Total Site Heat Integration: Utility selection and optimisation using cost and exergy derivative analysis

被引:19
|
作者
Tarighaleslami, Amir H. [1 ]
Walmsley, Timothy G. [2 ]
Atkins, Martin J. [1 ]
Walmsley, Michael R. W. [1 ]
Neale, James R. [1 ]
机构
[1] Univ Waikato, Sch Engn, Energy Res Ctr, Private Bag 3105, Hamilton 3240, New Zealand
[2] Brno Univ Technol, Fac Mech Engn, NETME Ctr, SPIL, Brno, Czech Republic
关键词
Total Site Heat Integration; Optimisation; Utility temperature; Exergy destruction; Total annualised cost; Utility cost; MINIMUM TEMPERATURE DIFFERENCE; NONISOTHERMAL UTILITIES; PROCESS DESIGN; SYSTEMS; POWER; RECOVERY; TARGETS; COGENERATION; METHODOLOGY; NETWORKS;
D O I
10.1016/j.energy.2017.09.148
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper presents a new Total Site Heat Integration utility temperature selection and optimisation method that can optimise both non-isothermal (e.g. hot water) and isothermal (e.g. steam) utilities. None of the existing methods addresses both non-isothermal and isothermal utility selection and optimisation incorporated in a single procedure. The optimisation affects heat recovery, the number of heat exchangers in Total Site Heat Exchanger Network, heat transfer area, exergy destruction (ED), Utility Cost (UC), Annualised Capital Cost (CC), and Total Annualised Cost (TC). Three optimisation parameters, UC, ED, and TC have been incorporated into a derivative based optimisation procedure where derivatives are minimised sequentially and iteratively based on the specified approach. The new optimisation procedure has been carried out for three different approaches as the combinations of optimisation parameters based on the created derivative map. The merits of the new method have been illustrated using three case studies. These case studies represent a diverse range of processing types and temperatures. Results for the case studies suggest the best derivative optimisation approach is to first optimise UC in combination with ED and then optimise TC. For this approach, TC reductions between 0.6 and 4.6% for different case studies and scenarios are achieved. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:949 / 963
页数:15
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