Operational optimization of large-scale parallel-unit SWRO desalination plant using differential evolution algorithm.

A large-scale parallel-unit seawater reverse osmosis desalination plant contains many reverse osmosis (RO) units. If the operating conditions change, these RO units will not work at the optimal design points which are computed before the plant is built. The operational optimization problem (OOP) of...

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Publicado en:Scientific World Journal pp. 584068 - 584069
Autores principales: Wang, Jian, Wang, Xiaolong, Jiang, Aipeng, Jiangzhou, Shu, Li, Ping
Formato: research Journal Article
Publicado: Wiley-Blackwell 2014
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Wiley-Blackwell
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        10.1155/2014/584068
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        atl: Operational optimization of large-scale parallel-unit SWRO desalination plant using differential evolution algorithm.
      aug:
        au:
          Wang, Jian
          Wang, Xiaolong
          Jiang, Aipeng
          Jiangzhou, Shu
          Li, Ping
        affil: School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027, China ; Institute of Energy Utilization & Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
      sug:
        subj:
          Algorithms
          Osmolar Concentration
          Sodium Chloride
          Water Supply Methods
          Models, Theoretical
          Osmosis
      ab: A large-scale parallel-unit seawater reverse osmosis desalination plant contains many reverse osmosis (RO) units. If the operating conditions change, these RO units will not work at the optimal design points which are computed before the plant is built. The operational optimization problem (OOP) of the plant is to find out a scheduling of operation to minimize the total running cost when the change happens. In this paper, the OOP is modelled as a mixed-integer nonlinear programming problem. A two-stage differential evolution algorithm is proposed to solve this OOP. Experimental results show that the proposed method is satisfactory in solution quality.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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