(72i) Synthesis and Optimization of Integrated Water and Membrane Network Systems with Multiple Electrodialysis Regenerators
AIChE Spring Meeting and Global Congress on Process Safety
Monday, April 27, 2015 - 5:00pm to 7:00pm
The increasing cost of freshwater and wastewater treatment coupled with stringent environmental regulations have pushed processing industries towards sustainable engineering emphasizing the need for water minimization. This can be achieved through the implementation of process integration strategies such as water recycle, reuse, regeneration-recycle and regeneration-reuse between water sources, water sinks and regenerators/partial water treaters; a concept referred to as water allocation planning (WAP). Most work that has addressed this problem approach it through superstructure optimization and it has been the norm to represent the regenerators as ‘black-boxes’. These are simplified linear models that do not accurately capture the regenerator performances and energy consumption.
This work addresses the WAP problem using superstructure-based framework to obtain an optimal integrated water network with multiple electrodialysis regenerators. A comprehensive formulation comprised of a detailed electrodialysis mathematical model that is linked to a water network model is proposed. The dynamics of regeneration which includes important design variables are captured in the detailed model such that a more accurate representation of the performance and costs associated with regeneration are represented. The objective is set to minimize the total annualized cost of the system which is made up of the total capital cost and operational costs. Piping costs, both capital and operational, are also included in the model. To demonstrate the proposed approach, the model is applied to a pulp and paper plant case study. The optimization problem, presented as a mixed integer nonlinear programming (MINLP) problem, is solved and the results indicate a potential significant reduction in freshwater use and wastewater generation that results in a 12% reduction in the total annualized cost of the system.
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