Otimização de sistemas hidrotérmicos de geração por meio de meta-heurísticas baseadas em enxame de partículas

• Autor(a) principal: Deus, Guilherme Resende
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• dARK ID: ark:/38995/001300000cc68
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/7530
• topic: Hidrotérmicos de geração; Planejamento da operação; Pesquisa operacional; Algoritmos meta-heurísticos; Otimização por enxame de partículas; Enxame de partículas; LSSPSO; ABeePSO; KFPSO; Hydrothermal generating systems; Operation planning; Operational research; Metaheuristic algorithms; Particle swarm optimization; Particle swarm; LSSPSO; ABeePSO; KFPSO; ENGENHARIAS

The objective of this work is to find reasonable solutions to the problem of optimization of hydrothermal generating systems by means of metaheuristics based on particle swarms. The proposed problem is complex, dynamic, nonlinear and presents some stochastic variables. The study consisted of the implementation of particle swarm algorithms, more specifically the variants of the Particle Swarm Optimization (PSO) algorithm: LSSPSO, ABeePSO and KFPSO. The algorithms were run in a mill simulator containing data from eight National Interconnected System mills during the five year period. The results were compared with the studies using the Nonlinear Programming (NLP) algorithm, and it was concluded that although the presented meta-heuristics were able to obtain a Final Storage Energy value equal to NLP, they did not have a generation cost Equivalent to or less than the Nonlinear Programming method.