Multi-objective optimization of RO desalination plants

A process optimization method has been developed for the design of reverse osmosis (RO) processes. RO process configurations are systematically generated using a flexible superstructure and evaluated by economical (investment and operating costs), technical (energy requirement, water recovery rate)...

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Bibliographic Details
Published in:Desalination Vol. 222; no. 1; pp. 96 - 118
Main Authors: Vince, François, Marechal, François, Aoustin, Emmanuelle, Bréant, Philippe
Format: Journal Article Conference Proceeding
Language:English
Published: Amsterdam Elsevier B.V 01.03.2008
Elsevier
Subjects:
Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization
Applied sciences
Chemical engineering
Drinking water and swimming-pool water. Desalination
Economical costs
Environmental impacts
Exact sciences and technology
Membrane separation (reverse osmosis, dialysis...)
Multi-objective optimization
Pollution
Process design
Reverse osmosis (RO) desalination
Water treatment and pollution
Process design
Environmental impacts
Economical costs
Multi-objective optimization
Reverse osmosis (RO) desalination
Desalination plant
Life cycle (environment)
Mixed integer programming
Non linear programming
Brackish water
Indicator
Optimization
Optimal design
Operating conditions
Membrane separation
Desalination
Environment impact
Superstructure
Reverse osmosis
Mathematical programming
ISSN:0011-9164, 1873-4464
Online Access:Get full text
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Summary:A process optimization method has been developed for the design of reverse osmosis (RO) processes. RO process configurations are systematically generated using a flexible superstructure and evaluated by economical (investment and operating costs), technical (energy requirement, water recovery rate) and environmental performance indicators (Life Cycle Assessment). The simultaneous optimization of the RO process layout and operating conditions constitutes a mixed-integer nonlinear programming (MINLP) problem, which is solved using a multi-objective optimization (MOO) approach. The MOO identifies the best technological alternatives for the set of selected objectives. In a given context, it allows to define a set of optimal solutions representing the trade-off between conflicting objectives such as economical costs and environmental impacts. As a case study, the methodology is applied on a brackish water reverse osmosis (BWRO) desalination project, for which the optimal design is characterized depending on the economical conditions.
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ISSN:0011-9164
1873-4464
DOI:10.1016/j.desal.2007.02.064