Abstract With an ever increasing emphasis on reliability of supply, improvement in the lightning performance of distribution lines is required. The arc quenching properties of wooden distribution line poles during lightning strikes are an important factor in the reduction of switchgear operation, hence outages. Measurements were conducted on a 22 kV distribution line and it was suspected, in some cases, that direct lightning strikes to the line did not cause switchgear operation. Distribution lines predominantly use wooden poles with a specific configuration which incorporates a 'wooden' spark gap. This paper provides background to the basic configuration of a typical distribution line and the processes which govern the electric arc. A simulation using a dynamic arc model shows that field measured lightning overvoltages on a distribution line are reproducible through system modelling. The simplistic dynamic arc model developed is sufficiently accurate to describe a set of arcs in a larger system such as a distribution line.

Energy security concerns and the impact of traditional sources of power generation on the climate have prompted a rise in renewable energy expansion around the world. Power transmission from remote generation sites to consumers over long distance is most efficient using High-Voltage Direct Current (HVDC) transmission lines. Consequently, HVDC and the integration of renewable resources are considered as key perspectives in the improvement of sustainable energy systems capable of secure and stable electric power supply. With the intention of huge energy demand in the future, the multi-terminal DC grid concept is proposed based on various converter topologies like Line Commutated Converter (LCC), Voltage Sourced Converter (VSC), and Modular Multilevel Converter (MMC) HVDC technologies. These converters play a vital role in integrating remotely-located renewable generation and reinforcing existing power systems. The MMC has become increasingly popular in HVDC transmission compared to conventional line commutated converters, two-level and multilevel voltage source converters. Low generation of harmonics, a low switching frequency of semiconductors, sine formed AC voltages and currents, black start capability and higher overall efficiency are a few of the unique features of MMC. The MMC is characterised by a modular arm structure, formed by a cascade connection of a vast number of simple cells with floating DC capacitors. These cells are called Sub-Modules (SMs) and can be easily assembled into a converter for high voltage power conversion systems. Compared with traditional VSCs, the analytical modelling of MMC is more challenging. This is because of technical issues such as higher order system, the discontinuous and non-linear nature of signal transfer through converters, the complexity of the interaction equations between the AC and DC variables, and harmonic frequency conversion through AC side and DC side of the converter. This work intends to resolve these challenges by developing a detailed non-linear model using fundamental switching Selective Harmonic Elimination (SHE) modulation technique, an average MMC model in DQ0 frame and an analytical dynamic MMC model, which can be suitable for small-signal stability studies, and control design. Firstly, the detailed model of MMC using fundamental switching SHE modulation scheme has been developed using PSCAD/EMTDC (Power systems computer aided design Electromagnetic transients for DC) software. The basic terms and equations of the MMC have been presented along control loops. The significance of the switching frequency on the performance of the MMC has been studied as well as the relation between the switching frequency, the Total Harmonic Distortion (THD) and the number of output voltage levels. Detailed representation of MMC systems in PSCAD/EMTDC programs incorporates the modelling of Insulated-Gate Bipolar Transistor (IGBT) valves and should typically utilise small integration time-steps to represent fast switching events precisely. Computational burden introduced by such detailed models make the study of steady-state and transient events more complex, highlighting the need to implement more efficient models that provide comparative behaviour and dynamic response. Secondly, average DQ0 models has been implemented to accurately replicate the steady-state, dynamic and transient behaviour of MMC in PSCAD/EMTDC programs. These simplified models represent the average response of switching devices and converters by using averaging techniques involving controlled sources and switching functions. Developing the MMC average model in DQ0 frame was a challenging task because of the multiplication terms in the MMC average model in ABC frame. The proposed approach to overcome this challenge is considering generic form for the product variables and multiplying them in ABC frame and then transferring only the DC and fundamental frequency components of the results to DQ0 frame. The comparisons between detailed model and the average model validated the effectiveness of the average model in representing the dynamics of MMC. It is at least one hundred times faster than the detailed model for the same simulation time step. Finally, a dynamic analytical MMC model and associated controls have been proposed. To enable the model application to a broad range of system configurations and various dynamic studies, the model is built on a modular modelling approach using four sub-systems; an AC system, Phase Locked Loop (PLL) system, MMC system and a DC arrangement. The developed MMC system model has been linearized and implemented in state-space form. To select the best open-loop controller gains, eigenvalue analysis is performed for each particular test system. The rationality and correctness of the proposed model are verified against non-linear PSCAD/EMTDC simulations, and good accuracy is obtained in the time domain analysis. Further, the model is also verified in the frequency domain, and it is concluded that the developed model can be employed for dynamic analysis below 300 Hz.

Enhancing power grids' performance and resilience has been one of the greatest challenges in engineering and science over the past decade. A recent report by the National Academies of Sciences, Engineering, and Medicine along with other studies emphasizes the necessity of deploying new ideas and mathematical tools to address the challenges facing the power grids now and in the future. To full this necessity, numerous grid modernization programs have been initiated in recent years. This thesis focuses on one of the most critical challenges facing power grids which is their vulnerability against failures and attacks. Our approach bridges concepts in power engineering and computer science to improve power grids resilience and security. We analyze the vulnerability of power grids to cyber and physical attacks and failures, design efficient monitoring schemes for robust state estimation, develop algorithms to control the grid under tension, and introduce methods to generate realistic power grid test cases. Our contributions can be divided into four major parts: Power Grid State Prediction: Large scale power outages in Australia (2016), Ukraine (2015), Turkey (2015), India (2013), and the U.S. (2011, 2003) have demonstrated the vulnerability of power grids to cyber and physical attacks and failures. Power grid outages have devastating effects on almost every aspect of modern life as well as on interdependent systems. Despite their inevitability, the effects of failures on power grids' performance can be limited if the system operator can predict and understand the consequences of an initial failure and can immediately detect the problematic failures. To enable these capabilities, we study failures in power grids using computational and analytical tools based on the DC power flow model. We introduce new metrics to efficiently evaluate the severity of an initial failure and develop efficient algorithms to predict its consequences. We further identify power grids' vulnerabilities using these metrics and algorithms. Power Grid State Estimation: In order to obtain an accurate prediction of the subsequent effects of an initial failure on the performance of the grid, the system operator needs to exactly know when and where the initial failure has happened. However, due to lack of enough measurement devices or a cyber attack on the grid, such information may not be available directly to the grid operator via measurements. To address this problem, we develop efficient methods to estimate the state of the grid and detect failures (if any) from partial available information. Power Grid Control: Once an initial failure is detected, prediction methods can be used to predict the subsequent effects of that failure. If the initial failure is causing a cascade of failures in the grid, a control mechanism needs to be applied in order to mitigate its further effects. Power Grid Islanding is an effective method to mitigate cascading failures. The challenge is to partition the network into smaller connected components, called islands, so that each island can operate independently for a short period of time. This is to prevent the system to be separated into unbalanced parts due to cascading failures. To address this problem, we introduce and study the Doubly Balanced Connected graph Partitioning (DBCP) problem and provide an efficient algorithm to partition the power grid into two operating islands. Power Grid Test Cases for Evaluation: In order to evaluate algorithms that are developed for enhancing power grids resilience, one needs to study their performance on the real grid data. However, due to security reasons, such data sets are not publicly available and are very hard to obtain. Therefore, we study the structural properties of the U.S. Western Interconnection grid (WI), and based on the results we present the Network Imitating Method Based on LEarning (NIMBLE) for generating synthetic spatially embedded networks with similar properties to a given grid. We apply NIMBLE to the WI and show that the generated network has similar structural and spatial properties as well as the same level of robustness to cascading failures. Overall, the results provided in this thesis advance power grids' resilience and security by providing a better understanding of the system and by developing efficient algorithms to protect it at the time of failure.

Orientador: Rubén Augusto Romero Lázaro / Banca: Antonio Padilha Feltrin / Banca: Sergio Azevedo de Oliveira / Banca: Antonio César Baleeiro Alves / Banca: Luis Gustavo Wesz da Silva / Resumo: Neste trabalho é realizada uma análise teórica e a implementação computacional de um algoritmo de Busca Dispersa especializado para resolver o problema de planejamento da expansão de sistemas de transmissão (PPEST) de energia elétrica estático. O problema de planejamento consiste em determinar entre um conjunto de circuitos candidatos, aqueles que quando forem incorporados ao sistema apresentarem o menor custo de investimento possível. Este problema é considerado complexo e difícil de ser resolvido por ser um problema não linear inteiro misto, altamente ilhado, envolvendo "explosões" combinatórias. A meta-heurística de busca dispersa é um algoritmo evolutivo que se propõe a combinar soluções de qualidade e de diversidade do espaço de busca. O algoritmo de busca dispersa desenvolvido apresentou-se altamente eficiente para encontrar soluções de ótima qualidade para todos os problemas testados comparados com a literatura consultada, especializada na área. A garantia da diversidade oferecida pelo algoritmo é adicionada intencionalmente como forma de evitar, ou mesmo avançar por ótimos locais. Outro fato importante é que o método opera sobre um conjunto reduzido de soluções do espaço de busca criteriosamente gerado, que faz reduzir significativamente o número de combinações que são realizadas. Rotinas geradas com a utilização de algoritmos heurísticos construtivos gulosos de Garver e Villasana-Garver-Salon para modelos como o de Transportes e o modelo DC no PPEST apresentaram alto desempenho neste trabalho. Uma perturbação controlada nos custos de instalação das linhas de transmissão foi decisiva para que o processo de geração de soluções (factíveis, diversas e/ou com qualidade) fosse altamente eficiente, sendo possível encontrar o ótimo global em alguns problemas ainda nesta etapa de geração de soluções. Mecanismos de melhoramento local aplicados ... / Abstract: This work presents a theoretical analysis and computational implementation of a specialized Scatter Search algorithm to solve the static transmission network expansion planning (TNEP) problem of electric power systems. The objective of such planning problems is to determine a set of circuits among the candidates in which not only satisfy the demands but also the minimum investment cost is at hand. This problem is considered as a complex mixed integer nonlinear programming (MINLP) problem that has a lot of local optimum problem. The scatter search is an evolutionary method with the objective of maintaining a set of diverse and high-quality candidate solutions. The proposed scatter search algorithmhas been applied in engineering optimization problems especially in electric power system problems and has presented high quality solutions. The diversity sets ensure to avoid getting trapped in a local optimum. Another important factor is that the proposed methodology reduces the search space and consequently the number of combinations is reduced. In this work, a high quality solution of TNEP is obtained using the greedy constructive heuristic algorithms such as Garver, and Villasana-Garver-Salon that work based on Transport model and DC model respectively. In this work, in order to generate the initial solutions, a controlled disturbance has been added in the costs of the transmission lines in order to obtain diverse and high quality solutions that lead to find the global optimum for some problems even in the initial generation step. Moreover, the proposed scatter search algorithm presents a local improvement phase during the implementation. In order to show the effectiveness of the proposed algorithm, 5 case studies are conducted such as Garver 6-bars and 15 branches , IEEE 24-bars and 41 branches , South Brazilian 46-bars and 79 branches, Colombian 93-bars and 155 branches, and the North-Northeast 87-bars ... / Doutor

This study is concerned with the analyses of modern electric power-grids designed to support large supply-demand considerations in metro areas of large cities. Hence proposed are methods to determine optimal performance of the associated distribution networks vis-á-vis power availability from multiple resources (such as hydroelectric, thermal, wind-mill, solar-cell etc.) and varying load-demands posed by distinct set of consumers of domestic, industrial and commercial sectors. Hence, developing the analytics on optimal power-distribution across pertinent power-grids are verified with the models proposed. Forecast algorithms and computational outcomes on supply-demand performance are indicated and illustratively explained using real-world data sets. This study on electric utility takes duly into considerations of both deterministic (technological factors) as well as stochastic variables associated with the available resource-capacity and demand-profile details. Thus, towards forecasting exercise as above, a representative load-curve (RLC) is defined; and, it is optimally determined using an Artificial Neural Network (ANN) method using the data availed on supply-demand characteristics of a practical power-grid. This RLC is subsequently considered as an input parametric profile on tariff policies associated with electric power product-cost. This research further focuses on developing an optimal/suboptimal electric-power distribution scheme across power-grids deployed between multiple resources and different sets of user demands. Again, the optimal/suboptimal decisions are enabled using ANN-based simulations performed on load sharing details. The underlying supply-demand forecasting on distribution service profile is essential to support predictive designs on the amount of power required (or to be generated from single and/or multiple resources) versus distributable shares to different consumers demanding distinct loads. Another topic addressed refers to a business model on a cost reflective tariff levied in an electric power service in terms of the associated hedonic heuristics of customers versus service products offered by the utility operators. This model is based on hedonic considerations and technoeconomic heuristics of incumbent systems In the ANN simulations as above, bootstrapping technique is adopted to generate pseudo-replicates of the available data set and they are used to train the ANN net towards convergence. A traditional, multilayer ANN architecture (implemented with feed-forward and backpropagation techniques) is designed and modified to support a fast convergence algorithm, used for forecasting and in load-sharing computations. Underlying simulations are carried out using case-study details on electric utility gathered from the literature. In all, ANN-based prediction of a representative load-curve to assess power-consumption and tariff details in electrical power systems supporting a smart-grid, analysis of load-sharing and distribution of electric power on smart grids using an ANN and evaluation of electric power system infrastructure in terms of tariff worthiness deduced via hedonic heuristics, constitute the major thematic efforts addressed in this research study. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

Orientador: José Roberto Sanches Mantovani / Banca: Fabio Bertequini Leão / Banca: Luis Gustavo Wesz da Silva / Resumo: Neste trabalho propõe-se um algoritmo baseado na meta-heurística busca dispersa para o problema de reconfiguração de redes de distribuição de energia elétrica radiais, considerando como sistema de codificação uma estrutura denominada representação nó profundidade (RNP). O problema é modelado como não linear inteiro misto e considera como objetivo principal minimizar as perdas de potência ativa nos alimentadores do sistema de distribuição. Utiliza-se neste trabalho o modelo de cargas com potência constante, como também o modelo exponencial de cargas. O algoritmo proposto é implementado em linguagem de programação C++ e testado em quatro sistemas conhecidos na literatura, 14, 84, 136 e 202 barras. A partir dos resultados obtidos, verifica-se o bom desempenho do algoritmo, pois é capaz de gerar soluções de boa qualidade atendendo a todas as restrições físicas e operacionais do problema. / Abstract: This work proposes a scatter search algorithm to solve the electric power distribution system reconfiguration problem, considering the encoding system node depth representation. The problem is a mixed-integer nonlinear programming and the objective is to minimize the real power losses in the distribution system. It is used in the work load model with constant power, but also exponential model load. The proposed algorithm is implemented in C + +. The validity of the methodology is verified through four commonly case studies such as 14, 84, 136 and 202 bus system. Results show the effectiveness and good performance of the proposed algorithm, where it obtains the good quality solution satisfying the operational and physics constraints of problem. / Mestre

Orientador: José Roberto Sanches Mantovani / Coorientador: Luis Gustavo Wesz da Silva / Banca: Marina Lavorato de Oliveira / Banca: Marcelo Escobar de Oliveira / Resumo: Neste trabalho, propõe-se um algoritmo baseado na meta-heurística busca tabu para o problema de restauração de redes de distribuição de energia elétrica radiais com geração distribuída, considerando como sistema de codificação uma estrutura denominada representação nó-profundidade (RNP). O problema é modelado como não linear inteiro misto e considera os principais objetivos da restauração de redes de distribuição: minimizar número de consumidores sem fornecimento de energia elétrica e o número de chaveamentos. Propõe-se, também, uma sequência lógica de chaveamentos que garante os aspectos operacionais. O algoritmo desenvolvido foi implementado em linguagem de programação C++ e testado em sistemas de distribuição de 136 e 7052 barras / Abstract: This work proposes a methodology based in the meta-heuristic tabu search to distribution power system restoration considering distributed generators installed on the system, using the encoding system node depth representation. The problem is established as a mixed-integer nonlinear programming taking into account the mainly goals: to minimize both the number of consumers without supply and the number of switching. This work also proposes a logic sequence of switching operations, taking care of operational issues. The proposed algorithm was implemented in C++ programming language and tested in a 136 and a 7052 bus distribution systems / Mestre

Thesis (M.S.)--Drexel University, 2007. / Includes abstract. Includes bibliographical references (leaves 81-83).

Thesis (Ph.D.)--University of Texas at Arlington, 2009.

Thesis (M. Phil.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 139-145).