Determining the Optimal Performance of Compressed Natural Gas (CNG) Station Based on PSO Algorithm

In this study, an attempt is made to model the compression and fast filling processes of the compressed natural gas (CNG) and their simulation in FORTRAN programming software. In this modeling, natural gas is considered as a real gas and AGA-8 equation of state used for computing the compressibility factor and other thermodynamic properties. In order to compute compressor work, the polytropic compression process of a real gas in a three stage compressor is considered. Also, fast filling process (FFP) is modeled based on mass conservation and thermodynamics first law in a non-adiabatic cylinder. Using the aforementioned proposed model, the compressor work, lost heat in the coolers, final temperature and accumulated mass of the gas in NGV tank, fill ratio and refueling process time are computed for different pressure arrangement of the station storage tanks at five ambient temperatures. Finally, to determine the optimal operational conditions, an optimization method is performed based on the Particle Swarm Optimization (PSO) algorithm. The pressure arrangement of 4-8.1-16-20.5 MPa for the station tanks and ambient temperature 273.15 K a reported as the optimal conditions.