文献类型：期刊文献

英文题名：Operational optimization of industrial steam systems under uncertainty using data-Driven adaptive robust optimization

作者：Zhao, Liang[1,2];Ning, Chao[2];You, Fengqi[2]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Cornell Univ, Robert Frederick Smith Sch Chem & Biomol Engn, Ithaca, NY 14853 USA

年份：2019

卷号：65

期号：7

外文期刊名：AICHE JOURNAL

收录：;EI(收录号：20190106332357);WOS:【SCI-EXPANDED(收录号:WOS:000475690500012)】；

基金：Chao Ning and Fengqi You acknowledge financial support from National Science Foundation (NSF) CAREER Award (CBET-1643244). Liang Zhao acknowledges funding from National Natural Science Foundation of China (61873092, 61590923), and National Science Fund of China for Distinguished Young Scholars (61725301).

语种：英文

外文关键词：industrial steam system; operational optimization; big data; adaptive robust optimization; uncertainty

摘要：This article addresses the operational optimization of industrial steam systems under device efficiency uncertainty using a data-driven adaptive robust optimization approach. A semiempirical model of steam turbine is first developed based on process mechanism and operational data. Uncertain parameters of the proposed steam turbine model are further derived from the historical process data. A robust kernel density estimation method is then used to construct the uncertainty sets for modeling these uncertain parameters. The data-driven uncertainty sets are incorporated into a two-stage adaptive robust mixed-integer linear programming (MILP) framework for operational optimization of steam systems to minimize the total operating cost. Integer variables are introduced to model the on/off decisions of the steam turbines and electrical motors, which are the major energy consumers of the steam system. By applying the affine decision rule, the proposed multilevel optimization model is transformed into its robust counterpart, which is a single-level MILP problem. The proposed framework is applied to the steam system of a real-world ethylene plant to demonstrate its applicability. (c) 2018 American Institute of Chemical Engineers AIChE J, 65: e16500 2019