文献类型：期刊文献

英文题名：A Data-Driven Rolling-Horizon Online Scheduling Model for Diesel Production of a Real-World Refinery

作者：Cao Cuiwen[1];Gu Xingsheng[1];Xin Zhong[2]

机构：[1]E China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, State Key Lab Chem Engn, Sch Chem Engn, Shanghai 200237, Peoples R China

年份：2013

卷号：59

期号：4

起止页码：1160

外文期刊名：AICHE JOURNAL

收录：;EI(收录号：20131316151065);WOS:【SCI-EXPANDED(收录号:WOS:000317466000014)】；

基金：The authors thank the anonymous reviewers for their valuable comments and suggestions which greatly improved the contents of this article. Financial support from the National High Technology Research and Development Program of China (No. 2009AA04Z141, 2011AA05A20401), Fundamental Research Funds for the Central Universities, the National Natural Science Foundation of China (No. 61174040, 21106039, U1162110), and Shanghai commission of Nature Science (No. 10ZR1408300, 12ZR1408100) is also grateful appreciated.

语种：英文

外文关键词：rolling-horizon optimal control strategy; data-driven; online scheduling; diesel production; uncertainty

摘要：A rolling-horizon optimal control strategy is developed to solve the online scheduling problem for a real-world refinery diesel production based on a data-driven model. A mixed-integer nonlinear programming (MINLP) scheduling model considering the implementation of nonlinear blending quality relations and quantity conservation principles is developed. The data variations which drive the MINLP model come from different sources of certain and uncertain events. The scheduling time horizon is divided into equivalent discrete time intervals, which describe regular production and continuous time intervals which represent the beginning and ending time of expected and unexpected events that are not restricted to the boundaries of discrete time intervals. This rolling-horizon optimal control strategy ensures the dimension of the diesel online scheduling model can be accepted in industry use. LINGO is selected to be the solution software. Finally, the daily diesel scheduling scheme of one entire month for a real-world refinery is effectively solved. (C) 2012 American Institute of Chemical Engineers AIChE J, 59: 1160-1174, 2013