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Dynamic optimization of desalination system designs using Aspen Custom Modeler

Malik, S.N., Bahri, P.A. and Vu, L.T.T. (2016) Dynamic optimization of desalination system designs using Aspen Custom Modeler. Computer Aided Chemical Engineering, 38 . pp. 1539-1544.

Link to Published Version: http://dx.doi.org/10.1016/B978-0-444-63428-3.50261...
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Abstract

The economical and sustainable desalination processes are of supreme importance. The two desalination processes leading the market are the Multistage Flash (MSF) and Reverse Osmosis (RO) systems. New configurations by combining the MSF and RO in a hybrid system have also been studied. The hybrid desalination systems are believed to provide better water quality and lower power demand. However, there is very limited work around modeling and optimization of these systems. Moreover, no attempt has been made to study the transient behaviour of these systems. Thus further insight into these processes is required before implementing them on an industrial scale. In this paper, dynamic optimization is conducted to select the best configuration based on the economic objective function. The formulated dynamic optimization problem determines the optimal process configuration and process variables for different feed water concentrations. The optimization problem is implemented using a superstructure and the open loop dynamic models based on the first principles. The results of the study show that the cost reduces over time as the optimizer trade-offs between the capacities of both systems while determining the objective function and meeting the constraint on the product quality. The results provided by the dynamic model are necessary for the development of the optimal control structures. Thus in a future study, these dynamic models will be used to develop appropriate optimal control strategies for rejecting disturbances and to select proper start-up and shut-down procedures.

Publication Type: Journal Article
Murdoch Affiliation: School of Engineering and Information Technology
Publisher: Elsevier BV
Copyright: © 2016 Elsevier B.V.
Other Information: Abstract from: 26th European Symposium on Computer Aided Process Engineering
URI: http://researchrepository.murdoch.edu.au/id/eprint/34546
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