Improved Swing-Cut Modeling for Planning and Scheduling of Oil-Refinery Distillation Units

Abstract

Nonlinear planning and scheduling models for crude-oil atmospheric and vacuum distillation units are essential to manage increased complexities and narrow margins present in the petroleum industry. Traditionally, conventional swing-cut modeling is based on fixed yields with fixed properties for the hypothetical cuts that swing between adjacent light and heavy distillates, which can subsequently lead to inaccuracies in the predictions of both its quantity and quality. A new extension is proposed to better predict quantities and qualities for the distilled products by taking into consideration that we require corresponding light and heavy swing-cuts with appropriately varying qualities. By computing interpolated qualities relative to its light and 2 heavy swing-cut quantities, we can show an improvement in the accuracy of the blended or pooled quality predictions. Additional nonlinear variables and constraints are necessary in the model, but it is shown that these are relatively easy to deal with in the nonlinear optimization.

Hybrid model for optimization of crude oil distillation units

“…As the assumption is that the properties of each swing cut are constant for the entire TBP range of the swing cut, this methodology can not represent accurately the fact that the properties are distributed nonlinearly across TBP intervals. In order to improve accuracy, Menezes et al divided each swing cut into “light part” and “heavy part.” Their approach still leaves open the question of how to determine the size of the cut in relationship to the separation capabilities of the distillation tower.…”

“…Once product TBP curve is known, its bulk properties can be computed by the methodology which is used by rigorous simulation models (pseudocomponents “carry” with them other properties and are blended to compute product bulk properties), as illustrated by Menezes et al…”

Impact of crude distillation unit model accuracy on refinery production planning

“…Alattas et al (2011) introduced a fractionation index-based CDU model and integrated it into a simple refinery model; this model requires that the fractionation indices be finetuned for different operating modes. Menezes et al (2013) divided swing cuts into light and heavy parts to improve the prediction of product properties.…”

Nonlinear Blend Scheduling via Inventory Pinch-based Algorithm using Discrete- and Continuous-time Models

“…Computation of optimal production plans is usually based on linear programming (LP) or successive linear programming (SLP) models 2,3,4 since these approaches have proven to be robust and provide good answers under a variety of circumstances. Production planning models are constructed by dividing the time horizon in a number of periods, the length of which is usually set equal to some calendar unit (e.g.…”

“…If the models are nonlinear, the likelihood of encountering convergence problems increases significantly as the problem size increases. However, formulation of planning models with nonlinearities is becoming more spread in practice 4,5,6,7 in order to compute more accurate solutions and increase profitability. Scheduling is in many cases a NP-complete 8,9 or NP-hard 10 problem, which means that there is no polynomial-bounded algorithm to solve it, even if the underlying supply chain models are linear.…”