Model and Design of Cogeneration System for Different Demands of Desalination Water, Heat and Power Production

吴现力; 胡仰栋; 伍联营; 李红

doi:10.1016/S1004-9541(14)60036-7

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Model and Design of Cogeneration System for Different Demands of Desalination Water, Heat and Power Production

过程系统工程与过程安全 | Updated：2026-01-06

- Model and Design of Cogeneration System for Different Demands of Desalination Water, Heat and Power Production
- Chinese Journal of Chemical Engineering Vol. 22, Issue 3, Pages: 330-3381004-954160036-7(2014)
- Affiliations：
  
  College of Chemistry and Chemical Engineering, Ocean University of China,Qingdao,China,266100
- Author bio：
- Funds：
- DOI：10.1016/S1004-9541(14)60036-7
  CLC：
- Published：2014
- Accepted：
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WU Xianli, HU Yangdong, WU Lianying, LI Hong. Model and Design of Cogeneration System for Different Demands of Desalination Water, Heat and Power Production[J]. Chin.J.Chem.Eng., 2014, 22(3): 330-338.
DOI：

WU Xianli, HU Yangdong, WU Lianying, LI Hong. Model and Design of Cogeneration System for Different Demands of Desalination Water, Heat and Power Production[J]. Chin.J.Chem.Eng., 2014, 22(3): 330-338. DOI： 10.1016/S1004-9541(14)60036-7.

摘要

Abstract

In order to improve the energy efficiency

reduce the CO

emission and decrease the cost

a cogeneration system for desalination water

heat and power production was studied in this paper. The superstructure of the cogeneration system consisted of a coal-based thermal power plant (TPP)

a multi-stage flash desalination (MSF) module and reverse osmosis desalination (RO) module. For different demands of water

heat and power production

the corresponding optimal production structure was different. After reasonable simplification

the process model of each unit was built. The economical model

including the unit investment

and operation and maintenance cost

was presented. By solving this non-linear programming (NLP) model

whose objective is to minimize the annual cost

an optimal cogeneration system can be obtained. Compared to separate production systems

the optimal system can reduce 16.1%-21.7% of the total annual cost

showing this design method was effective.

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