Optimization of design and operational parameters of hybrid MED-RO desalination system via modelling, simulation and engineering application

• Current research and development of standalone and hybrid desalination technologies. • Mathematical models were developed for hybrid MED-RO desalination system. • The key parameters influences on RO process in hybrid system were analyzed. • The optimal design and operational parameters of hybrid system were achieved through simulations and sensitivity analysis. • Engineering application and analysis of hybrid MED-RO desalination system based on actual operation data. Based on the current research, the hybridization of desalination technologies has proven to be an effective method of enhancing system performance, minimizing energy consumption, and reducing product water cost. This study focuses on a hybrid MED-RO desalination plant in a large coastal steel enterprise situated in Northeast Asia, China. A comparative analysis of distinct hybrid systems was undertaken, followed by the selection of an optimal process route that aligns with the site-specific conditions and the requirements of downstream freshwater users. To investigate the influences of feed and operational factors on RO process performance, mathematical models were developed for water balance, RO module performance, energy consumption, and economic indicators. Furthermore, according to actual plant conditions, the software simulation and cost benefit analysis were performed for the hybrid desalination system sensitivity analysis and optimization. The outcomes including permeate qualities, concentrate salinity, specific energy consumption, and economic indicators were analyzed to achieve the optimal hybrid system design and operational parameters. Finally, through engineering application of the optimized parameters, the hybrid system performance underwent notable improvement. The calculations reveal that, in comparison to standalone or alternative hybrid systems, this hybrid system exhibits superior energy-saving efficiency, lower operational costs, and reduced carbon emissions. Specifically, the system achieves a recovery rate of approximately 54.22%, with an average product water cost of 0.5582US$/m³. Additionally, the energy consumption is 1.015kgce/m³, translating to an equivalent carbon emission of 2.49kg/m³.

Authors

Institutions

Publication Details

Journal
Results in Engineering
Published
2024-11-07
DOI
https://doi.org/10.1016/j.rineng.2024.103253
Citations
12
Primary Topic
Membrane Separation Technologies
Type
article
Field-Weighted Citation Impact
2.42

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of design and operational parameters of hybrid MED-RO desalination system via modelling, simulation and engineering application

Liyun Wu, Zhixin Tang, Zhong Zheng, Dongming Zhang et al.
12 citations
Results in Engineering
Membrane Separation Technologies
2.42
article

Optimization of design and operational parameters of hybrid MED-RO desalination system via modelling, simulation and engineering application

Liyun Wu, Zhixin Tang, Zhong Zheng, Dongming Zhang, Yangang Zhang, Bo Zhang
article en
12 citations

Abstract

• Current research and development of standalone and hybrid desalination technologies. • Mathematical models were developed for hybrid MED-RO desalination system. • The key parameters influences on RO process in hybrid system were analyzed. • The optimal design and operational parameters of hybrid system were achieved through simulations and sensitivity analysis. • Engineering application and analysis of hybrid MED-RO desalination system based on actual operation data. Based on the current research, the hybridization of desalination technologies has proven to be an effective method of enhancing system performance, minimizing energy consumption, and reducing product water cost. This study focuses on a hybrid MED-RO desalination plant in a large coastal steel enterprise situated in Northeast Asia, China. A comparative analysis of distinct hybrid systems was undertaken, followed by the selection of an optimal process route that aligns with the site-specific conditions and the requirements of downstream freshwater users. To investigate the influences of feed and operational factors on RO process performance, mathematical models were developed for water balance, RO module performance, energy consumption, and economic indicators. Furthermore, according to actual plant conditions, the software simulation and cost benefit analysis were performed for the hybrid desalination system sensitivity analysis and optimization. The outcomes including permeate qualities, concentrate salinity, specific energy consumption, and economic indicators were analyzed to achieve the optimal hybrid system design and operational parameters. Finally, through engineering application of the optimized parameters, the hybrid system performance underwent notable improvement. The calculations reveal that, in comparison to standalone or alternative hybrid systems, this hybrid system exhibits superior energy-saving efficiency, lower operational costs, and reduced carbon emissions. Specifically, the system achieves a recovery rate of approximately 54.22%, with an average product water cost of 0.5582US$/m³. Additionally, the energy consumption is 1.015kgce/m³, translating to an equivalent carbon emission of 2.49kg/m³.

Results in EngineeringVol. 24
Jinggangshan University (CN), Chongqing University (CN), Shandong Iron and Steel Group (China) (CN), Shougang (China) (CN)
Ministry of Science and Technology of the People's Republic of China, Beijing Municipal Science and Technology Commission
Openalex Percentile: Top 12%
Membrane Separation Technologies
2.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.