Otimização do transporte de derivados claros de petróleo em rede de dutos utilizando programação linear inteira mista

Abstract

This work applies Mixed Integer Linear Programming for a new approach to batch sequencing in a real-world pipeline network. The proposed model is immersed in an optimization framework to aid the operational scheduling of light oil derivatives. The considered pipeline network consists of 14 nodes (areas), with 4 refineries, 2 harbors, 2 final clients, 5 distribution terminals, and a node that links valves and pumps, interconnected by 30 pipelines. In this network, 35 light oil derivatives can be transported. The scheduling process involves complex operational constraints for determining transfer and storage activities, being a combinatorial optimization problem difficult to solve. Due to the complexity of the problem, a decomposition approach is applied for modeling purposes. This strategy is based on a hierarchical division in the three key elements of scheduling: Assignment, Sequencing, and Timing. The Sequencing Module is addressed within this work. It is developed a continuous time MILP model that represents the transportation of light oil derivatives through pipelines. The aim is to obtain the pumping sequencing of batches in the sources, as well as the transportation sequences in pipelines, considering the management of inventories. Additionally, within the sequencing module, constraints to avoid flow reversions or insertion of plug products are modeled. Tests are performed using real scenarios for a time horizon of, approximately, 30 days. Comparative results with a heuristic approach and derived versions of the proposed model are presented in order to investigate the computational cost increase with the addition of new modeling features. The obtained results suggest the possibility of significant operational cost reductions with an adequate management of inventories.