Simultaneous Optimization of Crude Oil Blending and Purchase Planning with Delivery Uncertainty Consideration

Abstract

Crude-oil blending is a common practice to obtain qualified mixing oils for refinery processing at low costs. The blending component crudes are subject to inventory constraints, which in turn are dynamically affected by the refinery purchase plan including the crude-oil types, amounts, and delivery over a planned period of time. As the crude-oil price and availability constantly changes in a volatile market, the crude-oil blending and purchase planning should be coordinated and simultaneously optimized to maximize the potential profitability of a refinery plant. This becomes even more important when the uncertainty of crude-oil delivery time is also taken into account. In this paper, a general MINLP (mixed-integer nonlinear programming) model is developed to address the profit optimization of crude-oil blending and purchase planning in refinery plants. Inventory-related flexibility indexes are developed to characterize the ability of a refinery for handling the uncertainty of crude-oil delivery delays. In-depth relations between the production flexibility and the plant profit are also disclosed. The efficacy of the developed methodology is demonstrated by industrial case studies.