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Abstract(s)
Phasor Measurement Units (PMUs) são dispositivos de monitorização de redes elétricas que são utilizados na obtenção e envio instantâneo de informações acerca da tensão do nó em que estão instalados e das correntes nos ramos a si ligados. Para além dessas medições diretas, a sua utilização permite, através de um conjunto de regras de análise de circuitos elétricos, obter informação relativa a outros nós que não aquele em que são instalados. Assim, através da de nição de um conjunto de regras de observabilidade, um posicionamento diferente dos PMUs vai permitir monitorizar uma maior ou menor percentagem da rede. Isto conduz a um problema de otimização do posicionamento de PMUs em que se pretende decidir quais os nós em que devem ser colocados com o objetivo de minimizar o número de PMUs usados garantindo que a rede elétrica é totalmente monitorizada. Nesta dissertação, o problema a ser tratado terá como base o problema referido anteriormente, considerando agora que há um investimento máximo que pode ser feito na aquisição de PMUs. Neste contexto o problema a estudar é o da maximização do número de nós monitorizados, utilizando os PMUs que o orçamento permite adquirir. O problema foi resolvido usando uma meta-heurística (Simulated Annealing), sendo os seus resultados validados através de testes computacionais num conjunto de instâncias existentes na literatura.
Phasor Measurement Units (PMUs) are monitoring devices designed to obtain and instantaneously send information about the voltage of the buses in which they are installed and the currents in the branches. In addition to these direct measurements, its use allows to obtain information on other buses besides the ones in which they are placed on. This is obtained through a set of basic rules that are used to perform the analysis of electrical circuits. Thus, by defining a set of observability rules, a different PMU positioning will allow the monitoring of a higher or smaller percentage of a network. This leads to the PMU positioning problem that aims to minimize the number of PMUs necessary to fully monitored a power systems network, by conveniently selecting the nodes where the PMUs should be positioned. In this thesis, the problem to be addressed will be based on the previously mentioned one, considering now that there is a limit on the investment that can be made to acquire PMUs. Under such assumption we have a problem of maximizing the number of buses monitored using the PMUs that the budget allows to acquire. The problem was solved with a metaheuristic (Simulated Annealing), and its results were validated through computational tests using a set on instances present in the literature.
Phasor Measurement Units (PMUs) are monitoring devices designed to obtain and instantaneously send information about the voltage of the buses in which they are installed and the currents in the branches. In addition to these direct measurements, its use allows to obtain information on other buses besides the ones in which they are placed on. This is obtained through a set of basic rules that are used to perform the analysis of electrical circuits. Thus, by defining a set of observability rules, a different PMU positioning will allow the monitoring of a higher or smaller percentage of a network. This leads to the PMU positioning problem that aims to minimize the number of PMUs necessary to fully monitored a power systems network, by conveniently selecting the nodes where the PMUs should be positioned. In this thesis, the problem to be addressed will be based on the previously mentioned one, considering now that there is a limit on the investment that can be made to acquire PMUs. Under such assumption we have a problem of maximizing the number of buses monitored using the PMUs that the budget allows to acquire. The problem was solved with a metaheuristic (Simulated Annealing), and its results were validated through computational tests using a set on instances present in the literature.
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Keywords
PMUs Problema de otimização Meta-heurísticas Simulated Annealing Optimization problem Metaheuristics