Empirical study on the outliers of compressed nagural gas (CNG) refueling behaviors

DOI

10.2991/iccahe-16.2016.48How to use a DOI?

Keywords

CNG, Refueling behaviors, CNG filling station, Outlier, Python

Abstract

To improve a secondary CNG filling station's refueling effectiveness and reduce its operation costs, the abnormal CNG refueling behaviors or outliers are empirically studied. Firstly, the central tendency and dispersion of volume and pressure change is empirically studied, and the simple regression model is adopted to test the positive correlation between the two variables. Secondly, the abnormal behaviors are detected by parametric methods and non-parametric methods of statistical approaches based on volume or pressure change. Finally, these outliers are found mainly from the repeated filling behaviors by Python language. Therefore, the way to improve the refueling effectiveness and reduce operation costs is to reduce repeated filling actions.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yang Li
AU  - Dengchao Jin
AU  - Yulian Zhao
AU  - Zhenbo Bao
AU  - Weiyu Zhang
AU  - Yong Wei
AU  - Di Yang
AU  - Jian Shao
PY  - 2016/10
DA  - 2016/10
TI  - Empirical study on the outliers of compressed nagural gas (CNG) refueling behaviors
BT  - Proceedings of the 2016 5th International Conference on Civil, Architectural and Hydraulic Engineering (ICCAHE 2016)
PB  - Atlantis Press
SP  - 276
EP  - 280
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccahe-16.2016.48
DO  - 10.2991/iccahe-16.2016.48
ID  - Li2016/10
ER  -