Open AccessPrediction and analysis of natural gas consumption in chongqing with a grey prediction model group in the context of COVID‐19
Author(s) -
Zeng Bo,
Yang Shuangyi,
Mao Cuiwei,
Zhang Dehai
Publication year - 2022
Publication title -
energy science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 29
ISSN - 2050-0505
DOI - 10.1002/ese3.1164
Subject(s) - natural gas , consumption (sociology) , context (archaeology) , gas consumption , predictive modelling , covid-19 , natural (archaeology) , group (periodic table) , econometrics , statistics , mathematics , geography , engineering , petroleum engineering , medicine , chemistry , social science , disease , archaeology , organic chemistry , pathology , sociology , infectious disease (medical specialty) , waste management
In this paper, a grey prediction model group is employed to quantitatively study the impact of COVID‐19 on natural gas consumption in Chongqing, China. First, a grey prediction model group suitable for the prediction of Chongqing's natural gas consumption is introduced, which consists of GM(1,1), TWGM(1,1), and the newly‐developed ODGM(1,1). Then, the model group is constructed to predict Chongqing's natural gas consumption in 2020. Finally, compare the predicted results of the model group with the actual consumption and quantitatively analyze the impact of the epidemic on natural gas in Chongqing. It is found that the impact of the epidemic on the consumption of natural gas in the first quarter of the year is very small, but relatively bigger in the second and third quarters. The study is of positive significance to maintain the supply and demand balance of natural gas consumption in Chongqing in the background of COVID‐19; and it enriches and develops the theoretical system of grey prediction models.