Model-based real-time optimization of automotive gasoline blending operations

被引：98

作者：

Singh, A

Forbes, JF ^{[1
]}

Vermeer, PJ

Woo, SS

机构：

[1] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 2G6, Canada

[2] Univ Toronto, Dept Chem Engn & Appl Chem, Toronto, ON, Canada

[3] Imperial Oil Ltd, Toronto, ON, Canada

[4] Sunoco Inc, Sarnia, ON, Canada

来源：

JOURNAL OF PROCESS CONTROL | 2000年 / 10卷 / 01期

基金：

加拿大自然科学与工程研究理事会;

关键词：

blending; optimization; control;

D O I：

10.1016/S0959-1524(99)00037-2

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Gasoline blending is a key process in the successful operation of most petroleum refineries and real-time optimization (RTO) of gasoline blend recipes has the potential to provide a competitive benefit for oil refiners. The trend toward the use of "running" tanks for blender feedstocks and the recent advances in measurement technology have provided the opportunity for improved blending performance using RTO. This paper provides an improved formulation for the gasoline blend optimization problem that incorporates both the blend horizon and a stochastic model of disturbances into the RTO problem. The proposed approach is illustrated with a blender simulation study. (C) 1999 Elsevier Science Ltd. All rights reserved.

引用

页码：43 / 58

页数：16