| Issue |
E3S Web Conf.
Volume 248, 2021
2021 3rd International Conference on Civil Architecture and Energy Science (CAES 2021)
|
|
|---|---|---|
| Article Number | 02034 | |
| Number of page(s) | 6 | |
| Section | Energy Technology Application and Energy Saving and Emission Reduction Research and Development | |
| DOI | https://doi.org/10.1051/e3sconf/202124802034 | |
| Published online | 12 April 2021 | |
Modelling Natural Gas Energy Production of United States
School of Science, Southwest University of Science and Technology, Mianyang 621000, China.
* Corresponding author: caiyubin4@163.com
In the transformation of the energy system, natural gas energy is regarded as a buffer energy. How to make a reasonable energy distribution and effectively predict its production is very significant. In the work of this paper, a grid-optimized fractional-order non-homogeneous grey model is used to predict the natural gas energy production in the United States and obtain reliable results. This paper first introduces the prediction method and prediction mechanism. Then the model is optimized to make the prediction effect more prominent. The natural gas energy prediction results show that this method has high prediction accuracy compared with other methods, which means that the method proposed in this paper can be used as an effective tool for short-term forecasting of natural gas production in the United States and play an auxiliary role in energy forecasting.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.