Uma abordagem multicritério do planejamento ótimo de sistemas de distribuição de energia

• Ano de defesa: 2001
• Autor(a) principal: Luiz Augusto Epifanio Soares
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Automação; Engenharia Elétrica; Engenharia elétrica
• Link de acesso: http://hdl.handle.net/1843/BUOS-9K9P5K

The planning of power system distribution is a relatively complex task due to several options available. In large networks the number of variables is very important, in such a way that, the final configuration of the network that asserts the requirements of cost reduction with an appropriate reliability level, is unfeasible without the aid of computional tool.To aid in this task, an opmization algorithm was developed for planning a distribution system considering the objective of minimizing the initial costs and the losses by Joule effect , as well as, maximizing the realibily of the system. Different from most of previews works, which considered only the problem of a single objective (generally to minimize the cost) or a weighted sum of more than an objective( cost and reliability)the algorithm developed in this work uses the multi-obejctive approach based on the determination of a pareto-optimal set or a set of non-dominated solutions. In this way, the network configurations are reduced to a particular group of options (solutions), facilitating the final choice of the network configuration for the designer. In this work the algorithm used was based in the genetic algorithm. The algorithm was adapted considering that optimization in power distribution system in considered as combinatorial nature, highly nonlinear and with a strong multi-objective characteristic. It was necessary, also, to develop new crossing and mutation operators, since the operators traditionally used by the standard genetic algorithm were shown inefficient for the solution of our optimization problems in distribution networks.