In the literature, optimization models deal with planning and scheduling of several subsystems of the petroleum supply chain such as oilfield infrastructure, crude oil supply, refinery operations and product transportation. The focus of the present work is to propose a general framework for modeling petroleum supply chains. As a starting point, processing units are modeled based on the framework developed by Pinto et al. [Computers and Chemical Engineering 24 (2000) 2259]. Particular frameworks are then proposed to storage tanks and pipelines. Nodes of the chain are considered as grouped elementary entities that are interconnected by intermediate streams. The complex topology is then built by connecting the nodes representing refineries, terminals and pipeline networks. Decision variables include stream flow rates, properties, operational variables, inventory and facilities assignment. The resulting multiperiod model is a large-scale MINLP. The proposed model is applied to a real-world corporation and results show model performance by analyzing different scenarios.
This work focuses on the scheduling of an in-line diesel blending and distribution subsystem of an oil refinery. The formulation is based on a hybrid time representation in which time points are equally distributed along the time horizon, within which time slots of variable length are postulated. The hybrid time representation takes advantage of the flexibility of the continuous time representation and enables handling of intermediate due dates with the use of fixed time points. Time variables are defined in terms of resources instead of transfer operations leading to a smaller size formulation. Results from a real-world case are used to validate the proposed formulation that takes into consideration capacities and operating rules while minimizing costs. Results of the multiperiod scheduling are also compared to a day-ahead production planning policy. Computational efficiency is achieved after adding valid inequalities and symmetry breaking constraints.
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