Otimização do scheduling do transporte de derivados escuros de petróleo em uma malha dutoviária

• Ano de defesa: 2015
• Autor(a) principal: Bueno, Lucas
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Brasil; Programa de Pós-Graduação em Engenharia Elétrica e Informática Industrial; UTFPR
• Palavras-chave em Português: Petróleo - Derivados; Oleodutos de petróleo - Programação linear; Programação heurística; Engenharia elétrica; Petroleum products; Petroleum pipelines - Linear programming; Heuristic programming; Electric engineering; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/1893

In this work it is presented an approach to the optimization of the scheduling of heavy oil derivatives transportation in a pipeline network. There are four refineries in this network, three intermediate nodes and one maritime terminal. The derivatives transport is influenced by practical constraints and political needs, and so the scheduling problem is complex, which encourages the development of the current work. Some characteristics of this problem should be noticed, like the necessity of products exchanges on tanks during a scheduling horizon and the necessity of products blends. It is described an approach in which groups of products with unified inventory are treated. An approach in which, on the planning model, the main objective to optimize is the balance of the inventory and different periods are handled due the existence of products exchange on tanks, maintenance of tanks and periods in which the pipelines should not be used due heating constraints. The tanking park problem is also addressed in a more precise way than previous works. Heating constraints and blends of products are also treated. To solve this problem in a reasonable computational time (less than 1 minute) it is utilized a decomposition approach and Mixed Integer Linear Programming (MILP) models and heuristics to solve these sub-problems. It is also used real operational data of this pipeline network for experimentation purposes. With the analysis of the results it is concluded that the approach here described for the solution of the presented problem is viable in computational times terms and that the obtained results can assist the specialists of the network in the decision-making process.