Modeling and Optimization of Industrial Multi-Stage Compressed Air System Using Actual Variable Effectiveness in Hot Regions

In this article, modeling and optimization of power consumption of two–stage compressed air system have been investigated. This system includes two centrifugal compressors and a shell and tube intercooler. For modeling of power consumption, actual compressors, isentropic efficiencies are calculated from experimental data. Also for modeling of outlet temperature of the intercooler and calculation of thermal effectiveness, the neural network algorithm was used. In these equations isentropic the efficiency of compressors is a function of inlet temperature and thermal effectiveness of the intercooler is a function of inlet air temperature, inlet water temperature of the intercooler and inlet volumetric flow rate of the system. For optimization of power consumption, the Lagrangian method is used. Power consumption and isentropic efficiency of the first and second stage compressors, thermal effectiveness of the intercooler and entropy generation of compressors are considered as the objective function and optimization conditions, respectively. In comparison to the experimental data, the modeling provided suitable accuracy. The optimization effectively reduced the power consumption of the system, especially in summer, in a way that the minimum and maximum reduction was 2.9% and 9.6%, respectively.