Reliability and restoration are important considerations in electric distribution systems. Reliability analysis is generally considered as a design tool to be used to improve the performance of the system. Restoration analysis is generally considered as a tool to be used for outaged situations. Reliability and restoration analysis are related, and some of the relationships are pointed to in this work. / Ph. D.

This dissertation focuses on two specific problems related to the reliability of the modern power grid. The first part investigates the economic dispatch problem with uncertain power sources. The classic economic dispatch problem seeks generator power output levels that meet demand most efficiently; we add risk-awareness to this by explicitly modeling the uncertainty of intermittent power sources using chance-constrained optimization and incorporating the chance constraints into the standard optimal power flow framework. The result is a dispatch of power which is substantially more robust to random fluctuations with only a small increase in economic cost. Furthermore, it uses an algorithm which is only moderately slower than the conventional practice. The second part investigates “the power grid attack problem”: aiming to maximize disruption to the grid, how should an attacker distribute a budget of “damage” across the power lines? We formulate it as a continuous problem, which bypasses the combinatorial explosion of a discrete formulation and allows for interesting attacks containing lines that are only partially damaged rather than completely removed. The result of our solution to the attack problem can provide helpful information to grid planners seeking to improve the resilience of the power grid to outages and disturbances. Both parts of this dissertation include extensive experimental results on a number of cases, including many realistic large-scale instances.

Os dispositivos Indicadores de Faltas (IFs) contribuem para a melhoria do processo de localização de faltas em alimentadores de distribuição e, consequentemente, para a qualidade do fornecimento de energia elétrica. Todavia, a grande dificuldade de se aplicar tais dispositivos em larga escala está na escassez de metodologias eficientes que apontem em quais pontos do sistema de distribuição eles devem ser instalados. Por isso, o presente trabalho propõe uma abordagem computacional evolutiva capaz de alocar dispositivos IFs em alimentadores primários de distribuição de energia elétrica. De forma mais específica, o problema de se obter o melhor local de instalação é solucionado por meio da técnica de Algoritmos Genéticos (AGs), que busca obter uma configuração eficiente de instalação de IFs no tronco principal do alimentador de distribuição. A metodologia proposta é aplicada a dois alimentadores reais. Aspectos de viabilidade técnica e financeira dos IFs também são analisados. Os resultados apresentados comprovam a eficiência da metodologia proposta. / Fault Indicator (FIs) devices have contributed to improve the location of faults on primary feeders, and consequently the reliability of distribution systems. However, one of the main problems facing their installation in a large scale in a distribution system is the lack of efficient methods to analyze big networks and to pinpoint exactly on which buses these devices should be placed. Thus, this paper proposes an evolutionary computing strategy to solve the problem of fault indicator placement in primary distribution feeders. Specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions in the main feeder. The proposed methodology was applied in two actual distribution feeders. Technical and financial viability aspects are also analyzed. Finally, the results confirm the efficiency of the GA approach to the FI placement problem.

Os dispositivos Indicadores de Faltas (IFs) contribuem para a melhoria do processo de localização de faltas em alimentadores de distribuição e, consequentemente, para a qualidade do fornecimento de energia elétrica. Todavia, a grande dificuldade de se aplicar tais dispositivos em larga escala está na escassez de metodologias eficientes que apontem em quais pontos do sistema de distribuição eles devem ser instalados. Por isso, o presente trabalho propõe uma abordagem computacional evolutiva capaz de alocar dispositivos IFs em alimentadores primários de distribuição de energia elétrica. De forma mais específica, o problema de se obter o melhor local de instalação é solucionado por meio da técnica de Algoritmos Genéticos (AGs), que busca obter uma configuração eficiente de instalação de IFs no tronco principal do alimentador de distribuição. A metodologia proposta é aplicada a dois alimentadores reais. Aspectos de viabilidade técnica e financeira dos IFs também são analisados. Os resultados apresentados comprovam a eficiência da metodologia proposta. / Fault Indicator (FIs) devices have contributed to improve the location of faults on primary feeders, and consequently the reliability of distribution systems. However, one of the main problems facing their installation in a large scale in a distribution system is the lack of efficient methods to analyze big networks and to pinpoint exactly on which buses these devices should be placed. Thus, this paper proposes an evolutionary computing strategy to solve the problem of fault indicator placement in primary distribution feeders. Specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions in the main feeder. The proposed methodology was applied in two actual distribution feeders. Technical and financial viability aspects are also analyzed. Finally, the results confirm the efficiency of the GA approach to the FI placement problem.