Forecasting China’s natural gas consumption based on a combination model

Ensuring a sufficient energy supply is essential to a country. Natural gas constitutes a vital part in energy supply and therefore forecasting natural gas consumption reliably and accurately is an essential part of a country＇s energy policy. Over the years, studies have shown that a combinative model gives better projected results compared to a single model. In this study, we used Polynomial Curve and Moving Average Combination Projection （PCMACP） model to estimate the future natural gas consumption in China from 2009 to 2015. The new proposed PCMACP model shows more reliable and accurate results： its Mean Absolute Percentage Error （MAPE） is less than those of any previous models within the investigated range. According to the PCMACP model, the average annual growth rate will increase for the next 7 years and the amount of natural gas consumption will reach 171600 million cubic meters in 2015 in China.

Forecast of natural gas supply and demand in China under the background of “Dual Carbon Targets”

As a kind of clean energy which creates little carbon dioxide, natural gas will play a key role in the process of achieving “Peak Carbon Dioxide Emission” and “Carbon Neutrality”. The Long-range Energy Alternatives Planning System(LEAP) model was improved by using new parameters including comprehensive energy efficiency and terminal effective energy consumption. The Back Propagation(BP) Neural Network–LEAP model was proposed to predict key data such as total primary energy consumption, energy mix, carbon emissions from energy consumption, and natural gas consumption in China. Moreover, natural gas production in China was forecasted by the production composition method. Finally, based on the forecast results of natural gas supply and demand, suggestions were put forward on the development of China’s natural gas industry under the background of “Dual Carbon Targets”. The research results indicate that under the background of carbon peak and carbon neutrality, China’s primary energy consumption will peak(59.4×10^(8)tce) around 2035, carbon emissions from energy consumption will peak(103.4×10^(8)t) by 2025, and natural gas consumption will peak(6100×10^(8)m^(3)) around 2040, of which the largest increase will be contributed by the power sector and industrial sector. China’s peak natural gas production is about(2800–3400)×10^(8)m^(3), including(2100–2300)×10^(8)m^(3)conventional gas(including tight gas),(600–1050)×10^(8)m^(3)shale gas, and(150–220)×10^(8)m^(3)coalbed methane. Under the background of carbon peak and carbon neutrality, the natural gas consumption and production of China will further increase, showing a great potential of the natural gas industry.

Analysis of Driving Factors of Natural Gas Consumption in China: Based on Regional Integration and LMDI Method

In recent years,China has developed rapidly in terms of natural gas.Driven by regional economic integration,a regional natural gas market composed of neighboring provinces and cities has taken shape gradually,and it tends to grow toward the same direction in policy formulation,resource coordination,facility construction and market expansion.Based on the factors such as geographical location,economic conditions and natural gas consumption,this thesis tends to conduct a horizontal comparative analysis on the economic development conditions,natural gas consumption characteristics and natural gas pipeline network density of the three regions with obvious regional integration feature in China.Then according to LMDI,four core indicators,namely economic growth effect,energy intensity effect,energy structure effect,and substitution effect are selected.The thesis is expected to explore the contribution of different indicators to the growth of natural gas consumption in these three different regions.According to the results,it can be concluded that the driving factors of natural gas consumption differ greatly among regions.Specifically speaking,the more developed the economy is,the greater the contribution of the energy substitution effect to natural gas consumption will be,and the contribution of the economic growth effect to natural gas consumption will be smaller.Despite that the contribution of energy intensity in different regions shows slight difference,the energy structure contributes the least effect,which further explains the current differences in China’s natural gas consumption characteristics and the reasons behind.

Analysis of the supply-demand status of China's natural gas to 2020

The reserves, distribution, production and utilization of natural gas resources in China are introduced in this paper which leads a point of view that China＇s natural gas resources are relatively rich while distributed unevenly. The future production and consumption of China＇s natural gas are predicted using the Generalized Weng model and the Gray prediction model. The prediction suggests that with the increasing gas consumption China＇s natural gas production will not meet demand after 2010. In order to ease the supply-demand gap and realize rational development and utilization of China＇s natural gas resources, this paper puts forward some measures, such as using advanced technologies for natural gas development, establishing a long-distance pipeline network to rationalize the availability of natural gas across China and importing foreign natural gas and liquid natural gas （LNG）.

Refined analysis and prediction of natural gas consumption in China

In view of the abrupt and phased features of natural gas consumption,this paper attempts to predict natural gas consumption in China with a refined forecasting approach.First,we establish a Markov switching(MS)model to identify the phase characteristics after eliminating change points in the natural gas consumption sequence,using the product partition model(PPM).The results show that there are"rapid growth"and"slow growth"regimes in the development process of natural gas consumption in China.Second,the Bayesian model average(BMA)method is employed to determine the core determinants of natural gas consumption under sub-regimes,and it is determined that there are significant differences in the influencing factors under different regimes and periods.Third,this paper establishes the BMA model of the"rapid growth"regime after predicting the state of future natural gas consumption in China.We find that,compared to some other models,the BMA model that fully recognizes the regime without considering change points has the best predictive performance.Finally,the results of static and dynamic scenario analyses show that natural gas consumption continues to rise in 2019 and has obvious seasonal charac-teristics,while possible ultra-rapid growth of consumption in the future provides a new requirement for the supply of natural gas.

Quantitative Analysis and Prediction of China's Natural Gas Consumption in Different Sectors Based on Bayesian Network

In view of the heterogeneity of natural gas consumption in different sectors in China,this paper utilizes Bayesian network(BN)to study the driving factors of natural gas consumption in power generation,chemical and industrial fuel sectors.Combined with Bayesian model averaging(BMA)and scenario analysis,the gas consumption of the three sectors is predicted.The results show that the expansion of urbanization will promote the gas consumption of power generation.The optimization of industrial structure and the increase of industrial gas consumption will enhance the gas consumption of chemical sector.The decrease of energy intensity and the increase of gas consumption for power generation will promote the gas consumption of industrial fuel.Moreover,the direct influencing factors of gas price are urbanization,energy structure and energy intensity.The direct influencing factors of environmental governance intensity are gas price,urbanization,industrial structure,energy intensity and energy structure.In 2025,under the high development scenario,China’s gas consumption for power generation,chemical and industrial fuel sectors will be 66.034,36.552 and 109.414 billion cubic meters respectively.From 2021 to 2025,the average annual growth rates of gas consumption of the three sectors will be 4.82%,2.18%and 4.43%respectively.

The Extended Grey GM(2,1,Σexp(ct))Model and Its Application in the Predictions

The conventional grey GM(2,1)model built for the fast growing time sequence generally has big errors.To improve the modeling precision,the paper improves from the following two aspects:First,the paper transforms the accumulated generating sequence of original time sequence quantitatively to make the transformed time sequence have the better adaptability to the model;second,the paper extends the conventional grey GM(2,1)model’s structure to make the extended model meet the variation law of fast growing sequence better.The extended grey model is called the GM(2,1,Σexp(ct))model.The paper offers the parameter optimization method and the solving method of time response sequence of GM(2,1,Σexp(ct))model.Using the model and methods proposed,the paper builds the GM(2,1,Σexp(ct))models for the natural gas consumption of China and Chongqing City,China,respectively.Results show that the models built have high simulation precision and prediction precision.