Operational Optimization of Crude Distillation Units with Unknown and Changing Crudes
AIChE Spring Meeting and Global Congress on Process Safety
2018 Spring Meeting and 14th Global Congress on Process Safety
21st Topical Conference on Refinery Processing
Operational Excellence in Refinery Distillation
Monday, April 23, 2018 - 1:30am to 1:57am
In this work, a framework for solving the problem using data generated from optimization models is proposed. First, the process data under optimal operating conditions of different crude scenarios are generated from the optimization model. Next, the adjustable variables are divided into two groups, primary variables and secondary variables through data analysis. The purpose of the grouping procedure is to avoid over-optimization caused by inaccuracies of the model. Primary variables contribute to most of the economic potentials in all scenarios. Third, different strategies are applied to primary and secondary variables. âInsightâ variables, which represents common features among all crude scenarios, are extracted from the data and paired with the primary variables using self-optimizing control technique. A multi-input multi-output controller is possible to be designed to adjust the primary variables so that the insight variables are maintained at constant values. For secondary variables, two strategies are proposed. The simplest way is to keep them directly at constant values. The second method is to construct the correlation between the primary and secondary variables through the data. In this way, the secondary variables can be determined after the primary variables are adjusted to near-optimal values.