Dynamic Simulation of Compressed Air Systems

In recent years, energy engineers have examined industrial compressed air systems looking for opportunities to reduce the energy consumption, which in turn leads to operating cost savings. After identifying possible actions that might lead to a reduction in energy usage, it is necessary to perform an analysis to determine the projected energy and cost savings, and to estimate the cost of implementing the action. This analysis is a critical step in calculating the return on investment to determine if the recommended changes are cost effective. A number of sound recommendations are based on best practices and good engineering judgment. Often these methods employ approximate formulas and “rules of thumb”, which produce reasonable results depending on the assumptions made. For compressed air systems that utilize multiple compressors and various control strategies, dynamic system simulation provides a method to investigate opportunities in energy reduction and system optimization. In this paper, a dynamic compressed air system simulation model that was developed utilizing MATLAB/SIMULINK is presented. The model accounts for thermodynamic and fluid dynamic interactions within the compressed air system under a variety of operating conditions and control strategies. The system model is composed of component models that are linked to form the compressed air system. Each component model is based on relations that involve the key system variables. The component models discussed in this paper are two screw air compressors, an auxiliary air cooler, a receiver, the system piping and both regulated and unregulated air demand. The method of compressor control is load/unload. The simulation program was utilized to investigate the effect of air pressure on the performance of the system. It is usual to recommend reducing the delivered pressure from the compressor as a way to reduce the compression work. However, when multiple compressors are used to serve a system with varying air demands, increasing the pressure settings and properly sequencing the compressors could result in a reduction of the system energy usage. Other factors that affect the optimal performance of the system include the volume of the compressed air storage tank (receiver), the temperature of the discharge air (affected by the capacity of the after cooler), and the temperature of the inlet air to the compressor. Because the simulation program bases the calculations on fundamental principles of thermodynamics and fluid dynamics, it accounts for the interaction of various system operating parameters on the systems performance. Two simulation studies are presented. Results from the simulation program are discussed and optimal operating parameters are discussed in light of the simulation results. Introduction One method for analyzing the overall energy efficiency of a compressed air system (CAS) is to examine the system from the supply side and the demand side. For instance, a