Energy saving methodology for the SWRO desalination process: control of operating temperature and pressure

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@Article{Kim:2009:DS2,

• author = "Seung Joon Kim and Young Geun Lee and Sanghoun Oh and Yun Seok Lee and Young Mi Kim and Moon Gu Jeon and Sangho Lee and In S. Kim and Joon Ha Kim",
• title = "Energy saving methodology for the SWRO desalination process: control of operating temperature and pressure",
• journal = "Desalination",
• year = "2009",
• volume = "247",
• pages = "260--270",
• number = "1-3",
• keywords = "genetic algorithms, genetic programming, Seawater reverse osmosis (SWRO)",
• DOI = "doi:10.1016/j.desal.2008.12.006",
• ISSN = "0011-9164",
• URL = "http://www.sciencedirect.com/science/article/B6TFX-4X502WT-Y/2/733f20864f4a10d23d73aef497596e27",
• abstract = "This study proposes a new operation methodology for energy saving in the Fujairah seawater reverse osmosis (SWRO) plant, as the optimum feed pressure is determined at the controlled operating temperature. To this end, two functional models were developed by genetic programming (GP) using two-year operational data. The data revealed that the required feed pressure for the plant operation was potentially overestimated. Based on the developed models, simulation of a three-step sequential control was carried out to reduce and optimise the required feed pressure. The simulation results first indicate that the temperature control significantly reduces the required feed pressure at a reasonably high temperature. Second, as the permeate water flow rate (PFR) is determined by the optimised feed pressure instead of the permeate pressure actually used to maintain a steady PFR in Fujairah, the required feed pressure could be substantially reduced. As a result, the proposed methodology can potentially reduce the required feed pressure, by approximately 10 bar, under the identical performance of both PFR and permeate water total dissolved solids (TDS). This study implies that the optimization of operation and management of MSF-hybridized SWRO processes can considerably improve the efficiency of the desalination process in terms of energy and, eventually, cost saving.",

}

Genetic Programming entries for Seung Joon Kim Young Geun Lee Sanghoun Oh Yun Seok Lee Young Mi Kim Moongu Jeon Sangho Lee In S Kim Joon Ha Kim

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