An Improved Linear Programming Approach for Simultaneous Optimization of Water and Energy
An optimization method based on Mixed Integer Linear Programming (MILP) has been developed for simultaneous optimization of water and energy (SOWE) in industrial processes. The superstructure integrates process thermal streams and optimizes the consumption of water while maximizing internal heat recovery to reduce thermal utility consumption. In this paper, additional concepts have been implemented in the superstructure to target the issues of the pulp and paper processes. Non-Isothermal Mixing (NIM) has been considered at different locations in order to reduce the number of thermal streams and decrease the investment cost by avoiding unnecessary investment on heat exchangers. The concepts of restricted matches and water tanks have been added to the superstructure to adapt it to the pulp and paper case studies. The Integer-Cut Constraint (ICC) technique has been combined with the MILP model to generate systematically a set of optimal solutions to support the decision-making for cost-effective configurations.
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