371653 Optimizing the Refinery – Advances in Planning and Scheduling Decision-Making Strategies

Tuesday, November 18, 2014: 3:45 PM
406 - 407 (Hilton Atlanta)
Dimitrios Varvarezos, Aspen Technology, Inc., Houston, TX

Despite significant progress in the last decade, refining planning and scheduling processes continue to present very challenging modeling and optimization problems.  In this work we discuss recent advances made in the area of refinery optimization.  In particular, we cover three prominent areas that significantly affect the overall refinery economics: (i) crude assay characterization, (ii) optimization and analysis of crude purchasing decisions and (iii) optimal blending strategies for refinery products.  The resulting problems represent some of the most challenging large-scale, mixed integer, non-convex optimization problems.

For the crude acquisition problem, we present advances in two key areas:  (a) the creation of a novel assay modeling framework based on molecular characterization that describes crude assays at the detailed molecular level; (b) the creation of a robust optimization framework based on a combination of Pareto-type analysis, parametric optimization, and goal programming.  This approach allows users to accurately represent the key refinery raw materials and their critical properties that affect the crude selection process.  Given this assay representation, we evaluate the range of actionable decision-making options around the optimal solution that simultaneously preserve the economic optimization while accounting for important strategic and operational goals not explicit in the economic objective function (such as supply uncertainty, scheduling and maintenance).

For the product blending problem, we present a novel modeling and optimization methodology that determines the optimal sequence and timing of blend events, as well as rundown component tank switches in order to handle the blending of “hot” streams into a finished product tank.  This solution incorporates multiple blend headers and multiple blends in a multi-period, event-driven campaign, using open-equation based optimization and modeling technology.  This development is comprehensive, practical, and superior to current practices.


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