The contributions of the research are (a) an infrastructure of data acquisition systems that provides the necessary information for an automated EMS system enabling autonomous distributed state estimation, model validation, simplified protection, and seamless integration of other EMS applications, (b) an object-oriented, interoperable, and unified component model that can be seamlessly integrated with a variety of applications of the EMS, (c) a distributed dynamic state estimator (DDSE) based on the proposed data acquisition system and the object-oriented, interoperable, and unified component model, (d) a physically-based synchronous machine model, which is expressed in terms of the actual self and mutual inductances of the synchronous machine windings as a function of rotor position, for the purpose of synchronous machine parameters identification, and (e) a robust and highly efficient algorithm for the optimal power flow (OPF) problem, one of the most important applications of the EMS, based on the validated states and models of the power system provided by the proposed DDSE.

This thesis is based on studies of the deregulated electricity markets located in the United States of America. The problem statement of the thesis evolved continuously throughout our initial period of research. Focus was finally put on monitoring and detection of potential market power caused by congestion in the transmission network. The existence of market power is a serious concern in today’s electric energy markets. A system that monitors the trading is needed and much research and many proposals on how to deal with this problem have been introduced over the years. We focus on some of these approaches and develop an approach of our own, which we call “Monopolistic Energy Calculation”. We adopt the idea to identify participants with the ability to raise prices without losing market share. An ability that should not be present on a competitive market. We take this idea further by identifying participants with the ability to make considerable price raises without losing all market shares. We propose a way to calculate the remaining market shares (Monopolistic Energy Levels) after a large price raise. These calculated levels of energy, that are only deliverable by a certain participant or by a certain group of participants, are caused by the active congestions in the network. The approach detects the amounts of these energy levels and the location in the network at which they are present. This is a prospective method if used with a prediction of the following day’s demand, which is regularly available with high accuracy. The method can also be used for monitoring purposes to identify critical situations in real-time. The method is implemented and two sets of simulations are done in which we explain and evaluate the approach. The results are promising and the correlation between “Monopolistic Energy” and market power is confirmed. / Detta examensarbete är baserat på studier av de deregulerade electricitsmarknaderna i USA. Problemformuleringen var i början av detta arbete inte definitiv, utan utvecklades under en längre inledande fas av forskningsarbete. Slutligen kunde vi faställa att detektion av potentiell marknadskraft på elektricitetsmarknaden, orsakat av överbelastningar i transmissionnätverket, var av särskilt intresse. Ett system som övervakar handeln och förekomster av orättvisor orsakat av detta är nödvändigt. Det har de senaste åren gjorts mycket forskning inom detta område. Baserat på denna forskning utvecklades sedan ett eget förslag, som vi kallar ”Monopolistic Energy Calculations”. Vissa tidigare förslag på hur problemet kan angripas blev av särskilt intresse. En idé från dessa var att identifiera marknadsaktörer med förmågan att höja priser utan att förlora marknadsandelar, en icke önskvärd egenskap hos aktörer då en konkurrenskraftig marknad är eftertraktad. Vi tar denna idé ett steg längre genom att identifiera marknadsaktörer med förmågan att höja priser signifikant utan att förlora alla marknadsandelar. Vi föreslår ett sätt att beräkna dessa energinivåer som endast är möjliga att levereras av en eller ett fåtal särskilda aktörer, som direkt följd av de aktiva stockningarna i nätverket, under antagandet av en inelastisk efterfrågan. Vi föreslår ett sätt att beräkna de återstående marknadsandelarna (Monopolistic Energy Levels) efter en stor prishöjning. Vår metod beräknar mängden av denna energi och var i nätverket dessa mängder förekommer. Denna metod kan sia om framtida problem om en estimering av morgondagens efterfråga används. Sådana estimeringar görs idag regelbundet med hög träffsäkerhet. Metoden kan även användas i realtid för upptäckt av kritiska marknadssituationer. Simuleringar av detta görs som förklarar vår lösning och utvärderar den. Resultaten är lovande och korrelationen mellan ”Monopolistisk Energi” och marknadskraft är bekräftade.

The deployment of Renewable Energy (RE)-based generation has experienced a sustained global growth in the recent decades, driven by many countries' interest in reducing greenhouse gas emissions and dependence on fossil fuel for electricity generation. This trend is also observed in remote off-grid systems (isolated microgrids), where local communities, in an attempt to reduce fossil fuel dependency and associated economic and environmental costs, and to increase availability of electricity, are favouring the installation of RE-based generation. This practice has posed several challenges to the operation of such systems, due to the intermittent and hard-to-predict nature of RE sources. In particular, this thesis addresses the problem of reliable and economic dispatch of isolated microgrids, also known as the energy management problem, considering the uncertain nature of those RE sources, as well as loads. Isolated microgrids feature characteristics similar to those of distribution systems, in terms of unbalanced power flows, significant voltage drops and high power losses. For this reason, detailed three-phase mathematical models of the microgrid system and components are presented here, in order to account for the impact of unbalanced system conditions on the optimal operation of the microgrid. Also, simplified three-phase models of Distributed Energy Resources (DERs) are developed to reduce the level of complexity in small units that have limited impact on the optimal operation of the system, thus reducing the number of equations and variables of the problem. The proposed mathematical models are then used to formulate a novel energy management problem for isolated microgrids, as a deterministic, multi-period, Mixed-Integer Nonlinear Programming (MINLP) problem. The multi-period formulation allows for a proper management of energy storage resources and multi-period constraints associated with the commitment decisions of DERs. In order to obtain solutions of the energy management problem in reasonable computational times for real-time, realistic applications, and to address the uncertainty issues, the proposed MINLP formulation is decomposed into a Mixed-Integer Linear Programming (MILP) problem, and a Nonlinear programming (NLP) problem, in the context of a Model Predictive Control (MPC) approach. The MILP formulation determines the unit commitment decisions of DERs using a simplified model of the network, whereas the NLP formulation calculates the detailed three-phase dispatch of the units, knowing the commitment status. A feedback signal is generated by the NLP if additional units are required to correct reactive power problems in the microgrid, triggering a new calculation MINLP problem. The proposed decomposition and calculation routines are used to design a new deterministic Energy Management System (EMS) based on the MPC approach to handle uncertainties; hence, the proposed deterministic EMS is able to handle multi-period constraints, and account for the impact of future system conditions in the current operation of the microgrid. In the proposed methodology, uncertainty associated with the load and RE-based generation is indirectly considered in the EMS by continuously updating the optimal dispatch solution (with a given time-step), based on the most updated information available from suitable forecasting systems. For a more direct modelling of uncertainty in the problem formulation, the MILP part of the energy management problem is re-formulated as a two-stage Stochastic Programming (SP) problem. The proposed novel SP formulation considers that uncertainty can be properly modelled using a finite set of scenarios, which are generated using both a statistical ensembles scenario generation technique and historical data. Using the proposed SP formulation of the MILP problem, the deterministic EMS design is adjusted to produce a novel stochastic EMS. The proposed EMS design is tested in a large, realistic, medium-voltage isolated microgrid test system. For the deterministic case, the results demonstrate the important connection between the microgrid's imbalance, reactive power requirements and optimal dispatch, justifying the need for detailed three-phase models for EMS applications in isolated microgrids. For the stochastic studies, the results show the advantages of using a stochastic MILP formulation to account for uncertainties associated with RE sources, and optimally accommodate system reserves. The computational times in all simulated cases show the feasibility of applying the proposed techniques to real-time, autonomous dispatch of isolated microgrids with variable RE sources.

Power flow (PF) control can increase the utilization of the transmission system and connect lower cost generation with load. While PF controllers have demonstrated the ability to realize dynamic PF control for more than 25 years, PF control has been sparsely implemented. This research re-examines PF control in light of the recent development of fractionally-rated PF controllers and the incremental power flow (IPF) control concept. IPF control is the transfer of an incremental quantity of power from a specified source bus to specified destination bus along a specified path without influencing power flows on circuits outside of the path. The objectives of the research are to develop power system operation and planning methods compatible with IPF control, test the technical viability of IPF control, develop transmission planning frameworks leveraging PF and IPF control, develop power system operation and planning tools compatible with PF control, and quantify the impacts of PF and IPF control on multi-decade transmission planning. The results suggest that planning and operation of the power system are feasible with PF controllers and may lead to cost savings. The proposed planning frameworks may incent transmission investment and be compatible with the existing transmission planning process. If the results of the planning tool demonstration scale to the national level, the annual savings in electricity expenditures would be $13 billion per year (2010$). The proposed incremental packetized energy concept may facilitate a reduction in the environmental impact of energy consumption and lead to additional cost savings.

Optimal transmission switching (OTS) enables us to remove selected transmission lines from service as a cost reduction method. A mixed integer programming (MIP) model has been proposed to solve the OTS problem based on the direct current optimal power flow (DCOPF) approximation. Previous studies indicated computational issues regarding the OTS problem and the need for a more accurate model. In order to resolve computational issues, especially in large real systems, the MIP model has been followed by some heuristics to find good, near optimal, solutions in a reasonable time. The line removal recommendations based on DCOPF approximations may result in poor choices to remove from service. We assess the quality of line removal recommendations that rely on DCOPF-based heuristics, by estimating actual cost reduction with the exact alternating current optimal power flow (ACOPF) model, using the IEEE 118-bus test system. We also define an ACOPF-based line-ranking procedure and compare the quality of its recommendations to those of a previously published DCOPF-based procedure. For the 118-bus system, the DCOPF-based line ranking produces poor quality results, especially when demand and congestion are very high, while the ACOPF-based heuristic produces very good quality recommendations for line removals, at the expense of much longer computation times. There is a need for approximations to the ACOPF that are accurate enough to produce good results for OTS heuristics, but fast enough for practical use for OTS decisions.

abstract: The electric transmission grid is conventionally treated as a fixed asset and is operated around a single topology. Though several instances of switching transmission lines for corrective mechaism, congestion management, and minimization of losses can be found in literature, the idea of co-optimizing transmission with generation dispatch has not been widely investigated. Network topology optimization exploits the redundancies that are an integral part of the network to allow for improvement in dispatch efficiency. Although, the concept of a dispatchable network initially appears counterintuitive questioning the wisdom of switching transmission lines on a more regu-lar basis, results obtained in the previous research on transmission switching with a Direct Current Optimal Power Flow (DCOPF) show significant cost reductions. This thesis on network topology optimization with ACOPF emphasizes the need for additional research in this area. It examines the performance of network topology optimization in an Alternating Current (AC) setting and its impact on various parameters like active power loss and voltages that are ignored in the DC setting. An ACOPF model, with binary variables representing the status of transmission lines incorporated into the formulation, is written in AMPL, a mathematical programming language and this optimization problem is solved using the solver KNITRO. ACOPF is a non-convex, nonlinear optimization problem, making it a very hard problem to solve. The introduction of bi-nary variables makes ACOPF a mixed integer nonlinear programming problem, further increasing the complexity of the optimization problem. An iterative method of opening each transmission line individually before choosing the best solution has been proposed as a purely investigative approach to studying the impact of transmission switching with ACOPF. Economic savings of up to 6% achieved using this approach indicate the potential of this concept. In addition, a heuristic has been proposed to improve the computational efficiency of network topology optimization. This research also makes a comparative analysis between transmission switching in a DC setting and switching in an AC setting. Results presented in this thesis indicate significant economic savings achieved by controlled topology optimization, thereby reconfirming the need for further examination of this idea. / Dissertation/Thesis / M.S. Electrical Engineering 2011

Orientador: José Roberto Sanches Mantovani / Resumo: Neste trabalho, o modelo matemático do problema de fluxo de potência ótimo básico não linear é analisado e manipulado algebricamente para obter um modelo de programação convexa, do tipo cônico de segunda ordem. O conceito de envelopes convexos é apresentado para tratar a não linearidade e não convexidade da restrição trigonométrica inversa que surge ao escrever o modelo de FPO como um modelo cônico. Aplicando duas proposições apresentadas neste trabalho a restrição trigonométrica é resolvida em um pré-processamento por um solver de otimalidade local, neste caso o KNITRO, que enumera todas as possibilidades dos pontos de KKT para obter os envelopes convexos e tornar o modelo de FPO totalmente convexo. O modelo é implementado no AMPL e é resolvido com solvers de otimalidade global com sistemas testes da literatura, nesta tese usam-se os sistemas testes IEEE 14, 30, 57 e 118 barras. Os resultados obtidos são validados comparando-os com resultados fornecidos pelo Matpower, que é um simulador para FPO. Como contribuição desta tese, o modelo convexo de FPO obtido é utilizado como exemplo de aplicações no problema de despacho ótimo de potência ativa e reativa, considerando competições via programação binível. São apresentados dois modelos biníveis e dois modelos uníveis. O modelo iterativo convexo utiliza-se do modelo proposto de FPO convexo e as não linearidades são convexificadas fazendo uso dos envelopes de McCormick. O conceito de dualidade forte é empregado afim de obter um mod... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In this work, the basic nonlinear mathematical model for the optimal power flow (OPF) problem is analyzed and manipulated algebraically in order to obtain a second-order conic convex programming model. The concept of convex envelopes is presented to deal with the nonlinearity and nonconvexity of the inverse trigonometric constraint that arises when transforming the nonconvex OPF model into an equivalent conic model. By applying two propositions presented in this work, the trigonometric constraint is solved in a pre-processing stage by a local optimization solver, in this case, the KNITRO solver, which considers all the possibilities of the KKT points to obtain the convex envelopes and find a completely convex OPF model, is used. The model is implemented in AMPL and is solved via global optimization solvers while to show the effectiveness of the model several IEEE systems such as the IEEE 14-, 30-, 57-, and 118-bus systems are used. The obtained results are validated by comparing them with the results provided by Matpower, which is an OPF solver. As a contribution of this thesis, the obtained convex OPF model is used as an application in the active and reactive optimal power dispatch problem, considering competition via bilevel programming. Two bilevel models and two single-level models are presented. The convex iterative model uses the proposed convex OPF model, and the nonlinearities are convexified using McCormick envelopes. The concept of strong duality is employed to obta... (Complete abstract click electronic access below) / Doutor

Orientador: Prof. Dr. Edmarcio Antonio Belati / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2016. / A inclusão de fontes de geração distribuída (GD) em sistemas elétricos vem crescendo nos últimos anos motivando o uso de fontes de energia alternativas renováveis ao mesmo tempo em que tem aumentado a demanda de energia global. Uma das fontes que tem crescido nos últimos anos ao nível mundial é a energia eólica. Frente à possibilidade de uma situação de escassez de energia elétrica, o aumento no custo da eletricidade e a busca constante das companhias por ter uma operação econômica do sistema elétrico, o estudo do desempenho ótimo da rede é apresentado como um tema importante para os centros de operação das companhias de energia elétrica. Desta forma, os Sistemas Elétricos de Potência (SEP) necessitam de ferramentas rápidas de análise para auxiliar os agentes na tomada de decisões surgindo assim o interesse em desenvolver ferramentas de análise que permitam aos operadores da rede tomarem decisões rápidas em relação às possíveis eventualidades ou variações no comportamento do sistema. O objetivo principal deste trabalho é aplicar análise de sensibilidade de segunda ordem (ASSO) nos sistemas de distribuição com geração eólica para obter um possível ponto de operação ótima de forma rápida após ocorrerem perturbações tanto na geração eólica quanto na carga do sistema. Para tanto foi modelado um Fluxo de Potência Ótimo (FPO) com as características do sistema e com o objetivo de minimizar as perdas de potência ativa, caracterizando assim o caso base (CB) e posteriormente aplicou-se a ASSO à solução encontrada no CB de forma a obter uma resposta rápida e econômica. Vale destacar que para validação da metodologia proposta buscou-se aplica-lo em sistemas de distribuição de energia elétrica. / The inclusion of distributed generation sources (DG) in electrical systems has been growing in recent years encouraging the use of alternative renewable energy sources at the same time it has increased the global energy demand. One of the sources that has grown in recent years worldwide is wind energy. Facing the possibility of energy shortage situation, the increase in the cost of electricity and the constant pursuit of companies to have an economic operation of the electrical system, the study of the network optimal performance is presented as a major issue for the operation centers of electricity companies. Thus, the Electric Power System (EPS) need fast analysis tools to assist agents in decision-making thus resulting interest in developing analysis tools that allow network operators to make quick decisions in relation to the possible eventualities or variations in system behavior. The main objective of this work is to apply analysis of second-order sensitivity (ASOS) in distribution systems with wind generation for an approximate point of optimal operation fastest as possible after disturbances occur both in wind generation, as the system load. For Optimal Power Flow (OPF) with the system's features and with the objective of minimize the loss of active power much was modeled, characterizing the base case (BC) and then applying the ASOS the solution obtained in BC in order to get a quick answer and economic. Note that to validate the proposed methodology we sought to apply it in electric power distribution systems.

Neste trabalho propomos uma abordagem para a resolução do problema de fluxo de potência ótimo. Para isso, foram obtidos dados teóricos, a partir de um levantamento bibliográfico, que explicitaram os métodos de penalidade, de barreira, de Newton-Lagrangiano, da função Lagrangiana aumentada e dual-Lagrangiano. Nesta abordagem, as restrições de igualdade são tratadas pelo método de Newton, as restrições canalizadas, de tensão e tap, pelo método da função barreira logarítmica, e as restrições de desigualdade e demais restrições canalizadas, pelo método da função Lagrangiana aumentada. A motivação para este estudo foi a necessidade de manter as variáveis - tensão e tap - dentro de seus limites. Os resultados numéricos apresentados evidenciam o potencial desta metodologia para a resolução de problemas de programação não-linear e, em particular, do problema de fluxo de potência ótimo. / A new approach to solving the optimal power flow problem is proposed in this study. The first step in developing this method was to obtain theoretical material from bibliographic survey, which described in detail the penalty method, the barrier method, Newton\'s method, the augmented Lagrangian method end the dual-Lagrangian method. In the new approach, equality constraints are handled by Newton\'s method, the voltage end tap box inequality constraints by the logarithmic barrier method and the inequality constraints and the other box inequality constraints by the augmented Lagrangian method. The motivation for this research was the necessity to keep the voltage and tap variables within their limits. The numerical results demonstrate the potential of this methodology for the solution of nonlinear problems and, in particular, of the optimal power flow problem.

Orientador: Prof. Dr. Júlio Carlos Teixeira / Tese (doutorado) - Universidade Federal do ABC. Programa de Pós-Graduação em Energia, 2017. / Neste trabalho, foi proposto um novo método para analisar o efeito da intermitência do vento em sistemas elétricos de potência. O método estocástico proposto baseia-se no fluxo de potência ótimo e em técnicas de análise de sensibilidade. Essas técnicas são aplicadas em uma ferramenta computacional capaz de alocar a energia intermitente com uma técnica de busca exaustiva com baixo tempo de computação. A metodologia foi aplicada nos sistemas de distribuição de 34 e 70 barras. Os resultados foram comparados com a alocação de energia fixa considerando a potência média associada a três condições distintas: à velocidade média do vento; ao fator de capacidade do gerador e à potência máxima do gerador. Estes resultados mostraram que um método estocástico que considera cada valor da velocidade do vento é necessário para determinar o barramento correto para alocar energia eólica intermitente. / In this work, a new method for analyzing the effect of the wind intermittency in electric power systems is proposed. The proposed stochastic method is based on the optimal power flow and sensitivity analysis techniques. These techniques are applied on a computational tool capable of allocating the intermittent energy with an exhaustive search technique with low computation time. The methodology was applied in the distribution systems of 34 and 70 buses. The results are compared with fixed power allocation considering the mean power of three different conditions: the average wind speed; the generator capacity factor and the maximum generator power. They showed that a stochastic method that considers each value of wind speed is necessary to determine the correct bus to allocate intermittent wind power.