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

Document Type: Original Article

Authors

1 Department of Chemical Engineering, Faculty of engineering, Payame-Noor University, Tehran, Iran

2 Faculty of Engineering, Department of chemical engineering, University of Kashan, Iran

Abstract

In this study, we have attempted to model the compression and fast filling processes of the compressed natural gas (CNG) and its simulation in FORTRAN programming software. In this modeling, natural gas has been considered as a real gas and AGA-8 equation of state is used for computing the compressibility factor and other thermodynamic properties. In order to compute the compressor work, the polytropic compression process of a real gas in a three stage compressor is considered. Also, the fast filling process (FFP) is modeled based on mass conservation and thermodynamic first laws in a non-adiabatic cylinder. Using the aforementioned proposed models, the compressor work, the heat lost in the coolers, final temperature and accumulated mass of the gas in the cylinder, fill ratio and refueling process time in different pressure arrangements of the station tanks are computed at 5 ambient temperatures. Finally, in order to determine the optimal operational conditions, the optimization was 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 equal to 273.15 K were reported as the optimal conditions.

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