Minimization of energy consumption in multiple stage evaporator using Genetic Algorithm

Abstract

Maximization of the steam efficiency of a multiple stage evaporator employed for concentrating black liquor in pulp and paper mills carries immense significance and relevance in today's scenario. Nonlinear mathematical models of heptads’ effects backward feed flow with various energy saving schemes namely, steam-split, feed‐split, feed-preheating and their hybrid operations have been developed. The steam economy as a cost function translates the problem into a nonlinear optimal search problem. The mass and heat balance equations act as nonlinear equality constraints while vapor temperatures and liquor flows appear as inequality constraints. The formulated problem has been solved efficiently to attain optimal solution using Genetic Algorithm approach which demonstrates advantages of convergence and relative less sensitivity towards initial values versus conventional algorithms. The simulations indicate that a hybrid of steam-split, feed-split and feed-preheating process arrangements with backward feed flow could provide the highest heat transfer across evaporator effects with an optimum steam economy of 6.47 and consumption of 6541.93 kg/h. © 2017 Elsevier Inc.