Scheduling of multi-pipeline crude oil blending based on constrained ordinal optimization

摘要

Blending can help refineries, which have to deal with different types of crude oil, obtain a qualified feedstock. In this paper, a novel scheduling strategy of multi-pipeline crude oil blending based on constrained ordinal optimization (COO) is proposed. The objective is to keep the property of feedstock, mainly described by the true boiling point (TBP) data, consistent and suitable. Firstly, a MINLP scheduling model is established. Then, an efficient COO algorithm based on a two-level optimization structure is proposed. Finally, the whole scheduling strategy is validated by a real case study.