In this dissertation topics of optimal meter placement and transaction-based loss allocation in deregulated power system operation are investigated. Firstly, Chapter II introduces the basic idea of candidate measurement identification, which is the selection of candidate measurement sets, each of which will make the system observable under a given contingency (loss of measurements and network topology changes). A new method is then developed for optimal meter placement, which is the choice of the optimal combination out of the selected candidate measurement sets in order to ensure the entire system observability under any one of the contingencies. A new method, which allows a natural separation of losses among individual transactions in a multiple-transaction setting is proposed in Chapter III. The proposed method does not use any approximations such as a D.C. power flow, avoiding method induced inaccuracies. The power network losses are expressed in terms of individual power transactions. A transaction-loss matrix, which illustrates the breakdown of losses introduced by each individual transaction and interactions between any two transactions, is created. The network losses can then be allocated to each transaction based on the transaction-loss matrix entries. The conventional power flow analysis is extended in Chapter IV to combine with the transaction loss allocation. A systematic solution procedure is formed in order to adjust generation while simultaneously allocating losses to the generators designated by individual transactions. Furthermore, Chapter V presents an Optimal Power Flow (OPF) algorithm to optimize the loss compensation if some transactions elect to purchase the loss service from the Independent System Operator (ISO) and accordingly the incurred losses are fairly allocated back to individual transactions. IEEE test systems have been used to verify the effectiveness of the proposed method.

Power system operation requires accurate monitoring of electrical quantities and a reliable database of the power system. As the power system operation becomes more competitive, the secure operation becomes highly important and the role of state estimation becomes more critical. Recently, due to the development of new technology in high power electronics, new control and monitoring devices are becoming more popular in power systems. It is therefore necessary to investigate their models and integrate them into the existing state estimation applications. This dissertation is dedicated to exploiting the newly appeared controlling and monitoring devices, such as Flexible AC Transmission System (FACTS) devices and (Phasor Measurement Units) PMUs, and developing new algorithms to include them into power system analysis applications. Another goal is to develop a 3D visualization tool to help power system operators gain an in-depth image of the system operation state and to identify limit violations in a quick and intuitive manner. An algorithm of state estimation of a power system with embedded FACTS devices is developed first. This estimator can be used to estimate the system state quantities and Unified Power Flow Controller (UPFC) controller parameters. Furthermore, it can also to be used to determine the required controller setting to maintain a desired power flow through a given line. In the second part of this dissertation, two methods to determine the optimal locations of PMUs are derived. One is numerical and the other one is topological. The numerical method is more effective when there are very few existing measurements while the topology-based method is more applicable for a system, which has lots of measurements forming several observable islands. To guard against unexpected failures of PMUs, the numerical method is extended to account for single PMU loss. In the last part of this dissertation, a 3D graphic user interface for power system analysis is developed. It supports two basic application functions, power flow analysis and state estimation. Different visualization techniques are used to represent different kinds of system information.

Desenvolveu-se neste trabalho um método para projeto e fortalecimento de planos de medição, para efeito de estimação de estados. O método proposto permite a obtenção de planos de medição que além de isentos de medidas críticas e de conjuntos críticos de medidas, garantem a observabilidade do sistema, mesmo com a perda simultânea de 1 ou 2 medidas quaisquer, ou, até mesmo, com a perda de 1 UTR. É um método numérico simples, de fácil implantação, que se baseia na análise da estrutura da matriz resultante da decomposição LDU, que é obtida através da fatoração triangular da matriz Jacobiana. Para comprovar a sua eficiência, vários testes foram realizados, utilizando os sistemas de 14 e 30 barras do IEEE, o sistema de 121 barras da ELETROSUL e o sistema de 383 barras da CHESF. / In this work a method to design and to upgrade Measurements Placement Plan for state estimation is proposed. The proposed method allows the obtention of measurements placement plans that, besides free of both critical measurements and critical sets, maintain the system observability when 1 or 2 measurements are lost, at same time, or even when a Remote Terminal Unit (RTU) is lost. It is a simple numerical method, easy to implement and based on the analysis of the structure of the resultant matrix of the decomposition LDU, that it is obtained through a triangular factorization of the Jacobian matrix. To prove the efficiency of the proposed method, several tests were made using the IEEE 14 and 30-bus systems, a 121-bus system from ELETROSUL and a 383-bus system from CHESF.

The goal of a water distribution system (WDS) is to supply the desired quantity of fresh water to consumers at the appropriate time. In order to properly operate a WDS, system operators need information about the system states, such as tank water level, nodal pressure, and water quality for the system wide locations. Most water utilities now have some level of SCADA (Supervisory Control and Data Acquisition) systems providing nearly real-time monitoring data. However, due to the prohibitive metering costs and lack of applications for the data, only portions of systems are monitored and the use of the SCADA data is limited. This dissertation takes a comprehensive view of real-time demand estimation in water distribution systems. The goal is to develop an optimal monitoring system plan that will collect appropriate field data to determine accurate, precise demand estimates and to understand their impact on model predictions. To achieve that goal, a methodology for real-time demand estimates and associated uncertainties using limited number of field measurements is developed. Further, system wide nodal pressure and chlorine concentration and their uncertainties are predicted using the estimated nodal demands. This dissertation is composed of three journal manuscripts that address these three key steps beginning with uncertainty evaluation, followed by demand estimation and finally optimal metering layout.The uncertainties associated with the state estimates are quantified in terms of confidence limits. To compute the uncertainties in real-time alternative schemes that reduce computational efforts while providing good statistical approximations are evaluated and verified by Monte Carlo simulation (MCS). The first order second moment(FOSM) method provides accurate variance estimates for pressure; however, because of its linearity assumption it has limited predictive ability for chlorine under unsteady conditions. Latin Hypercube sampling (LHS) provides good estimates of prediction uncertainty for chlorine and pressure in steady and unsteady conditions with significantly less effort.For real-time demand estimation, two recursive state estimators; tracking state estimator (TSE) based on weighted least squares (WLS) scheme and Kalman filter (KF), are applied. In addition, in order to find available field data types for demand estimation, comparative studies are performed using pipe flow rate and nodal pressure head as measurements. To reduce the number of unknowns and make the system solvable, nodes with similar user characteristics are grouped and assumed to have same demand pattern. The uncertainties in state variables are quantified in terms of confidence limits using the approximate methods (i.e., FOSM and LHS). Results show that TSE with pipe flow rates as measurements provide reliable demand estimations. Also, the model predictions computed using the estimated demands match well with the synthetically generated true values.Field measurements are critical elements to obtaining quality real-time state estimates. However, the limited number of metering locations has been a significant obstacle for the real-time studies and identifying locations to best gain information is critical. Here, an optimal meter placement (OMP) is formulated as a multi-objective optimization problem and solved using a multi-objective genetic algorithm (MOGA) based on Pareto-optimal solutions. Results show that model accuracy and precision should be pursued at the same time as objectives since both measures have trade-off relationship. GA solutions were improvements over the less robust methods or designers' experienced judgment.

Power outages usually lead to customer complaints and revenue losses. Consequently, fast and accurate fault location on electric lines is needed so that repair work can be carried out as fast as possible. Chapter 2 describes novel fault location algorithms for radial and non-radial ungrounded power distribution systems. For both types of systems, fault location approaches using line to neutral or line to line measurements are presented. It’s assumed that network structure and parameters are known, so that during-fault bus impedance matrix of the system can be derived. Functions of bus impedance matrix and available measurements at substation are formulated, from which the unknown fault location can be estimated. Evaluation studies on fault location accuracy and robustness of fault location methods to load variations and measurement errors has been performed. Most existing fault location methods rely on measurements obtained from meters installed in power systems. To get the most from a limited number of meters available, optimal meter placement methods are needed. Chapter 3 presents a novel optimal meter placement algorithm to keep the system observable in terms of fault location determination. The observability of a fault location in power systems is defined first. Then, fault location observability analysis of the whole system is performed to determine the least number of meters needed and their best locations to achieve fault location observability. Case studies on fault location observability with limited meters are presented. Optimal meter deployment results based on the studied system with equal and varying monitoring cost for meters are displayed. To enhance fault location accuracy, an optimal fault location estimator for power distribution systems with distributed generation (DG) is described in Chapter 4. Voltages and currents at locations with power generation are adopted to give the best estimation of variables including measurements, fault location and fault resistances. Chi-square test is employed to detect and identify bad measurement. Evaluation studies are carried out to validate the effectiveness of optimal fault location estimator. A set of measurements with one bad measurement is utilized to test if a bad data can be identified successfully by the presented method.

Desenvolveu-se neste trabalho um método para projeto e fortalecimento de planos de medição, para efeito de estimação de estados. O método proposto permite a obtenção de planos de medição que além de isentos de medidas críticas e de conjuntos críticos de medidas, garantem a observabilidade do sistema, mesmo com a perda simultânea de 1 ou 2 medidas quaisquer, ou, até mesmo, com a perda de 1 UTR. É um método numérico simples, de fácil implantação, que se baseia na análise da estrutura da matriz resultante da decomposição LDU, que é obtida através da fatoração triangular da matriz Jacobiana. Para comprovar a sua eficiência, vários testes foram realizados, utilizando os sistemas de 14 e 30 barras do IEEE, o sistema de 121 barras da ELETROSUL e o sistema de 383 barras da CHESF. / In this work a method to design and to upgrade Measurements Placement Plan for state estimation is proposed. The proposed method allows the obtention of measurements placement plans that, besides free of both critical measurements and critical sets, maintain the system observability when 1 or 2 measurements are lost, at same time, or even when a Remote Terminal Unit (RTU) is lost. It is a simple numerical method, easy to implement and based on the analysis of the structure of the resultant matrix of the decomposition LDU, that it is obtained through a triangular factorization of the Jacobian matrix. To prove the efficiency of the proposed method, several tests were made using the IEEE 14 and 30-bus systems, a 121-bus system from ELETROSUL and a 383-bus system from CHESF.

Real time monitoring of the shipboard power system is a complex task to address. Unlike the terrestrial power system, the shipboard power system is a comparatively smaller system but with more complexity in terms of its system operation. This requires the power system to be continuously monitored to detect any type of fluctuations or disturbances. Planning metering systems in the power system of a ship is a challenging task not only due to the dimensionality of the problem, but also due to the need for reducing redundancy while improving network observability and efficient data collection for a reliable state estimation process. This research is geared towards the use of a Genetic Algorithm for intelligent placement of meters in a shipboard system for real time power system monitoring taking into account different system topologies and critical parameters to be measured from the system. The algorithm predicts the type and location of meters for identification and collection of measurements from the system. The algorithm has been tested with several system topologies.

Made available in DSpace on 2016-08-17T14:52:40Z (GMT). No. of bitstreams: 1 Dissertacao-AntonioAdolphoMartinsRaposo.pdf: 6219934 bytes, checksum: 92f0e1fb7c3d703fcf27aae305b549f2 (MD5) Previous issue date: 2016-02-26 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / To plan and operate properly a Smart Grid (SG), many new technical considerations in the context of distribution systems, must be considered, for example: stability (due to installation of Distributed Generation (DG), the load and generation dispatch, management of energy storage devices and the assessment of the impact of electric vehicle connection on the distribution system. The main prerequisite for many of these new functions in the distribution system control center is to determine the electrical network state (magnitude and angle of nodal voltages) in real time from measurement devices installed in it. In the transmission system control centers, this task is performed by the state estimation tool. Thus, the Distribution System State Estimation (DSSE) is one of the cornerstones for the implementation of a SG. The presence of a small number of measurements can make the grid unobservable in the context of the DSSE. That is, the state variables (magnitude and angle of the node voltages of all bus) can not be determined from a set of measurements by a state estimator. Due to this, it is usually added a large number of pseudo measurements to the existing measurement plan to ensure observability and to enable the DSSE. A drawback with this strategy is that the accuracy of the estimated state is compromised due to the fact that the errors associated with the pseudo measurements are considerably higher than those relating to real measurements. Consequently, it is necessary to allocate meters (voltage magnitude, active and reactive power flows, current magnitudes, etc.) to guarantee the accuracy of the DSEE. The meter placement problem for the state estimation in the transmission networks is usually carried out with the objective of assuring the observability. On the other hand, the meter placement for the EERD aims to minimize probabilistic index associated with the errors between the true and estimated state vectors. An important component of the method used to solve the meters placement problem is a probabilistic technique used to estimate the objective function. Due to the nonlinear nature of DSSE problem, the best option has been to use the Monte Carlo Simulation (MCS). A disadvantage of the MCS to estimate the objective function of the allocation problem is its high computational cost due to the need to solve a nonlinear state estimation problem for each sample element. The main objective of this dissertation is to propose a probabilistic techniques to improve the computational performance of existing methodologies for meter placement without reducing the accuracy of the estimated ix state. This compromise has been established using two strategies. In the first one, a linear model is used to estimate the state and the MCS is applied to determine the risks of the objective function. In the second one, a closed analytical formula is used to determine the risks based on the linearized model. Furthermore, the improved versions of the meter placement algorithms proposed in this dissertation consider the effect of the correlation among the measurements. The proposed meter placement algorithms were tested in the British distribution system of 95 bus. The tests results demonstrate that the introduction of the proposed strategies in a meter placement algorithm significantly reduced its computational cost. Moreover, it can be observed that there were improvements in accuracy in some cases, because the risk estimates provided by MCS are not accurate with small samples. / Para planejar e operar adequadamente uma Rede Elétrica Inteligente (REI), muitas novas considerações técnicas, no âmbito de sistemas de distribuição, devem ser apreciadas, por exemplo: a estabilidade devido a instalação de Geração Distribuída (GD), o despacho de carga e geração, o gerenciamento de dispositivos de armazenamento de energia e a avaliação do impacto da conexão de veículos elétricos na rede de distribuição. O principal pré-requisito para muitas destas novas funções do centro de controle do sistema de distribuição é a determinação do estado da rede elétrica (módulo e a fase das tensões nodais) em tempo real a partir de dispositivos de medição nela instalados. Em centros de controle de sistemas de transmissão esta tarefa é realizada por ferramentas de estimação de estado. Desta forma, a Estimação de Estado em Redes de Distribuição (EERD) é um dos alicerces para a implantação de uma REI. A presença de um número reduzido de medições pode tornar a rede elétrica não observável no âmbito da EERD. Isto é, as variáveis de estado (módulo e fase das tensões nodais em todas as barras) não podem ser determinadas a partir de um conjunto de medições por um estimador de estado. Devido a isto, geralmente adiciona-se um grande número de pseudo-medições ao plano de medição existente para assegurar a observabilidade e viabilizar a EERD. Um problema com esta estratégia é que a precisão do estado estimado é comprometida devido ao fato de que os erros associados com as pseudo-medições são consideravelmente maiores do que aqueles referentes às medições reais. Consequentemente é necessário alocar medidores (magnitude das tensões, fluxos de potência ativa e reativa, magnitude das correntes, etc.) para garantir a precisão do EERD. O problema de alocação de medidores para a estimação de estado em redes de transmissão é, geralmente, realizado com o objetivo de assegurar a observabilidade. Por outro lado, a alocação de medidores para EERD é realizada visando minimizar índices probabilísticos associados com os erros entre os vetores de estado estimado e verdadeiro. Um componente importante do método usado para resolver o problema de alocação de medidores é a técnica probabilística usada para estimar a função objetivo. Devido à natureza não-linear do problema de EERD, a melhor opção tem sido utilizar a Simulação Monte Carlo (SMC). Uma desvantagem da SMC para estimar a função objetivo do problema de alocação é o seu alto custo computacional devido a necessidade de resolver um problema de estimação de estado não-linear para cada vii elemento da amostra. O principal objetivo desta dissertação é propor técnicas probabilísticas para melhorar o desempenho computacional de metodologias existentes para alocação de medidores sem sacrificar a precisão do estado estimado. Este compromisso foi estabelecido usando-se duas estratégias. Na primeira, um modelo linearizado é usado para estimar o estado e a SMC para determinar os riscos da função objetivo. Na segunda, uma fórmula analítica fechada é usada para determinar os riscos com base no modelo linearizado. Além disso, as versões melhoradas dos algoritmos de alocação propostos nesta dissertação consideram o efeito da correlação entre as medições. As metodologias de alocação propostas foram testadas no sistema de distribuição britânico de 95 barras. Os resultados dos testes demonstraram que a introdução das estratégias propostas em um algoritmo de alocação de medidores reduziu significativamente o seu custo computacional. Além disso, pode-se observar que ocorreram melhorias na precisão em alguns casos, pois as estimativas dos riscos fornecidas pela SMC não são precisas com pequenas amostras.