SCI和EI收录∣中国化工学会会刊

中国化学工程学报 ›› 2021, Vol. 40 ›› Issue (12): 167-178.DOI: 10.1016/j.cjche.2020.12.028

• Process Systems Engineering and Process Safety • 上一篇    下一篇

Optimization of circulating cooling water systems based on chance constrained programming

Bo Liu1, Yufei Wang1, Xiao Feng2   

  1. 1. State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing 102249, China;
    2. School of Chemical Engineering & Technology, Xi'an Jiaotong University, Xi’an 710049, China
  • 收稿日期:2020-11-05 修回日期:2020-12-03 出版日期:2021-12-28 发布日期:2022-01-14
  • 通讯作者: Yufei Wang,E-mail:wangyufei@cup.edu.cn
  • 基金资助:
    Financial support from the National Natural Science Foundation of China (22022816, 22078358) are gratefully acknowledged.

Optimization of circulating cooling water systems based on chance constrained programming

Bo Liu1, Yufei Wang1, Xiao Feng2   

  1. 1. State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing 102249, China;
    2. School of Chemical Engineering & Technology, Xi'an Jiaotong University, Xi’an 710049, China
  • Received:2020-11-05 Revised:2020-12-03 Online:2021-12-28 Published:2022-01-14
  • Contact: Yufei Wang,E-mail:wangyufei@cup.edu.cn
  • Supported by:
    Financial support from the National Natural Science Foundation of China (22022816, 22078358) are gratefully acknowledged.

摘要: Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained under deterministic conditions may not be stable and economical. This paper studies the optimization of circulating cooling water systems under uncertain circumstance. To improve the reliability of the system and reduce the water and energy consumption, the influence of different uncertain parameters is taken into consideration. The chance constrained programming method is used to build a model under uncertain conditions, where the confidence level indicates the degree of constraint violation. Probability distribution functions are used to describe the form of uncertain parameters. The objective is to minimize the total cost and obtain the optimal cooling network configuration simultaneously. An algorithm based on Monte Carlo method is proposed, and GAMS software is used to solve the mixed integer nonlinear programming model. A case is optimized to verify the validity of the model. Compared with the deterministic optimization method, the results show that when considering the different types of uncertain parameters, a system with better economy and reliability can be obtained (total cost can be reduced at least 2%).

关键词: Circulating cooling water system, Uncertainty, Chance constrained programming, Design, Optimization, Simulation

Abstract: Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained under deterministic conditions may not be stable and economical. This paper studies the optimization of circulating cooling water systems under uncertain circumstance. To improve the reliability of the system and reduce the water and energy consumption, the influence of different uncertain parameters is taken into consideration. The chance constrained programming method is used to build a model under uncertain conditions, where the confidence level indicates the degree of constraint violation. Probability distribution functions are used to describe the form of uncertain parameters. The objective is to minimize the total cost and obtain the optimal cooling network configuration simultaneously. An algorithm based on Monte Carlo method is proposed, and GAMS software is used to solve the mixed integer nonlinear programming model. A case is optimized to verify the validity of the model. Compared with the deterministic optimization method, the results show that when considering the different types of uncertain parameters, a system with better economy and reliability can be obtained (total cost can be reduced at least 2%).

Key words: Circulating cooling water system, Uncertainty, Chance constrained programming, Design, Optimization, Simulation