SPREAD - Exploring the decision space in energy systems synthesis

被引：11

作者：

Hennen, Maike ^{[1
]}

Lampe, Matthias ^{[1
]}

Voll, Philip ^{[1
]}

Bardow, Andre ^{[1
]}

机构：

[1] Rhein Westfal TH Aachen, Chair Tech Thermodynam, D-52056 Aachen, Germany

来源：

COMPUTERS & CHEMICAL ENGINEERING | 2017年 / 106卷

关键词：

Decision support; Synthesis of energy supply systems; Integer cuts; MILP; Near-optimal solutions; MULTIOBJECTIVE OPTIMIZATION; DESIGN; IDENTIFICATION; UNCERTAINTY; MULTIPLE; DISTANCE; SUPPORT; CUTS;

D O I：

10.1016/j.compchemeng.2017.06.002

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A method is presented to systematically analyze the decision space in the synthesis of energy supply systems. Commonly, synthesis problems are solved by mathematical optimization yielding a single optimal design. However, optimization is based on a model which never represents reality to perfection. Thus, the designer will be forced to revise parts of the optimal solution. We therefore support the design process by automatically identifying important features of good solutions. For this purpose, we analyze near-optimal solutions. To explore the decision space, we minimize and maximize both the number and the capacity of units while keeping the costs within a specified range. From this analysis, we derive insight into correlations between decisions. To support the decision maker, we represent the range of good design decisions and their correlations in the flowsheet of the energy system. The method is illustrated for the synthesis of an energy system in the pharmaceutical industry. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：297 / 308

页数：12

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