Estudo de Técnicas de Otimização de Sistemas Hidrotérmicos por Enxame de Partículas

• Autor(a) principal: GOMIDES, Lauro Ramon
• Data de Publicação: 2012
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• dARK ID: ark:/38995/001300000dgp8
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tde/973
• topic: sistemas hidrotérmicos de geração; planejamento da operação; otimização por enxame de partículas; enxame de partículas; inteligência de enxames; pesquisa operacional; hydrothermal systems; operation planning; particle swarm optimization; swarm intelligence; operational research; CNPQ::ENGENHARIAS

Particle Swarm Optimization has been widely used to solve real-world problems, including the operation planning of hydrothermal generation systems, where the main goal is to achieve rational strategies of operation. This can be accomplished by minimizing the high-cost thermoelectric generation, while maximizing the low-cost hydroelectric generation. The optimization process must consider a set of complex constrains. This work presents the application of some recently proposed Particle Swarm Optimizers for a group of hydroelectric power plants of the Brazilian interconnected system, using real data from existing plants. There were performed some tests by using the standard PSO, PSO-TVAC, Clan PSO, Clan PSO with migration, Center PSO, and one approach proposed in this work, called Center Clan PSO, over three different mid-term periods. All PSO approaches were compared to the results achieved by a Non-linear Programming algorithm (NLP). Furthermore, another approach was proposed, based on Center PSO, named Extended Center PSO. It was observed that the PSO approaches presented as promising solutions to the problem, even better than NLP in some cases.