详细信息

Efficient rolling horizon approach to a crude oil scheduling problem for marine-access refineries  ( SCI-EXPANDED收录 EI收录)  

文献类型:期刊文献

英文题名:Efficient rolling horizon approach to a crude oil scheduling problem for marine-access refineries

作者:Yang, Yunning[1];He, Renchu[1];Yu, Guo[1];Du, Wei[1];Yang, Minglei[1];Du, Wenli[1]

机构:[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份:2023

卷号:170

外文期刊名:COMPUTERS & CHEMICAL ENGINEERING

收录:;EI(收录号:20230213367243);WOS:【SCI-EXPANDED(收录号:WOS:000921703000001)】;

基金:This work was supported by National Natural Science Fund for Distinguished Young Scholars, China (61725301) , International (Regional) Cooperation and Exchange Project, China (61720106008) , National Natural Science Foundation of China (62073142) , the Programme of Introducing Talents of Discipline to Universities (the 111 Project) , China under Grant B17017 and Shanghai AI Lab, China.

语种:英文

外文关键词:Crude oil scheduling; Rolling horizon

摘要:We aim to address a crude oil scheduling problem for a marine-access refinery considering the storage, blending and processing of complex types of crude and the demands of feedstock from downstream units. Since diverse crude oils present significant variations in compositions, properties, and yields, the incoming crude oils should be appropriately stored and blended in refinery tanks and a proper charging schedule of tanks feeding crude distillation units (CDUs) should be determined to meet quality specifications and production demands. Meanwhile, complex types of crude can eventually lead to a complex mixture in the storage tanks, which affects the model size and final solution of the mathematical model. In this paper, a full-space mixed integer nonlinear programming (MINLP) model is proposed with new constraints represented by (1) a better optimization for the operation of crude unloading and blending, and (2) an application of heuristic rules to deal with the complex mixtures in the tank. An efficient rolling horizon approach with variable fixing strategy and constraint pruning strategy is developed for instances of large model sizes. Case studies are performed to show the efficiency of this approach compared with the other methods, and the influence of new constraints on the final solution. The results show that it is efficient to find a feasible solution of reasonable quality.

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