Energy Consumption Structure In China Research Articles

An innovative MGM–BPNN–ARIMA model for China’s energy consumption structure forecasting from the perspective of compositional data

Effective forecasting of energy consumption structure is vital for China to reach its “dual carbon” objective. However, little attention has been paid to existing studies on the holistic nature and internal properties of energy consumption structure. Therefore, this paper incorporates the theory of compositional data into the study of energy consumption structure, which not only takes into account the specificity of the internal features of the structure, but also digs deeper into the relative information. Meanwhile, based on the minimization theory of squares of the Aitchison distance in the compositional data, a combined model based on the three single models, namely the metabolism grey model (MGM), back-propagation neural network (BPNN) model, and autoregressive integrated moving average (ARIMA) model, is structured in this paper. The forecast results of the energy consumption structure in 2023–2040 indicate that the future energy consumption structure of China will evolve towards a more diversified pattern, but the proportion of natural gas and non-fossil energy has yet to meet the policy goals set by the government. This paper not only suggests that compositional data from joint prediction models have a high applicability value in the energy sector, but also has some theoretical significance for adapting and improving the energy consumption structure in China.

Optimization path of China’s energy industry structure under low carbon economy situation

The study discusses the main aspects of optimizing the structure of China’s energy industry in a situation with a low-carbon economy. To build a model for forecasting electricity demand, the method of partial least squares regression is used. The basic scenario and the scenario with restrictions are set taking into account the peculiarities of the development of a new normal economy. Based on the baseline scenario and the restricted scenario, the total energy demand, energy consumption structure and CO2 emissions in China are projected. Taking into account energy, economic and environmental factors, a multi-purpose optimization model of the energy consumption structure was built and the structure of China’s energy consumption and the corresponding CO2 emissions under optimization scenarios were obtained. This research describes revise the energy consumption structure in China, should reducing energy consumption and carbon dioxide emissions is very helpful.

Interactions Among Energy Consumption per GDP, Technological Innovation Input and Energy Consumption Structure in China During the 14th Five-Year Plan Period

In the context of China's 14th Five-Year Plan, this paper examines the complex interactions between energy utilization efficiency, technological advancement, and energy-consuming structure. The Vector Autoregressive (VAR) model, impulse response functions, and variance decomposition are used to thoroughly analyze time series data extending from 1999 to 2022 to reveal the dynamic relationships and effect mechanisms among these variables. The results show that the multidimensional adjustment of energy use has been driven in large part by technological innovation. In the short term, the improvement in energy utilization efficiency is predominantly propelled by its inherent inertia, while technological innovation gradually becomes the primary driving force. The positive impact of technological innovation input enhances energy utilization efficiency, while improved energy utilization efficiency stimulates later-stage technological innovation investment. Furthermore, a shift towards reduced GDP energy intensity is essential, focusing on controlling fossil fuel usage while advancing non-fossil energy sources. It underscores the significance of optimizing traditional fossil fuel utilization and gradually transitioning to clean energy sources for sustained and efficient energy-consuming patterns.

The impact of carbon finance on energy consumption structure: evidence from China.

As a financial innovation model to promote sustainable economic development, carbon finance promotes green and inclusive economic development by reshaping the financial system. As a big energy consumer, China has been committed to the green transformation of energy structure, and carbon finance has been regarded as an important tool to support carbon emission reduction. This paper divides carbon finance from three levels, financial macro, environmental governance, and technological development, and selects 17 indexes to measure the development level of carbon finance in China. Time series regression model and the entropy weight method (EWM) are used to analyze the impact of carbon finance on China's energy consumption structure. The empirical results show that carbon finance plays a positive role in promoting China's energy consumption structure, and developing carbon finance is conducive to the use of clean energy and the optimization of energy consumption structure in China; carbon finance can further optimize China's energy consumption structure by investing capital, resources, and technology in industries related to promoting clean energy consumption. Therefore, China should continue to develop carbon finance and promote the establishment of a unified national carbon trading market; at the same time, China should use the CCER trading mechanism to promote the development of renewable energy and enhance the endogenous driving force of energy transformation by promoting technological progress.

Quantitative decomposition of China's industrial energy consumption structure based on production-theoretical decomposition method

The environment constraints have become more restrictive over time, because the transformation of energy consumption structure (ECS) is the key path to achieve the commitment of net-zero emission. However, the adjustment of ECS involves the influence of many factors, including economic factors, energy factors and social factors. Not to mention how ECS-driving factors under tougher environmental regulation may behave throughout long time period remains explored. According to the background, the periodic driving factors of industrial ECS in China based on the periodic effect of environmental regulation on ECS are discussed. In this paper, industries of China are divided into four sectors from 1998 to 2017, and a multi-layer LMDI decomposition model is constructed to decompose ECS of the four sectors in stages. Since the industrial and commercial sector provides the largest contribution rate, the LMDI model based on PDA production theory method is applied to decompose industrial and commercial ECS, aiming to deeply explore the main driving factors of ECS in subindustries, and formulate scientific energy and environmental policies. The results show that from the perspective of the whole industry, the per capita pollution control investment has the most significant negative contribution, and the economic activity effect provides a great positive contribution to the ECS. In terms of subindustries, the main negative drivers are potential energy intensity and GDP technology change.

Geological and Geochemical Characteristics of the Geothermal Resources in Rucheng, China

Abstract The development of geothermal energy promotes the changing of energy consumption structure in China. A series of experiments were performed to evaluate the geothermal resources of Rucheng County, which is the largest geothermal field in Central South China. The experiments include geothermal exploration, apparent resistivity, and determining the geochemical characteristics of the geothermal water. The experimental results show that the F3 fault zone and F1 hanging wall secondary fault are the main thermal control, heat conduction, water diversion, and thermal storage structures. The pH, EC, and Eh of the river water, shallow groundwater, and geothermal water exhibit seasonal changes. The pH and EC of the geothermal water are higher than those of the river water and shallow groundwater, while the Eh is lower. In addition, the corrosivity coefficient Kk and the Ryznar index are used to evaluate the corrosivity and calcium carbonate scaling of the geothermal water, and it is found that the geothermal water has no corrosiveness or calcium carbonate scaling, which indicates that the geothermal energy in Rucheng County has wide application prospects.

Impacts of coal prices on the performance of Chinese financial institutions: Does electricity consumption matter?

This paper investigates the impacts of coal prices on Chinese financial institutions' performance through the CAMEL indicators. We also analyze the potential impact mechanism of coal price shocks. Considering the energy consumption structure in China, we further discuss the impacts of electricity price control on coal price shocks. Results show that the coal price shocks have adverse impacts on Chinese financial institutions. And different industries play different roles in the transmission process of coal price shocks. Coal price shocks are partly mitigated by electricity price control, but these interventions in the market are inefficient.

Evaluation of consumption preference in China under environmental regulation policies: Scenario analysis based on a DECGE model

Consumption preference can affect the regional industrial structure and then the energy market. Taking China as an example, this paper constructs a dynamic energy computable general equilibrium (DECGE) model with knowledge capital to explain the effect of consumption preference on energy environment under the environmental regulation. We set three different consumption preference scenarios to conduct policy simulation. The results show that there are great differences in CO2 emission trends and energy consumption structure between different scenarios. China's current consumption preference cannot guarantee achievement of 2030 energy target. Environmental regulation policy would be helpful to the control of emissions. However, the policy effectiveness of environmental regulation will be affected by consumption preference. Moreover, consumption preference is the decisive factor affecting the industrial structure. And the adjustment of industrial structure will lead to the change of industrial energy consumption structure in China. Under the dual influence of environmental regulation and consumption scale effects, the knowledge capital and energy efficiency of energy intensive industry will be further improved. Our results reveal that the consumption preference and energy environment have synergistic effect. Although optimizing consumption structure cannot guarantee the realization of all energy targets, it will reduce the difficulty for the region to achieve these goals.

Forecasting Chinese CO2 emission using a non-linear multi-agent intertemporal optimization model and scenario analysis

The whole community have paid a lot of attention to whether China can achieve its emission target. The paper adds to the existing literature on emission forecast by considering consumption preference, knowledge capital and technological innovation mechanism with in a non-linear multi-agent intertemporal optimization model (NL-MIOM) which can further improve the accuracy of CO2 emission prediction. The historical fitting test shows that the MAPE value of NL-MIOM model is 1.81%, which is lower than the GM, NGM, ARIMA, OGM, SVR and BR-AGM models. By using this model, we forecast the CO2 emissions and energy consumption structure in China under different scenarios from 2018 to 2035. We find that China’s CO2 emissions will peak around 2032, 2029 or 2027 with 12.34, 11.59 or 11.17 billion tons CO2 emissions under the benchmark scenario, Preference A (American consumption preference) scenario and Preference B (Japanese consumption preference) scenario. Based on the methodology of LMDI decomposition, we identify the main factors affecting China’s CO2 emissions. The results show that the technical progress is the main reason for the reduction of CO2 emissions in the historical stage, pre-peak stage and post-peak stage. Moreover, we also forecast the energy use of 14 different industries in China under different scenarios.

Direct and indirect contributions of energy consumption structure to carbon emission intensity

Purpose Reductions in emissions intensity have been expressed in commitments of many countries’ intended nationally determined contribution. Energy structure adjustment is one of the main approaches to reduce carbon emissions. This paper aims to study the causal relationship between carbon emission intensity and energy consumption structure in China based on path analysis. Design/methodology/approach After data collection, this paper performs correlation analysis, regression and path analysis. Findings Correlation results display clear collinearity among energy structure variables. Regression finds that coal, oil, natural gas and technology can be used as indicators for carbon intensity while primary electricity has been excluded. Path analysis shows that coal had the largest direct and positive impact on emission intensity. Natural gas had a positive direct and negative indirect effect through its negative relationship with coal on emission intensity. Technology has the largest negative elasticity while all fossil energies are positive. Results indicate a negative effect of energy structure adjustment on China’s national carbon intensity. Originality/value Given the major role of China in global climate change mitigation, significant future reductions in China’s CO2 emissions will require transformation toward low-carbon energy systems. Considering the important role in mitigating global climate change, China needs to transition toward a low-carbon energy system to significantly reduce its carbon intensity in the future.

Research on the Status Quo and Existing Problems of Rural Energy Development in China

Over more than forty years of deepening reform and opening up, China has become the second largest world economy after the United States. As a component of energy system in China, rural energy is becoming more and more important. With the development of rural economy in China, the efforts of energy conservation and emission reduction have been continuously strengthened and expanded in China. Sustained, safe, and green energy supply is the material basis for the sustainable development of rural economy in China, and it is also a prerequisite for improving the quality of life of rural residents in China. Given living habits and income levels, energy consumption in rural areas in China is still dominated by traditional energy sources such as coal and firewood. There is little use and consumption of new energy. Rural energy is gradually declining for the investment in special funds for rural energy projects is not enough. New energy technology research and development are lagging. At the same time, rural areas have low using efficiency but high demand of energy, which leads more contradictions. In order to meet the needs of farmers for energy production and increase their income, it is necessary to study the countermeasures of rural energy development, which becomes an important part of the construction of a new socialist countryside. Based on the analysis of rural energy developing status and rural energy consumption structure in China, this article pointed out the problems including unreasonable energy structure, insufficient supply, the contradiction between supply and demand, and the lagging construction of follow-up service management system, and uncompleted energy support policies and imperfect incentive measures. We also put forward corresponding countermeasures and suggestions.

The drivers of China’s national and regional energy consumption structure under environmental regulation

Optimizing energy consumption structure (ECS) is the key to reduce pollution emissions and develop a green economy. Understanding the effect of each influencing factor on ECS is conducive to providing theoretical reference for the formulation of energy and environmental policies, howbeit it lacks studies about the main drivers of national and regional ECS in China. With the consideration of increasingly standardized formal environmental regulation (FER), an extended LMDI model is constructed to decompose the national and regional ECS from 1998 to 2017 into ten influencing factors. The ultimate goals of this concept are to explore the dominant factors of national and regional ECS at different time stages by employing temporal decomposition model, and to investigate the primary drivers that cause the disparity between provincial ECS and national average ECS by applying spatial decomposition model. The results reveal that the effect of FER, the reciprocal of industrial pollution control investment per unit GDP and economic development are the main factors leading to the change of national and regional ECS, specifically FER has a stronger effect on resource-based regions. Also, R&D intensity and R&D efficiency are important factors for ECS change. Energy efficiency and Per capita energy production are the leading factors of ECS disparity between 30 provinces and the national average. What’s more, FER and R&D factors play important roles. Policy suggestions are put forward according to the results.

Substitution Effect of Natural Gas and the Energy Consumption Structure Transition in China

A crucial problem which China faces is how to improve its energy consumption structure. In this paper, a system dynamic model of energy substitution based on energy capital and putty-clay theory is adopted, in order to explore the substitution effect of natural gas on the energy consumption structure transition in China. The results demonstrate that the huge capital stocks of coal and oil capacities effectively delay the progress of natural gas substitution for optimizing the energy structure, resulting in a limited effect of natural gas substitution in the short term and a large cumulative effect in the long term. Further scenario analyses indicate that natural gas subsidies and carbon price policies have positive effects on the growth of natural gas consumption and the optimization of the energy structure. We also found that a higher pressure of safety supply may emerge to meet the demand for energy consumption in the energy transition. Recommendations are given for improving the energy consumption structure in China from three aspects: allocating capital investment to natural gas, reducing the transition cost between natural gas and other energy sources, and awareness of the systemic risks in energy consumption.

Dynamic relationship between environmental regulation and energy consumption structure in China under spatiotemporal heterogeneity

The optimization of energy consumption structure (ECS) is indispensable in developing green economy and mitigating environmental pollution, but the regional heterogeneity of environmental regulation (ER) and socio-economic drivers leads to more complicated formulation of energy and environment policy. In this paper, the dynamic relationship between ER and ECS and the driving mechanism of ECS in the context of spatiotemporal heterogeneity are analyzed using China's province-level data over 1998–2017. Firstly, the spatial autocorrelation of ECS is tested to observe the spatiotemporal characteristics. Secondly, the dynamic relationship between formal environmental regulation (FER) and ECS is analyzed by system generalized moment method at national and regional level. Finally, the nonlinear relationship between FER and ECS is estimated by applying panel threshold model, and the effects of FER on ECS in different intervals are studied. The results illustrate that the autocorrelation of ECS is gradually weakened, and ECS has obvious regional features. What's more, the lagged ECS hinders the optimization of ECS, that is, ECS has a strong path dependence. The lagged FER promotes ECS. Furthermore, two thresholds exist in the sample period to divide FER into three mechanisms. Weak and medium FER promotes ECS optimization, while strong FER inhibits the optimization. According to empirical results, energy policies are put forward.

Improvement pathway of energy consumption structure in China's industrial sector: From the perspective of directed technical change

The improvement in energy consumption structure is of great significance to the green transformation of economic development. In this paper, to explore the reasonable improvement pathway of energy consumption structure in China's industrial sector, we treat fossil energy and non-fossil energy as two different factors into the production function, and conduct a stochastic frontier analysis to estimate the factor-biased degree of production technical change and the substitution elasticities between factors. The results show that the production technology of China's industrial sector is more biased to fossil energy and labor and deviated from non-fossil energy and capital. There is a substitution relationship between capital and labor, as well as labor and fossil energy, and the relationship between capital and fossil energy is complementary. We find that the energy consumption structure in most industrial sub-sectors has a large room for improvement. We propose that the Chinese government should promote the market-oriented reform of energy pricing mechanism to improve the energy consumption structure based on the differentiated characteristics of the energy consumption structures of different industrial sub-sectors.

The Significance of Chinese Culture Going-out

Under the background of energy consumption structure in China, this paper compares the prices of natural gas, coal, liquefied petroleum gas, electricity, diesel oil and natural gas, coal, electricity and coal used by industry and residents by using calorific value ratio method, respectively. Based on the comparison of the price changes of household electricity and other goods, the guiding mechanism of electricity price in electricity market, cross-subsidy, tax, and consumer and so on is further discussed on the basis of revealing the relationship between energy price and price.

Natural gas price effects in China based on the CGE model

Natural gas is a clean energy source with many benefits and its proportion in the energy consumption structure in China has been gradually increasing over the recent years. Since the price of natural gas in China has been controlled and maintained at a relatively low level by the government, reforming the natural gas industry in China has been the matter of much attention in light of its macroeconomic effects on the overall economy. Using the Computable General Equilibrium model and the 2012 Social Accounting Matrix, the results show increases in natural gas prices lead to an increase in the consumer price index (CPI) and lead to reductions in GDP. The chemical industry sector is strongly influenced by a natural gas price increase. Furthermore, chemical fertilizer manufacturing industry and chemical products’ manufacturing have very significant effects in China. Therefore the government may gradually establish and improve the management of natural gas price to avoid negative effects, and implement a differential price as the industries exhibit different levels of resistance in response to natural gas price changes.

China’s regional energy and carbon dioxide emissions efficiency evaluation with the presence of recovery energy: an interval slacks-based measure approach

Recovery energy has been one of important components of energy consumption structure in China. Recovery energy is a type of secondary energy, which is generated from various sources. Since the estimation of recovery energy from some sources such as coke oven gas and other coal gas contains some uncertainties, recovery energy can be represented as an interval variable. The extant studies in the literature ignore recovery energy in the evaluation of energy efficiency or carbon dioxide ( $$\text {CO}_{2}$$ ) emissions efficiency. As a part of energy supply in China, recovery energy may influence regional primary energy consumption and $$\text {CO}_{2}$$ emissions significantly. In this context, this paper proposes an interval slacks-based measure approach to evaluate energy efficiency and $$\text {CO}_{2}$$ emissions efficiency in the presence of recovery energy in China. In the described approach, the indicator of $$\text {CO}_{2}$$ emissions is incorporated based on the weak disposability assumption, and recovery energy is modeled as a dual factor. The optimal exact data on recovery energy of each region can be obtained. Based on the proposed approach, the measures of energy saving potential and $$\text {CO}_{2}$$ emissions reduction potential are derived. Findings resulting from the model application show that there are great disparities in regional efficiencies, and the inefficiency of Chinese regions is largely driven by those inefficient regions in the central and western areas. Notably, the development of recovery energy can help to improve regional energy efficiency and $$\text {CO}_{2}$$ emissions efficiency in China.

Natural Gas Pricing Mechanism Reform and its Impacts on Future Energy Options in China

Natural gas is the cleanest fossil fuel. In recent years, its demand in China has been increasing at a rapid pace, but its pricing mechanism is still based on the planned economy system and is not keeping up pace with that of its consumption. Therefore, reforming the existing pricing system is of great significance. This paper first reviews the evolution of the pricing mechanism of natural gas in China, and then examines with model predictions the feasibility of a nationwide implementation of the reform programs currently carried out in Guangdong and Guangxi and its possible impacts. The results show that the reform can: (a) benefit Chinese natural gas producers and importers by increasing their profits, (b) increase the production of natural gas and accelerate the development of the industry, (c) reduce the use of natural gas in the chemical industry and optimize the energy consumption structure in China, (d) change the current energy portfolio in China and achieve the goal of sustainable development, and (e) help Chinese companies enhance their ability of adapting to high prices and promote their international competitiveness.