Optimization of Energy Efficiency of Multiple-Stage Evaporator Using ABC Algorithm

The current work focuses on the development of nonlinear energy models for a multiple-stage evaporator (MSE) system and its integration with three different energy reduction schemes (ERSs). The associated ERSs include steam split, feed split, and feed preheater operations that ensure energy efficiency enhancement. The considered MSE is placed at a pulp and paper mill and used to concentrate the weak black liquor. The energy efficiency of MSE is computed by two parameters, steam consumption and steam economy, obtained from the optimal selection of the unknown process parameters (fresh steam supplied, temperature, and liquor flow rate). The computation of these optimum process parameters is obtained by simulating a population-based meta-heuristic optimization technique called artificial bee colony (ABC) algorithm in MATLAB environment. The obtained results show an enhancement in the steam economy of 65.57% in the case of ERSs incorporated model (hybrid model) than that of the base case model. These models are validated against the data of real plat operated model.