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An ever-growing population together with globally depleting water resources pose immense stresses for water supply systems. Desalination technologies can reduce these stresses by generating fresh water from saline water sources. Reverse osmosis (RO), as the industry leading desalination technology, typically involves a complex network of membrane modules that separate unwanted particles from water. The optimal design and operation of these complex RO systems can be computationally expensive. In this work, we present a modeling and optimization strategy for addressing the optimal operation of an industrial-scale RO plant. We employ a feed-forward artificial neural network (ANN) surrogate modeling representation with rectified linear units as activation functions to capture the membrane behavior accurately. Several ANN set-ups and surrogate models are presented and evaluated, based on collected data from the H2Oaks RO desalination plant in South-Central Texas. The developed ANN is then transformed into a mixed-integer linear programming formulation for the purpose of minimizing energy consumption while maximizing water utilization. Trade-offs between the two competing objectives are visualized in a Pareto front, where indirect savings can be uncovered by comparing energy consumption for an array of water recoveries and feed flows.
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Emerging investigator series: toward the ultimate limit of seawater desalination with mesopelagic open reverse osmosis
Seawater desalination has become an important tool to attain global water security and sustainability. Among the available technologies, reverse osmosis (RO) has become the golden standard for seawater desalination due to its unparalleled energy efficiency. While RO is already efficient after development for half a century, there remains room for over 50% further reduction in energy consumption that can translate into tens of terawatt hours of potential annual energy saving. However, this significant energy saving cannot be achieved under the conventional paradigm of on-ground RO. In this analysis, we assess the idea of operating RO with open modules several hundred meters below the ocean surface ( i.e. , the mesopelagic zone). This new process, namely mesopelagic open reverse osmosis (MORO), can potentially push the energy consumption of seawater desalination to its theoretical limit. We first describe the concept of MORO, and then examine both the theoretical potential of energy saving and the practical challenges facing the implementation of MORO. Our analysis provides a theoretical framework for the future development of MORO for more sustainable desalination.
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- Award ID(s):
- 2017998
- PAR ID:
- 10291663
- Date Published:
- Journal Name:
- Environmental Science: Water Research & Technology
- Volume:
- 7
- Issue:
- 7
- ISSN:
- 2053-1400
- Page Range / eLocation ID:
- 1212 to 1219
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/D1EW00153A
