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Advisor(s)
Abstract(s)
A presente dissertação tem como objetivos analisar e propor soluções para o problema da máxima injeção nodal de geração distribuída, simultânea e não simultânea, que é possível integrar numa rede de energia elétrica. Desta forma, consegue-se obter a localização mais adequada para a instalação de novos centros produtores.
Para o efeito, foram analisados e desenvolvidos em Matlab, recorrendo ao Matpowerpara avaliação das soluções, dois algoritmos evolutivos distintos, algoritmos genéticos e differential evolution, para obtenção de melhores perfis de injeção nodal simultânea.
Foi também proposta e desenvolvida uma variante do algoritmo differential evolution, denominado differential evolution modificado, que altera o modo de operação do algoritmo convencional de crossover. Embora todos os algoritmos evolutivos possam ser aplicados em qualquer topologia de rede, o algoritmo genético destaca-se dos demais, apresentando resultados superiores aos outros algoritmos desenvolvidos. No entanto, é de referir que o algoritmo differential evolution modificado apresentou resultados de melhor qualidade em comparação aos resultados obtidos por aplicação do differential evolution.
Abstract: This thesis aims to analyze and propose solutions to the problem of maximum nodal injection of distributed generation, simultaneous and non-simultaneous, that ispossible to integrate in a power grid. This way, it is possible to obtain the most appropriate location for the installation of new production centers. To this end, were developed and analyzed in Matlab, using the Matpower forevaluating solutions, two distinct evolutionary algorithms, genetic algorithms anddifferential evolution, to obtain the best profiles of simultaneous nodal injection. It was also proposed and developed a variant of the differential evolution algorithm, named modified differential evolution, amending the operating mode of theconventional crossover algorithm. Although all evolutionary algorithms can be applied to any network topology, the genetic algorithm stands out from the others, presenting superior results to other developed algorithms. However, it is noteworthy that the modified differential evolution algorithm showed better quality results when compared to the results obtained by the application of the differential evolution.
Abstract: This thesis aims to analyze and propose solutions to the problem of maximum nodal injection of distributed generation, simultaneous and non-simultaneous, that ispossible to integrate in a power grid. This way, it is possible to obtain the most appropriate location for the installation of new production centers. To this end, were developed and analyzed in Matlab, using the Matpower forevaluating solutions, two distinct evolutionary algorithms, genetic algorithms anddifferential evolution, to obtain the best profiles of simultaneous nodal injection. It was also proposed and developed a variant of the differential evolution algorithm, named modified differential evolution, amending the operating mode of theconventional crossover algorithm. Although all evolutionary algorithms can be applied to any network topology, the genetic algorithm stands out from the others, presenting superior results to other developed algorithms. However, it is noteworthy that the modified differential evolution algorithm showed better quality results when compared to the results obtained by the application of the differential evolution.
Description
Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica - Ramo de Energia
Keywords
Máxima injeção nodal Maximum nodal injection Algoritmos genéticos Genetic algorithms Differential evolution Matpower
Citation
ALVES, Pedro Miguel Dias dos Santos - Algoritmos evolutivos na determinação das máximas injeções nodais em redes de energia elétrica. Lisboa: Instituto Superior de Engenharia de Lisboa, 2014. Dissertação de mestrado.
Publisher
Instituto Superior de Engenharia de Lisboa