化工学报 ›› 2025, Vol. 76 ›› Issue (6): 2813-2827.DOI: 10.11949/0438-1157.20241183

• 过程系统工程 • 上一篇    下一篇

多效蒸发海水淡化系统变量相关性分析与全周期操作优化

袁梦星(), 孙琳(), 罗雄麟   

  1. 中国石油大学(北京)人工智能学院自动化系,北京 102249
  • 收稿日期:2024-10-24 修回日期:2024-11-26 出版日期:2025-06-25 发布日期:2025-07-09
  • 通讯作者: 孙琳
  • 作者简介:袁梦星(1999—),男,硕士研究生,yuan121617@163.com
  • 基金资助:
    国家自然科学基金项目(62073142)

Variable correlation analysis and full-cycle operation optimization of a multi-effect evaporative desalination system

Mengxing YUAN(), Lin SUN(), Xionglin LUO   

  1. Department of Automation, School of Artificial Intelligence, China University of Petroleum, Beijing 102249, China
  • Received:2024-10-24 Revised:2024-11-26 Online:2025-06-25 Published:2025-07-09
  • Contact: Lin SUN

摘要:

多效蒸发是当前最为主要的海水淡化方法之一,其包含多个操纵变量且变量间相互耦合共同作用。在实际生产过程中,常以满足一定淡水产量要求和造水比最优为目标进行操作优化。同时随着生产运行,操作条件和要求也时常发生变化,根据工艺设计的操作方案难以在全周期运行过程中实现持续优化。首先提出一种操作变量决策策略,通过相关性及通径分析确定各操作变量与二次蒸汽产量的内在联系以及作用机制,并综合考虑系统各效间的关联性以及装置能量回收,最终确定优化决策变量。同时,考虑到稳态优化大多基于初始状态,兼顾全运行周期,引入滚动优化方法,以最大化全周期累积造水比为目标,提出一种全周期操作优化策略。结果表明,相比于示例仿真,全周期操作优化方法的累积造水比显著提升了12.15%。

关键词: 多效蒸发, 耦合特性, 相关分析, 全周期, 累积造水比, 滚动优化

Abstract:

Multi-effect evaporation is one of the most important desalination methods at present, which contains multiple manipulated variables and the variables are coupled and act together. In the actual production process, operations are frequently optimized to meet specific freshwater production requirements and to achieve the optimal gained output ratio. Simultaneously, the operating conditions and requirements fluctuate periodically throughout production runs, which complicates the continuous optimization of the operational scheme established in accordance with the process over the entire operational cycle. This paper firstly proposes a decision-making strategy for operating variables, which determines the intrinsic relationship and mechanism between each operational variable and secondary steam production through correlation and path analysis, and comprehensively considers the correlation between system effects and device energy recovery, ultimately determining the optimized decision variable. Furthermore, recognizing that steady-state optimization is primarily based on initial conditions, this study addresses the dynamic changes throughout the full operational cycle. The paper introduces a rolling optimization method and proposes a full-cycle operational optimization strategy aimed at maximizing the cumulative gained output ratio over the entire cycle. The results indicate that, compared to the example simulation, the cumulative gained output ratio achieved through the full-cycle operational optimization method is significantly improved by 12.15%.

Key words: multi-effect evaporation, coupling characteristics, correlation analysis, full cycle, cumulative gained output ratio, rolling optimization

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