Demand Of Natural Gas In China Research Articles

Forecast of China’s natural gas demand based on the double-logarithmic model with stepwise regression method

ABSTRACT In the current world’s energy system, natural gas, as a clean energy source, is gradually becoming the main energy source. However, the volume of natural gas demand could be able to be influenced by numerous factors, in order to forecast the future trend of the requirement more precisely, it is necessary to further explore effective driving factors influencing the volume of demand and construct a brand new function model of forecasting natural gas demand. In this study, the relative gray relational degree is used to quantitatively describe the correlation among variables, diagnosing whether there are serious multicollinearity problems among these factors. According to the principle of correlation degree: first and then small, a stepwise regression analysis is adopted to refine the analysis of factors influencing natural gas demand. On the basis of statistical significance testing, in-depth studying is conducted on the effective influencing factors of natural gas demand. This helps to develop a more accurate prediction model. In this study, we find that: (1) China’s energy consumption structure and economic development influence its natural gas demand. (2) The stepwise regression double logarithmic demand function model based on the effective drivers has good forecasting performance. Researchers can use it to forecast the natural gas demand for medium- and long-term in different regions, and the forecasting results can be considered an important reference basis for scientific natural gas policy formulation. (3) Over the coming 15 years, Natural gas demand in China will continue to grow. It will reach about 6910 × 10 8 m 3 by 2035. It is concluded that the development of China’s natural gas demand would be promoted in an increasing scale trend by striving to promote China’s high-quality economic development, carefully building a new pattern of high-quality energy development, and increasing the proportion of natural gas consumption.

Research on the monthly fluctuation of natural gas demand in China

AbstractWith the rapid growth of natural gas consumption in China, the monthly peak shaving and security issues of the gas supply have become increasingly prominent. In view of this situation, the monthly fluctuation law of natural gas consumption in China must be studied to guide gas storage peak shaving and gas supply planning. In this study, the concepts of the gas year (statistical method of breaking through the calendar year to gas year and reflecting the complete gas consumption cycle), typical year (the year that had the representative load curve of China), and some fluctuation characteristics parameters were applied to study the monthly fluctuation law of natural gas consumption in China. Furthermore, according to the monthly statistical data of China, including natural gas demand, power generation, crude steel output, refined copper output, the monthly average temperature in the typical city, the relationship between influencing factors and natural gas demand was analyzed by the gray relative correlation method. Based on the stepwise regression Cobb–Douglas (C–D) production function, the natural gas demand of China in the gas year of 2030/31 was predicted. The research results can be used for energy planning, statistics, peak shaving of gas storage, liquefied natural gas trade, and can also be used as a reference for energy big data analysis and refined management.

Probability density forecasts for natural gas demand in China: Do mixed-frequency dynamic factors matter?

Due to the expensive infrastructures and the difficulties in storage, the supply and demand for natural gas in China has experienced periodic fluctuations and geographical imbalance. The primary purpose of this study is to provide satisfying probability density forecasts using mixed-frequency dynamic factors to alleviate the imbalance risks between the supply and the demand. To this end, this paper develops a novel hybrid model named EEMD-MIDAS-SVR, based on ensemble empirical mode decomposition (EEMD) procedure, mixed data sampling (MIDAS) framework and support vector machine regression (SVR). The empirical results reveal that the mixed-frequency dynamic factors could provide powerful predictive information for natural gas demand. By the model confidence set (MCS) test, we identify the most predictive dynamic factors: gas industry index, electricity industry index, Daqing crude oil prices, Qinhuangdao steam coal prices, West Texas Intermediate crude oil prices, and Australia steam coal prices. They could improve forecasting accuracy by about 70% than benchmark models, particularly considering the nonlinearity of natural gas demand contributes to 21% roughly. Based on the MCS test, we provide the non-parametric bootstrap probability density forecasts for natural gas demand, which performs well in capturing the uncertainty of natural gas demand. These findings have several policy implications and practical value for natural gas pricing and carbon neutrality achieving in emerging markets.

Urban natural gas demand and factors analysis in China: Perspectives of price and income elasticities

Urban natural gas is becoming the main sector driving China's natural gas consumption growth in recent years. This study explores the impacts of urban natural gas price, wage, socioeconomic determinants, and meteorological conditions on urban natural gas demand in China over 2006–2017. Furthermore, this study also analyzes the potential regional heterogeneity and asymmetry in the impacts of gas price and income on China's urban gas demand. Empirical results reveal that: (1) The increased gas price can significantly reduce the urban gas demand, and the average income level may effectively promote the gas demand, also, a strong switching effect exists between electricity and natural gas in urban China; (2) these impacts are heterogeneous in regions among China, urban natural gas demand is largely affected by the gas price in regions with high-gas-price and by income in regions with low-gas-price; and (3) the impact of gas price on urban gas consumption is consistent in regions with different urban natural gas consumption, while the impact of income is asymmetric. This study further provides several policy implications for improving the urban natural gas industry in China.

Evaluating natural gas supply security in China: An exhaustible resource market equilibrium model

The continuous growth of natural gas demand in China has brought about supply security from the insufficient supply of domestic resources and ever-increasing dependency on natural gas imports. A multi-agent game framework for supply security is proposed to investigate availability, accessibility, and affordability along natural gas industry and supply chain. In this framework, an exhaustible resource market equilibrium model based on mixed complementary programming (MCP) is developed, taking into account the dynamic depletion of the remaining recoverable reserves, to evaluate the gas supply security in China. The results indicate the supply security of China's natural gas is far from optimistic from 2020 to 2049, and the newly-increased recoverable reserves of 200 bcm/a are required to meet the expanding scale of the natural gas market. However, it will face supply risks with lower Reserve-Production ratios after 2030 and higher dependencies after 2040. Therefore, the equilibrium model is used to simulate for seeking feasible solutions to ensure the natural gas supply security from three aspects: market structure, discount rate, and resources tax. Several combinational strategies suitable for China's natural gas supply security are suggested according to the market structure, natural gas import, discount rate, and resources tax for building a more diversification system of natural gas supply, establishing an efficient allocation system of the natural gas market and setting up an effective strategic stockpile system of natural gas resources.

Government-led urbanization and natural gas demand in China

The Chinese government is actively promoting urbanization to stimulate its economic growth while facing increasingly prominent environmental concerns. The main objective of this research is to assess whether the Chinese government is making efforts to promote cleaner energy demand while pushing for urbanization. This study employs system GMM models to empirically investigate the causal relationship between urbanization and natural gas demand by using a sample of 30 provinces in China over the period 2005–2018. The estimates of the preferred specifications show that government-led urbanization has a positive impact on natural gas demand conditional on total energy use. By attaching natural gas facilities to new structures through the use of administrative power, the government induces natural gas demand while promoting urbanization. Robustness checks indicate that adding more potentially influential factors will not qualitatively change the results from the baseline. A constrained two-step static panel data estimation is used to estimate the depreciation rates of natural gas and of all fuel appliances, suggesting that the promotion of natural gas demand provides a relatively economical way to balance the trade-off between economic growth and environmental protection. The empirical results also show that the dynamic model outperforms its static counterpart in predictions. Based on the results, policy recommendations are made towards the goals of the Fourteenth Five-Year Plan for the National Economic and Social Development of China.

Assessing the resilience of China’s natural gas importation under network disruptions

Natural gas (NG) supply disruptions are growing with an ever-increasing NG demand in China. To better understand China’s NG security, this paper proposed a new framework to assess the resilience of NG importation under disruptive events. We focus on the resilience of NG importation network (NGIN). By constructing the NGIN during 2011–2017, which all reveal to be scale-free networks, we analysed some network properties of NGIN for resilience assessment. To assess resilience, a new set of metrics considering both network structure and NG import flow are proposed. Then the resilience of NGIN is assessed under both random failures and malicious attacks. In random failures, NGIN reveals to be vulnerable seen from all three metrics. In malicious attacks, the network is even more fragile to node failures. Besides, the resilience of NGIN has hardly improved along the study period. Furthermore, we proposed three modification strategies to improve the resilience of NGIN. The Results of this research indicate that: firstly, with low resilience of NGIN to import disruptions, China should increase the NG storage for sudden demand shortages; secondly, China should import more NG from countries that are closer to China or with importing routes not subject to malicious attacks.

How did the price and income elasticities of natural gas demand in China evolve from 1999 to 2015? The role of natural gas price reform

As a cleaner, high-efficiency, and low-carbon fuel, natural gas has been an important fuel resource for China. To achieve a substantial increase in natural gas demand, China has sought to reform its natural gas pricing mechanism. Employing a set of unbalanced panel data for China’s 30 provinces covering 1999–2015, this study aims to estimate the evolving price and income elasticities of natural gas demand and explore the effect of natural gas price reform in China. For this purpose, a series of econometric techniques allowing for cross-sectional dependence and slope homogeneity is utilized. The results suggest that although natural gas demand in China still lacks negative price elasticity, the phenomenon is improving. Moreover, the estimates suggest that natural gas demand in China is indeed becoming increasingly sensitive to income changes. Our estimates also provide strong evidence in favor of the effect of natural gas price reform on the change in price elasticity as the price elasticity decreases in five of the seven regions. In addition, the results indicate large variations in the change in price and income elasticities of natural gas demand across China’s regions. Natural gas demand is becoming more price inelastic in Southwest China and Northwest China, while such demand in North China and East China responds less sensitively to income changes. These findings offer several policy suggestions for the reform of China’s natural gas market at the national and regional levels.

Price elasticity, block tariffs, and equity of natural gas demand in China: Investigation based on household-level survey data

Abstract: On the basis of a newly established database from the Chinese Residential Energy Consumption Survey, this paper estimates the price elasticity of natural gas demand for the households and investigates the factors that affect residential natural gas consumption in China. To address the endogeneity problems, the non-residential natural gas price has been adopted as the instrumental variable for residential natural gas price. Results demonstrate that the natural gas demand of Chinese households respond significantly to price change, with an overall price elasticity coefficient of −0.898. In the meanwhile, 1% increase in family members would cause 0.159% rise in natural gas demand, and household in the south consumes 28.8% more natural gas than that in the north. Recognizing the heterogeneity of residential natural gas price elasticity for different households, quantile regression technique has further been applied to analyze the distributional effect of natural gas consumption. The simulation suggests that the Gini coefficient drops from 0.49 to 0.40 after introducing an increasing block tariff scheme to replace the original flat tariff system, confirming a price reform has potential to improve the energy equity situation by reshaping the energy consumption pattern.

Forecasting the natural gas demand in China using a self-adapting intelligent grey model

Reasonably forecasting demands of natural gas in China is of significance as it could aid Chinese government in formulating energy policies and adjusting industrial structures. To this end, a self-adapting intelligent grey prediction model is proposed in this paper. Compared with conventional grey models which have the inherent drawbacks of fixed structure and poor adaptability, the proposed new model can automatically optimize model parameters according to the real data characteristics of modeling sequence. In this study, the proposed new model, discrete grey model, even difference grey model and classical grey model were employed, respectively, to simulate China's natural gas demands during 2002–2010 and forecast demands during 2011–2014. The results show the new model has the best simulative and predictive precision. Finally, the new model is used to forecast China's natural gas demand during 2015–2020. The forecast shows the demand will grow rapidly over the next six years. Therefore, in order to maintain the balance between the supplies and the demands for the natural gas in the future, Chinese government needs to take some measures, such as importing huge amounts of natural gas from abroad, increasing the domestic yield, using more alternative energy, and reducing the industrial reliance on natural gas.

Forecasting natural gas demand in China: Logistic modelling analysis

Abstract Natural gas has increasingly appeared as an important policy choice for China’s government to modify high carbon energy consumption structure and deal with environmental problems. This study is aimed to develop the logistic and logistic-population model based approach to forecast the medium- (2020) to long- (2035) term natural gas demand in China. The adopted modelling approach is relatively simple, compared with other forecasting approaches. In order to further improve the forecasting precision, the Levenberg–Marquardt Algorithm (LMA) has been implemented to estimate the parameters of the logistic model. The forecasting results show that China’s natural gas demand will reach 330–370 billion m3 in the medium-term and 500–590 billion m3 in the long-term. Moreover, the forecasting results of this study were found close in studies conducted by the national and international institutions and scholars. The growing natural gas demand will cause significant increase in import requirements and will increase China’s natural gas import dependency. The outcomes of this study are expected to assist the energy planners and policy makers to chalk out relevant natural gas supply and demand side management policies.