Process Parameters Optimization for Energy Saving in Paper Machine Dryer Section

Abstract

Due to high energy consumption in the Chinese paper industry, this study considers higher-energy efficiency for the multicylinder dryer section of paper machines. A common situation in the Chinese paper industry is that energy is consumed in extensive mode. In order to improve the energy efficiency of the paper machine dryer section, deeper analysis and optimization of process parameters are necessary. A NLP optimization method is developed for integration of steam system and air system to reduce the steam consumption and decrease the loads of centrifugal blowers in the multicylinder dryer section of a paper machine. Equality constraints of the optimization model are extracted from different process modules based on material and energy balance. Inequality constraints are from the production capacity, operating condition, etc. Two illustrative examples are presented in this paper. The results show that the optimization model is adaptive and convenient for application. For a newsprint machine, less dry air and steam are used and the energy consumption can be reduced by about 8% in the dryer section. Applied on a linerboard machine which has surface sizing, the method can reduce the energy consumption by 5.6%.