Published December 1, 2017 | Version v1
Journal article

Forecasting China's natural gas demand based on optimised nonlinear grey models

  • 1. Department of Electrical Engineering, Mehran University of Engineering & Technology (MUET), Jamshoro, Sindh (Pakistan)
  • 2. Mehran University Centre for Energy & Development (MUCED), Mehran University of Engineering & Technology (MUET), Jamshoro, Sindh (Pakistan)
  • 3. Center for Energy and Environmental Policy Research, Institutes of Science and Development, Chinese Academy of Sciences, Beijing, 100190 (China)
  • 4. School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049 (China)

Description

Natural gas increasingly has become an important policy choice for China to modify its high carbon energy consumption structure. Natural gas is a low carbon energy option for China's government to fulfil its volunteer commitments with the international community to mitigate greenhouse gas emissions. This study has constructed China's natural gas consumption forecasting model by utilising two optimised nonlinear grey models: the Grey Verhulst Model and the Nonlinear Grey Bernoulli Model. Both of these models have precisely adapted China's actual natural gas consumption and forecasted that the country's natural gas demand will reach 315 billion m3 by 2020. In addition, the existing and projected natural gas supplies and the capacities of imports, such as liquefied natural gas and pipeline natural gas, have been evaluated to gain a better understanding of the supply-demand and import trends. Accordingly, it has been observed that China's existing and planned natural gas supplies and LNG and PNG infrastructure will be sufficient to cope with the growing energy demand for the period 2014–2020. However, this situation will cause a significant increase in its import dependency. - Highlights: • Modelled the non-linear pattern (2002–2013) for China's natural gas consumption. • Demand will grow at a rate of 11% per year and jump to 315 BCM by 2020. • Import dependency will increase from exiting 32% to above 50% by 2020. • Import infrastructure will be sufficient to import required quantity by 2020.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.energy.2017.09.037

Additional details

Identifiers

DOI
10.1016/j.energy.2017.09.037;
PII
S0360-5442(17)31559-1;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
140
Journal Issue
Part 1
Journal Page Range
p. 941-951
ISSN
0360-5442
CODEN
ENEYDS

Optional Information

Copyright
Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.