Stochastic optimization-based approach for simultaneous process design and HEN synthesis of tightly-coupled RO-ORC-HI systems under seasonal uncertainty

Zhichao Chen, Zhibin Lu, Bingjian Zhang, Qinglin Chen, Chang He, Haoshui Yu, Jingzheng Ren

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

The use of waste heat powered wastewater desalination by coupling an organic Rankine cycle (ORC) with reverse osmosis (RO) has been recognized as a promising solution to desalination. Herein, a tightly-coupled system that allows for optimally customizing the RO-ORC to a background process via heat integration (HI) is developed to minimize the expected desalination cost, while accounting for the seasonal wastewater variability. Moreover, the developed RO-ORC-HI system can improve the membrane permeability by preheating the feed wastewater. To achieve these goals, a stochastic optimization-based solution strategy is proposed by sequentially considering (1) a Pinch-based Duran-Grossman model embedded with uncertainty realization for performing optimal HI during process optimization; (2) a flexible multi-scenario heat exchanger network (HEN) synthesis model that minimizes the total annualized cost of HEN based on a customized stage-wise superstructure. Finally, the behaviors of the proposed system and solution strategy are illustrated through its comparison with a deterministic solution.

Original languageEnglish
Article number116961
JournalChemical Engineering Science
Volume246
DOIs
Publication statusPublished - 31 Dec 2021

Keywords

  • Duran-Grossman model
  • flexible HEN synthesis
  • Rankine cycle
  • Reverse osmosis
  • Seasonal uncertainty
  • Stochastic optimization
  • Waste heat powered desalination

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)
  • Industrial and Manufacturing Engineering

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