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Dynamic simulation scenario analysis of multiobjective optimization configuration of China's natural gas resources.
- Source :
- Energy Science & Engineering; Nov2020, Vol. 8 Issue 11, p3772-3787, 16p
- Publication Year :
- 2020
-
Abstract
- In order to seek the optimal growth of China's economy under the premise of natural gas supply safety and air pollution emission constraints, this paper builds a multiobjective optimal allocation model of China's natural gas. The model takes 2012 as the base period, and the simulation period is from 2013 to 2025. Four types of policy combinations are set as variables to be introduced into the model. Lingo is used to simulate the policy combinations under considerations by the model to select the optimal scenario. The dynamic scenario simulation results are as follows: (a) Comparing the simulated data with actual data from 2013 to 2018, we find that the relative error between the simulated results and the actual results is less than 3%, indicating that the constructed multiobjective optimization configuration model is reliable and effective. (b) By 2025, China's natural gas production will be 333.4 billion cubic meters, and its consumption will be 217.1 billion cubic meters. The output will gradually exceed the demand; the proportion of natural gas consumption in the total energy consumption will increase from 5.4% to 7.8%. The proportion has increased significantly; the total GDP is 139 trillion yuan, with an average annual growth rate of 7.5%, and the contribution of the tertiary industry to GDP accounts for 55.8%; (c) China's SO2 emissions from 19.54 million tons in 2013 will be reduced to 12.64 million tons in 2025, China's NOx emissions plummeted from 21.92 million tons in 2013 to 12.59 million tons, and the emission intensity of atmospheric pollutants dropped from 34.0 tons/100 million yuan in 2013 to 9.1 tons/100 million yuan in 2025. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20500505
- Volume :
- 8
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- Energy Science & Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 147017461
- Full Text :
- https://doi.org/10.1002/ese3.803