of electricity within the context of electricity markets is a significant and novel research area. Specifically, the link among stability, FACTS controllers and electricity pricing should be appropriately studied and modelled. <br /><br /> Consequently, in this thesis, the focus is on proposing and describing of a novel OPF technique which includes a new stability constraint. This technique is compared with respect to existent OPF techniques, demonstrating that it provides an appropriate modelling of system controllers, and thus a better understanding of their effects on system stability and energy pricing. The proposed OPF technique offers a new methodology for pricing the dynamic services provided by the system's controllers. Moreover, the new OPF technique can be used to develop a novel tuning methodology for PSS and FACTS controllers to optimize power dispatch and price levels, as guaranteeing an adequate level of system security. All tests and comparisons are illustrated using 3-bus and 14-bus benchmark systems.

Recently, the widespread use of power system controllers, such as PSS and FACTS controllers, has led to the analysis of their effect on the overall stability of power systems. Many studies have been conducted to allocate FACTS controllers so that they achieve optimal power flow conditions in the context of Optimal Power Flow (OPF) analysis. However, these studies usually do not examine the effect of these controllers on the voltage and angle stability of the entire system, considering that the types of these controllers and their control signals, such as reactive power, current, or voltage, have significant effect on the entire system stability. <br /><br /> Due to the recent transition from government controlled to deregulated electricity markets, the relationship between power system controllers and electricity markets has added a new dimension, as the effect of these controllers on the overall power system stability has to be seen from an economic point of view. Studying the effect of adding and tuning these controllers on the pricing of electricity within the context of electricity markets is a significant and novel research area. Specifically, the link among stability, FACTS controllers and electricity pricing should be appropriately studied and modelled. <br /><br /> Consequently, in this thesis, the focus is on proposing and describing of a novel OPF technique which includes a new stability constraint. This technique is compared with respect to existent OPF techniques, demonstrating that it provides an appropriate modelling of system controllers, and thus a better understanding of their effects on system stability and energy pricing. The proposed OPF technique offers a new methodology for pricing the dynamic services provided by the system's controllers. Moreover, the new OPF technique can be used to develop a novel tuning methodology for PSS and FACTS controllers to optimize power dispatch and price levels, as guaranteeing an adequate level of system security. All tests and comparisons are illustrated using 3-bus and 14-bus benchmark systems.

As open access market principles are applied to power systems, significant changes are happening in their planning, operation and control. In the emerging marketplace, systems are operating under higher loading conditions as markets focus greater attention to operating costs than stability and security margins. Since operating stability is a basic requirement for any power system, there is need for newer tools to ensure stability and security margins being strictly enforced in the competitive marketplace. This dissertation investigates issues associated with incorporating voltage security into the unbundled operating environment of electricity markets. It includes addressing voltage security in the monitoring, operational and planning horizons of restructured power system. This dissertation presents a new decomposition procedure to estimate voltage security usage by transactions. The procedure follows physical law and uses an index that can be monitored knowing the state of the system. The expression derived is based on composite market coordination models that have both PoolCo and OpCo transactions, in a shared stressed transmission grid. Our procedure is able to equitably distinguish the impacts of individual transactions on voltage stability, at load buses, in a simple and fast manner. This dissertation formulates a new voltage stability constrained optimal power flow (VSCOPF) using a simple voltage security index. In modern planning, composite power system reliability analysis that encompasses both adequacy and security issues is being developed. We have illustrated the applicability of our VSCOPF into composite reliability analysis. This dissertation also delves into the various applications of voltage security index. Increasingly, FACT devices are being used in restructured markets to mitigate a variety of operational problems. Their control effects on voltage security would be demonstrated using our VSCOPF procedure. Further, this dissertation investigates the application of steady state voltage stability index to detect potential dynamic voltage collapse. Finally, this dissertation examines developments in representation, standardization, communication and exchange of power system data. Power system data is the key input to all analytical engines for system operation, monitoring and control. Data exchange and dissemination could impact voltage security evaluation and therefore needs to be critically examined.

A power system with multiple interconnected areas needs to be operated coordinately for the purposes of the system reliability and economic operation, although each area has its own ISO under the market environment. In consolidation of different areas under a common grid coordinator, analysis of a power system becomes more computationally demanding. Furthermore, the analysis becomes more challenging because each area cannot obtain the network operating or economic data of other areas. This dissertation investigates decomposition algorithms for multi-area power system transfer capability analysis and economic dispatch analysis. All of the proposed algorithms assume that areas do not share their network operating and economic information among themselves, while they are willing to cooperate via a central coordinator for system wide analyses. The first proposed algorithm is based on power transfer distribution factors (PTDFs). A quadratic approximation, developed for the nonlinear PTDFs, is used to update tie-line power flows calculated by Repeated Power Flow (RPF). These tie-line power flows are then treated as injections in the TTC calculation of each area, as the central entity coordinates these results to determine the final system-wide TTC value. The second proposed algorithm is based on REI-type network equivalents. It uses the Continuation Power Flow (CPF) as the computational tool and, thus, the problem of voltage stability is considered in TTC studies. Each area uses REI equivalents of external areas to compute its TTC via the CPF. The choice and updating procedure for the continuation parameter employed by the CPF is implemented in a distributed but coordinated manner. The third proposed algorithm is based on inexact penalty functions. The traditional OPF is treated as the optimization problems with global variables. Quadratic penalty functions are used to relax the compatible constraints between the global variables and the local variables. The solution is proposed to be implemented by using a two-level computational architecture. All of the proposed algorithms are verified by numerical comparisons between the integrated and proposed decomposition algorithms. The proposed algorithms lead to potential gains in the computational efficiency with limited data exchanges among areas.

Electric power systems continue to increase in complexity because of the deployment of market mechanisms, the integration of renewable generation and distributed energy resources (DER) (e.g., wind and solar), the penetration of electric vehicles and other price sensitive loads. These revolutionary changes and the consequent increase in uncertainty and dynamicity call for significant modifications to power system operation models including unit commitment (UC), economic load dispatch (ELD) and optimal power flow (OPF). Planning and operation of these ???smart??? electric grids are expected to be impacted significantly, because of the intermittent nature of various supply and demand resources that have penetrated into the system with the recent advances. The main focus of this thesis is on the application of the Affine Arithmetic (AA) method to power system operational problems. The AA method is a very efficient and accurate tool to incorporate uncertainties, as it takes into account all the information amongst dependent variables, by considering their correlations, and hence provides less conservative bounds compared to the Interval Arithmetic (IA) method. Moreover, the AA method does not require assumptions to approximate the probability distribution function (pdf) of random variables. In order to take advantage of the AA method in power flow analysis problems, first a novel formulation of the power flow problem within an optimization framework that includes complementarity constraints is proposed. The power flow problem is formulated as a mixed complementarity problem (MCP), which can take advantage of robust and efficient state-of-the-art nonlinear programming (NLP) and complementarity problems solvers. Based on the proposed MCP formulation, it is formally demonstrated that the Newton-Raphson (NR) solution of the power flow problem is essentially a step of the traditional General Reduced Gradient (GRG) algorithm. The solution of the proposed MCP model is compared with the commonly used NR method using a variety of small-, medium-, and large-sized systems in order to examine the flexibility and robustness of this approach. The MCP-based approach is then used in a power flow problem under uncertainties, in order to obtain the operational ranges for the variables based on the AA method considering active and reactive power demand uncertainties. The proposed approach does not rely on the pdf of the uncertain variables and is therefore shown to be more efficient than the traditional solution methodologies, such as Monte Carlo Simulation (MCS). Also, because of the characteristics of the MCP-based method, the resulting bounds take into consideration the limits of real and reactive power generation. The thesis furthermore proposes a novel AA-based method to solve the OPF problem with uncertain generation sources and hence determine the operating margins of the thermal generators in systems under these conditions. In the AA-based OPF problem, all the state and control variables are treated in affine form, comprising a center value and the corresponding noise magnitudes, to represent forecast, model error, and other sources of uncertainty without the need to assume a pdf. The AA-based approach is benchmarked against the MCS-based intervals, and is shown to obtain bounds close to the ones obtained using the MCS method, although they are slightly more conservative. Furthermore, the proposed algorithm to solve the AA-based OPF problem is shown to be efficient as it does not need the pdf approximations of the random variables and does not rely on iterations to converge to a solution. The applicability of the suggested approach is tested on a large real European power system.

The purpose of the proposed research is to design a Decentralized Voltage/Stability Monitoring and Control System to counteract voltage violations and the impact of disturbances/contingencies on power system voltage stability. A decentralized voltage and stability control system is designed to coordinate the controls of the local secondary voltage control devices and necessary load shedding without requiring information about the rest of the system. The voltage/stability control can be formulated as a multi-objective optimization problem. The control objectives include, but are not limited to: minimization of system active/reactive losses; maximization of the system stability margin; and minimization of the control actions. The constraints of the optimization problem depend on the specifications of the actual system components. For the first time, margin sensitivities of the control actions are included in the control formulation. The concept of using margin sensitivity to evaluate the post-control load margin is presented as a fast and accurate way to assess potential voltage and stability control options. A system decomposition procedure is designed to define the disturbance-affected zone as an independent control subsystem. A normal constraint algorithm is adopted to identify the most suitable control solution in a shorter timeline than the typical utility voltage-control practice. Both steady-state and dynamic simulations are performed to compare the proposed system with typical utility control practices.

Submitted by DAISY PAES SILVA null (daisypaess@gmail.com) on 2016-05-18T15:43:23Z No. of bitstreams: 1 Dissertação.pdf: 3068870 bytes, checksum: d65c9a34405a8cb377b1440005b0fb11 (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-05-20T17:31:48Z (GMT) No. of bitstreams: 1 silva_dp_me_bauru.pdf: 3068870 bytes, checksum: d65c9a34405a8cb377b1440005b0fb11 (MD5) / Made available in DSpace on 2016-05-20T17:31:48Z (GMT). No. of bitstreams: 1 silva_dp_me_bauru.pdf: 3068870 bytes, checksum: d65c9a34405a8cb377b1440005b0fb11 (MD5) Previous issue date: 2016-03-29 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / O problema de Fluxo de Potência Ótimo (FPO) é considerado um importante problema da Engenharia Elétrica desde a década de 1960. A partir de então, muitos trabalhos foram publicados com diferentes formulações e abordagens para a resolução deste problema. Muitas destas abordagens desconsiderava a natureza discreta das variáveis de controle e consideram todas as variáveis do problema como contínuas. Estas formulações são aproximações do problema de FPO, pois, algumas variáveis podem somente ser ajustadas por passos discretos, conforme a realidade do sistema. No problema de Fluxo de Potência Ótimo Reativo (FPOR), caso particular do problema de FPO, as variáveis relacionadas à potência ativa são fixadas e a otimização somente considera as variáveis relacionadas à potência reativa. O problema de FPOR pode ser modelado matematicamente como um problema de programação não-linear com variáveis discretas e contínuas. Neste trabalho, propõem-se das abordagens para resolução do problema FPOR que consideram a natureza discreta das variáveis do problema. Nas abordagens propostas são utilizadas funções penalidade associadas a um método de pontos interiores, combinando as vantagens de ambos para a resolução do problema de FPOR. Desenvolvem-se funções penalidade polinomiais para tratar as variáveis de controle discretas do problema, taps dos transformadores e bancos de capacitores e de reatores shunt, obtendo-se uma sequência de problemas contínuos, diferenciáveis e penalizados, que são resolvidos pelo método de pontos interiores implementado no solver gratuito IPOPT. As soluções de tais problemas convergem para a solução do problema original. Os testes numéricos foram realizados com os sistemas elétricos IEEE 14, 30, 118 e 300 barras para verificar a eficiência das abordagens propostas. / The Optimal Power Flow Problem (OPF) is considered an important problem of the electrical engineering since the 1960s. From that moment, many papers were published with different formulations and approaches for solving this problem. Many of these approaches disregard the discrete nature of the control variables and consider all the variables of the problem as continuous. These formulations are approximations of the OPF problem, because some variables can be adjusted only by discrete steps, according to the system reality. In the Reactive Optimal Power Flow problem (ROPF), particular case of the OPF problem, the variables related to the active power are fixed and the optimization only considers the variables related to the reactive power. The ROPF problem can be mathematically modeled as a nonlinear programming problem with discrete and continuous variables. In this work, two approaches are presented for solving the ROPF problem considering the discrete nature of its variables. In the presented approaches, penalty functions are used associated with an interior-point method, combining the advantages of both for solving the ROPF problem. Polynomial penalty functions are used to treat the discrete control variables of the problem, transformers taps and shunt susceptances, obtaining a sequence of continuous, differentiable and penalized problems, which are solved by the interior-point method implemented in the IPOPT free solver. The solution of such problems converge to the solution of the original problem. The numerical tests were performed in the electrical systems IEEE 14, IEEE 30 and IEEE 118 buses to show the efficiency of the proposed methods. / CNPq: 130486/2014-0

[pt] Em alguns países, os sistemas de energia elétrica estão operando próximos aos seus limites devido à falta de investimentos para expansão da transmissão e crescimento natural da demanda de energia elétrica. Esta condição de operação também pode ocorrer em sistemas de potência nos quais a expansão da transmissão é realizada de forma adequada. Neste caso, o carregamento excessivo da rede de transmissão é geralmente originado pela perda de interligações que transportam grandes blocos de energia. Os dois cenários de operação descritos acima têm causado problemas de Estabilidade de Tensão em sistemas de energia elétrica. Os estados de instabilidade de tensão são caracterizados principalmente pela presença de dois mecanismos: a insolubilidade das equações de fluxo de potência e a perda de controlabilidade. Os distúrbios que originam estes dois mecanismos são de natureza aleatória. Conseqüentemente, os índices de estabilidade de tensão, usados para analisar a perda de controlabilidade e a insolubilidade, são variáveis aleatórias. Desta forma, a análise de estabilidade de tensão deveria reconhecer incertezas associadas com parâmetros da rede elétrica, tais como: flutuações de carga e disponibilidade dos equipamentos. Geralmente, a modelagem de incertezas na análise de estabilidade de tensão é realizada usando os seguintes métodos probabilísticos: a Simulação Monte Carlo e a Enumeração de Estados. O principal índice estimado por estes métodos é o risco de instabilidade de tensão. Entretanto, o cálculo do risco de instabilidade de tensão é geralmente realizado contabilizando apenas um dos mecanismos causadores dos cenários de instabilidade de tensão. Além disso, a severidade dos estados de instabilidade de tensão não tem sido devidamente investigada. O objetivo desta tese é desenvolver um método para realizar uma análise probabilística da estabilidade de tensão que contabilize os dois mecanismos causadores da instabilidade de tensão no cálculo do seu risco. Serão também propostos índices probabilísticos, baseados na Análise de Robustez, para expressar a severidade dos estados de instabilidade de tensão. O método proposto se baseia na combinação das seguintes técnicas: Enumeração de Estados, Simulação Monte Carlo, Método da Matriz D’ e Fluxo de Potência Ótimo Não-Linear. Os métodos de Enumeração de Estados e Simulação Monte Carlo são usados para selecionar os estados do sistema resultantes de falhas nos equipamentos e erros de previsão de carga. A identificação da perda de controlabilidade e a restauração da solubilidade dos estados selecionados são realizadas pelo Método da Matriz D’ e pelo Fluxo de Potência Ótimo, respectivamente. A combinação dos métodos citados acima foi usada para obter os seguintes índices probabilísticos: risco de instabilidade de tensão, valores esperados da margem de estabilidade de tensão para as barras, e probabilidades dos estados de robustez. Os resultados dos testes com o método proposto revelaram que as probabilidades de estados instáveis, associados aos dois mecanismos causadores da instabilidade de tensão, são bastante significativas. Adicionalmente, a Análise de Robustez permitiu identificar a causa raiz e a severidade dos problemas de instabilidade de tensão. / [en] In some countries, the electric power systems are operating near to their limits due to the absence of investments in the transmission network expansion and natural growth of the electricity demand. This operation condition can also occur in electric power systems in which the transmission expansion is carried out in appropriate way. In this case, the excessive loading of the transmission network is usually originated by the loss of interconnections that transport large energy blocks. The two operation scenarios described above have caused Voltage Stability problems in the electric power systems. The voltage instability states are mainly characterized by the presence of two mechanisms: the unsolvability of the power flow equations and the controllability loss. The disturbances that originate these two mechanisms are of stochastic nature. Consequently, the voltage instability indices, used to analyze the unsolvability and controllability loss, are random variables. In this way, the voltage stability assessment would recognize the uncertainties associated with the parameters of the electric network, for example: load fluctuations and equipment availability. Generally, the uncertainties modeling in the voltage stability is carried out using the following probabilistic methods: the Monte Carlo Simulation and the State Enumeration. The main index estimated by these methods is the voltage instability risk. However, the voltage instability risk evaluation is usually carried out considering only one of the mechanisms that cause voltage instability scenarios. Furthermore, the severity of the unstable states has not been properly investigated. The aim of this thesis is to develop a method to carry out a probabilistic assessment of the voltage stability that take into account the two mechanisms that cause the voltage instability in the evaluation of its risk. Probabilistic indices, based on Well-Being Analysis, are also proposed to express the severity of the voltage instability states. The proposed method is based on the combination of the following techniques: State Enumeration Method, Monte Carlo Simulation, D’ Matrix Method and Nonlinear Optimal Power Flow. The State Enumeration and Monte Carlo Simulation Methods are used to select the system states resulting of equipment failures and load forecast errors. The identification of the controllability loss and the solvability restoration of the power flow equations for the selected states are carried out by the D’ Matrix Method and by the Nonlinear Optimal Power Flow, respectively. The combination of the methods cited above was used to obtain the following probabilistic indices: voltage instability risk, expected value of the voltage instability margin for the buses, and Well-Being states probabilities. The results of the tests with the proposed method revealed that the probabilities of unstable states, associated with the two voltage instability mechanism, are very significant. Additionally, the Well-Being Analysis was able to identify the root cause and the severity of the voltage instability problems.

Orientador: Prof. Dr. Edmarcio Antonio Belati / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2015. / Este trabalho visa à operação ótima de um sistema de energia elétrica com a presença de aerogeradores. Considerando as injeções de potência ativa e reativa para a geração eólica, será analisado o comportamento da rede por meio de um Fluxo de Potência Ótimo Multiobjetivo (FPO - MO). A metodologia consiste na modelagem da rede elétrica, inserindo as características do gerador eólico na formulação do FPO - MO, objetivando minimizar as perdas ativas em conjunto com o perfil de tensão por meio do despacho ótimo de potência ativa e reativa. O problema modelado como um FPO - MO reativo é resolvido com auxilio do AMPL (Modeling Language for Mathematical Programming) e do solver Knitro. Estudos realizados com os sistemas IEEE de 14, 30, 57 e 118 barras evidenciam os benefícios da utilização da geração eólica aliada ao FPO - MO. / This approach aims optimal operation of power system with wind turbines. Considering the active and reactive power injections for wind generation, network behavior is analyzed using a multi-objective Optimal Power Flow (OPF - MO). The methodology consists in modeling the electrical network by entering characteristics of wind generator in the formulation of the FPO - MO, aiming to minimize active power losses in conjunction with the voltage profile through the optimal dispatch of active and reactive power. The problem modeled as a FPO - MO reactive is solved with the aid of AMPL (Modeling Language for Mathematical Programming) and Knitro solver. Studies with the IEEE 14, 30, 57 and 118 modified system show the benefits of using wind power combined with the FPO - MO.

Orientador: Prof. Dr. Haroldo de Faria Junior / This dissertation presents a planning methodology to reduce emissions of greenhouse gases, applicable in active distribution networks, using renewable distributed generation and new control strategies. The studies done had as main objective the development of a methodology, applicable in distribution networks with feature of generation and variable load, to reduce emissions of greenhouse gases derived from electricity generation activities. The developed optimization methodology was based on the formulation of a AC optimal power flow (OPF) problem, integrating the new strategy of active networks management (ANM) that contains schemes such as coordinated voltage control (CVC), adaptive power factor control (PFC) and energy curtailment (EC). To solve the optimization problem, the modeling and optimization software AIMMS was used. The results show that significant reduction of greenhouse gas emissions can be achieved through the connection of renewable distributed generation in active distribution networks compared to passive networks. / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2015. / Nesta dissertação apresenta-se uma metodologia de planejamento para redução de emissões de gases de efeito estufa, aplicável em redes de distribuição ativas, usando geração distribuída renovável e novas estratégias de controle. Os estudos feitos tiveram como objetivo principal o desenvolvimento de uma metodologia, aplicável em redes de distribuição com característica de geração e carga variável, para reduzir emissões de gases de efeito estufa derivados das atividades de geração de energia elétrica. A metodologia de otimização desenvolvida foi baseada na formulação de um problema de fluxo de potência ótimo (FPO) AC multi-período integrando a nova estratégia de gestão de redes ativas (GRA), que contém esquemas como o controle de tensão coordenado (CVC), controle de fator de potência adaptativo (CFPA) e redução de energia (RE). Para resolver o problema de otimização, foi utilizado o programa computacional de modelagem e otimização AIMMS. Os resultados mostram que reduções significativas de emissões de gases de efeito estufa podem ser alcançadas mediante a ligação de geração distribuída renovável em redes de distribuição ativas em comparação com redes passivas.