A comprehensive review of renewable energy source on energy optimization of black liquor in MSE using steady and dynamic state modeling, simulation and control

Increasing energy demand, high energy cost and global warming issues require energy-intensive industries to make sincere efforts to improve energy efficiency. The energy consumption data available for different industries suggests that pulp and paper industry accounts for a significant share. Amongst various procedures to make paper, Kraft recovery process is majorly employed that yields weak but lignin-rich black liquor as a byproduct. Black liquor is one of the emerging biomass energy resources with a strong potential to be used as a biofuel for generating steam/energy to operate the process units, thereby, ensuring process self-sufficiency and sustainability. A Multi-Stage Evaporator (MSE) is needed to concentrate it but suffers from being the most energy consuming unit among all. This piques our interest to explore various energy reducing schemes or configurations used previously for MSE and to report previous research endeavors in the area of steady-state, dynamic modeling and simulation of such processes. It is noted that steady-state and transient behavior analysis together with an efficient controller design may significantly contribute in eliminating or troubleshooting problems to ensure both energy savings and product quality. The article highlights that such an analysis and effective solutions of developed models, due to their non-linear complex nature, are highly dependent on the nature of the algorithm employed. Attempts to design control techniques to enable efficient process control and to eliminate process uncertainties have suffered limitations not only due to inherent inefficiency of control techniques but also due to insufficient underlying knowledge or inappropriate modeling of system transience. With this perspective in mind, advanced and intelligent control techniques and their influence on process/energy transience and optimization have been reviewed. Here, we propose that it is very essential to maintain sufficient prudence in selecting an appropriate simulation, optimization and control algorithm to ensure a sustainable production.