Energies

Research

13 pages, 942 KiB

Open AccessArticle

Is China’s Natural Gas Consumption Converging? Empirical Research Based on Spatial Econometrics

by Xin Guan, Xiangyi Lu and Yang Wen

Energies 2022, 15(24), 9448; https://doi.org/10.3390/en15249448 - 13 Dec 2022

Cited by 2 | Viewed by 1219

Excessive regional differences in energy consumption have led to inequality and energy poverty. It is essential to clarify the factors of energy consumption convergence to solve this problem. We use the spatial convergence model to analyze the convergence characteristics and conditions of China’s [...] Read more.

Excessive regional differences in energy consumption have led to inequality and energy poverty. It is essential to clarify the factors of energy consumption convergence to solve this problem. We use the spatial convergence model to analyze the convergence characteristics and conditions of China’s natural gas consumption from 2005 to 2017. The results of spatial absolute convergence show that there is absolute convergence of natural gas consumption in China, and the economic competition among provinces slightly hinders the convergence. Furthermore, based on the spatial Durbin model and the spatial conditional convergence model, we found that insufficient pipe network construction and the price difference caused by provincial borders are the main factors hindering the flow of natural gas, which also restricts the spatial convergence of natural gas consumption. The development of the tertiary industry and the improvement of purchasing power will help accelerate the convergence of natural gas consumption. This research not only evaluates the spatial convergence of China’s natural gas consumption for the first time, but also provides an analytical idea for formulating policies to eliminate poverty in energy consumption. Full article

(This article belongs to the Special Issue New Insights into Energy Economics and Sustainable Development)

► Show Figures

Figure 1

26 pages, 1264 KiB

Open AccessArticle

Sectoral Analysis of Energy Transition Paths and Greenhouse Gas Emissions

by Róbert Csalódi, Tímea Czvetkó, Viktor Sebestyén and János Abonyi

Energies 2022, 15(21), 7920; https://doi.org/10.3390/en15217920 - 25 Oct 2022

Cited by 5 | Viewed by 2243

Abstract

The Paris Climate Agreement and the 2030 Agenda for Sustainable Development Goals declared by the United Nations set high expectations for the countries of the world to reduce their greenhouse gas (GHG) emissions and to be sustainable. In order to judge the effectiveness [...] Read more.

The Paris Climate Agreement and the 2030 Agenda for Sustainable Development Goals declared by the United Nations set high expectations for the countries of the world to reduce their greenhouse gas (GHG) emissions and to be sustainable. In order to judge the effectiveness of strategies, the evolution of carbon dioxide, methane, and nitrous oxide emissions in countries around the world has been explored based on statistical analysis of time-series data between 1990 and 2018. The empirical distributions of the variables were determined by the Kaplan–Meier method, and improvement-related utility functions have been defined based on the European Green Deal target for 2030 that aims to decrease at least 55% of GHG emissions compared to the 1990 levels. This study aims to analyze the energy transition trends at the country and sectoral levels and underline them with literature-based evidence. The transition trajectories of the countries are studied based on the percentile-based time-series analysis of the emission data. We also study the evolution of the sector-wise distributions of the emissions to assess how the development strategies of the countries contributed to climate change mitigation. Furthermore, the countries’ location on their transition trajectories is determined based on their individual Kuznets curve. Runs and Leybourne–McCabe statistical tests are also evaluated to study how systematic the changes are. Based on the proposed analysis, the main drivers of climate mitigation and evaluation and their effectiveness were identified and characterized, forming the basis for planning sectoral tasks in the coming years. The case study goes through the analysis of two counties, Sweden and Qatar. Sweden reduced their emission per capita almost by 40% since 1990, while Qatar increased their emission by 20%. Moreover, the defined improvement-related variables can highlight the highest increase and decrease in different aspects. The highest increase was reached by Equatorial Guinea, and the most significant decrease was made by Luxembourg. The integration of sustainable development goals, carbon capture, carbon credits and carbon offsets into the databases establishes a better understanding of the sectoral challenges of energy transition and strategy planning, which can be adapted to the proposed method. Full article

(This article belongs to the Special Issue New Insights into Energy Economics and Sustainable Development)

► Show Figures

Figure 1

16 pages, 891 KiB

Open AccessArticle

Analysis of Influencing Factors of Thermal Coal Price

by Shiqiu Zhu, Yuanying Chi, Kaiye Gao, Yahui Chen and Rui Peng

Energies 2022, 15(15), 5652; https://doi.org/10.3390/en15155652 - 4 Aug 2022

Cited by 5 | Viewed by 3872

Abstract

As the world’s largest coal consumer, China’s coal consumption in 2021 was 2934.4 million tons of standard coal. Thermal coal occupies an important position in the coal market and industry system, as an important raw material in the power industry, steel industry and [...] Read more.

As the world’s largest coal consumer, China’s coal consumption in 2021 was 2934.4 million tons of standard coal. Thermal coal occupies an important position in the coal market and industry system, as an important raw material in the power industry, steel industry and other industries. The price of thermal coal in 2021 was at its highest level in a decade, and reached a historical level of about 2587.5 yuan per ton in October 2021. In the same month, the government intervened in the thermal coal price, which fell 51.9% by the end of the year under the influence of the policy. In previous studies, there has been little research on thermal coal and the impact of the variable “policy” on the thermal coal price. Thus, this paper analyzed the factors that affect the price fluctuation of thermal coal, and the impact of economic policy uncertainty on the thermal coal price. The cointegration test and forecast-error variance decomposition (FEVD) are adopted in this study. Our results show that the impact of policy uncertainty on the thermal coal price gradually increases over time, but the impact of policy uncertainty on price is negative and not as strong as expected. On the contrary, inventory and other energy prices have a greater positive impact on the price of thermal coal. The results of this study are of significance for the prediction of thermal coal prices in the future. Full article

(This article belongs to the Special Issue New Insights into Energy Economics and Sustainable Development)

► Show Figures

Figure 1

25 pages, 2278 KiB

Open AccessArticle

Optimization of Operating Hydrogen Storage System for Coal–Wind–Solar Power Generation

by Rui Yan, Yuwen Chen and Xiaoning Zhu

Energies 2022, 15(14), 5015; https://doi.org/10.3390/en15145015 - 8 Jul 2022

Cited by 4 | Viewed by 1773

Abstract

To address the severity of the wind and light abandonment problem and the economics of hydrogen energy production and operation, this paper explores the problem of multi-cycle resource allocation optimization of hydrogen storage systems for coal–wind–solar power generation. In view of the seriousness [...] Read more.

To address the severity of the wind and light abandonment problem and the economics of hydrogen energy production and operation, this paper explores the problem of multi-cycle resource allocation optimization of hydrogen storage systems for coal–wind–solar power generation. In view of the seriousness of the problem of abandoning wind and photovoltaic power and the economy of hydrogen production and operation, the node selection and scale setting issues for hydrogen production and storage, as well as decision-making problems such as the capacity of new transmission lines and new pipelines and route planning, are studied. This research takes the satisfaction of energy supply as the basic constraint and constructs a multi-cycle resource allocation optimization model for an integrated energy system, aiming to achieve the maximum benefit of the whole system. Using data from Inner Mongolia, where wind abandonment and power limitation are severe, and Beijing and Shanxi provinces, where hydrogen demand is high, this paper analyzes the benefits of the hydrogen storage system for coal–wind–solar power generation, and explores the impact of national subsidy policies and technological advances on system economics. Full article

(This article belongs to the Special Issue New Insights into Energy Economics and Sustainable Development)

► Show Figures

Figure 1

15 pages, 3048 KiB

Open AccessArticle

Efficiency versus System Synergism: An Advanced Life Cycle Assessment for a Novel Decarbonized Grid System Innovation

by Shukai Liu, Liang Dong, Ling Han, Jiajia Huan and Baihao Qiao

Energies 2022, 15(12), 4214; https://doi.org/10.3390/en15124214 - 8 Jun 2022

Cited by 3 | Viewed by 1515

Abstract

The power sector plays a significant role in carbon neutrality strategies, and the grid system is a crucial part of the power sector. In particular, with less mitigation potential from technology efficiency, the credit from whole life cycles is critical. This paper describes [...] Read more.

The power sector plays a significant role in carbon neutrality strategies, and the grid system is a crucial part of the power sector. In particular, with less mitigation potential from technology efficiency, the credit from whole life cycles is critical. This paper describes the investigation of the environmental impacts of various scenarios from the perspective of life cycles. By using the life cycle assessment (LCA) method, various grid systems are examined as a case study, including a traditional, renewable energy, and power storage grid system, as well as a microgrid, in Guangdong. The results highlight the fact that with the systematic improvement of a grid, significant environmental benefits can be achieved. For a grid system, optimization through technology has significant carbon reduction effects even if the power grid structure is not changed. Using renewable energy instead of traditional fuel can reduce the emission of 0.05 kg of CO₂-equivalent greenhouse gas per 1 kWh of electricity produced, which is 7.9% of the baseline, and microgrid technology leads to a much greater carbon reduction potential of 23.8% of the baseline. The role of energy storage is undervalued due to the limitations of the data. Full article

(This article belongs to the Special Issue New Insights into Energy Economics and Sustainable Development)

► Show Figures

Figure 1

11 pages, 1622 KiB

Open AccessArticle

Prediction Method of Beijing Electric-Energy Substitution Potential Based on a Grid-Search Support Vector Machine

by Yuanying Chi, Yangyi Zhang, Guozheng Li and Yongke Yuan

Energies 2022, 15(11), 3897; https://doi.org/10.3390/en15113897 - 25 May 2022

Cited by 5 | Viewed by 1461

Abstract

Recently, “power cuts” and “coal price surges” have been significant concerns of individuals and societies. The main reasons for a power cut are a recent rapid increase in power consumption, shortage of thermal coal or the large shutdown capacity of thermal power units, [...] Read more.

Recently, “power cuts” and “coal price surges” have been significant concerns of individuals and societies. The main reasons for a power cut are a recent rapid increase in power consumption, shortage of thermal coal or the large shutdown capacity of thermal power units, resulting in a tight power supply in the power grid. In recent years, the shortage of fossil resources has led to frequent energy crises. In the context of carbon peaks and carbon neutralization, how to better develop electric-energy substitution and eliminate the dependence on fossil energy has become a problem that needs to be solved at present. In this paper, the influencing factors of electric-energy substitution in Beijing are analyzed, and the indexes affecting the electric-energy substitution are outlined. By constructing various machine-learning models, the prediction is performed. The results show that the Gaussian kernel support vector machine model based on a grid search has a good prediction effect on the electric-energy substitution potential in Beijing, which has certain guiding significance for electric-energy substitution potential analysis. Full article

(This article belongs to the Special Issue New Insights into Energy Economics and Sustainable Development)

► Show Figures

Figure 1

15 pages, 1201 KiB

Open AccessArticle

Driving Factors of CO₂ Emissions in China’s Power Industry: Relative Importance Analysis Based on Spatial Durbin Model

by Yuanying Chi, Wenbing Zhou, Songlin Tang and Yu Hu

Energies 2022, 15(7), 2631; https://doi.org/10.3390/en15072631 - 3 Apr 2022

Cited by 9 | Viewed by 1924

Abstract

The low-carbon transformation of the power industry is of great significance to realize the carbon peak in advance. However, almost a third of China’s CO₂ emissions came from the power sector in 2019. This paper aimed to identify the key drivers of [...] Read more.

The low-carbon transformation of the power industry is of great significance to realize the carbon peak in advance. However, almost a third of China’s CO₂ emissions came from the power sector in 2019. This paper aimed to identify the key drivers of CO₂ emissions in China’s power industry with the consideration of spatial autocorrelation. The spatial Durbin model and relative importance analysis were combined based on Chinese provincial data from 2003 to 2019. This combination demonstrated that GDP, the power supply structure and energy intensity are the key drivers of CO₂ emissions in China’s power industry. The self-supply ratio of electricity and the spatial spillover effect have a slight effect on increasing CO₂ emissions. The energy demand structure and CO₂ emission intensity of thermal power have a positive effect, although it is the lowest. Second, the positive impact of GDP on CO₂ emissions is decreasing, but that of the power supply structure and energy intensity is increasing. Third, the energy demand of the industrial and residential sectors has a greater impact on CO₂ emissions than that of construction and transportation. For achieving the CO₂ emission peak in advance, governments should give priority to developing renewable power and regional electricity trade rather than upgrading thermal power generation. They should also focus on promoting energy-saving technology, especially tapping the energy-saving potential of the industry and resident sectors. Full article

(This article belongs to the Special Issue New Insights into Energy Economics and Sustainable Development)

► Show Figures

Graphical abstract

14 pages, 994 KiB

Open AccessArticle

Research on Straw-Based High-Quality Energy in China under the Background of Carbon Neutrality

by Ji-Qin Ren, Ya-Wen Yang and Yuan-Ying Chi

Energies 2022, 15(5), 1724; https://doi.org/10.3390/en15051724 - 25 Feb 2022

Cited by 4 | Viewed by 1894

Abstract

It is imperative to use clean energy in order to achieve “carbon neutrality” and “carbon peaking”. This research aims to explore the impact of the agricultural mechanization level, the rural infrastructure construction level, and the rural economic development level on the utilization of [...] Read more.

It is imperative to use clean energy in order to achieve “carbon neutrality” and “carbon peaking”. This research aims to explore the impact of the agricultural mechanization level, the rural infrastructure construction level, and the rural economic development level on the utilization of high-quality straw energy, and, resultingly, this study aims to help provide suggestions for promoting high-quality straw energy utilization, develop the potential of high-quality straw energy, and alleviate China’s energy shortage problem. This paper develops a measurement model using the ridge regression model with panel fixed effects, which overcomes the multi-collinearity problem among the various factors influencing the utilization of high-quality energy from straw. Panel data from 24 provinces and cities, from 2009 to 2017, are used. The results show that the improvements of the agricultural mechanization level, the rural infrastructure construction level, and the rural economic development level all promote the use of high-quality straw energy. Moreover, the level of rural economic development plays a mediating role in the agricultural mechanization level and the rural infrastructure construction level pertaining to straw-based high-quality energy. Policy implications can be easy to derive based on our findings, and these include strengthening governmental investment in agricultural machinery in rural areas, paying more attention to areas with backward rural energy infrastructure construction, ensuring the steady improvement of economic development in rural areas, providing the necessary economic foundation for agricultural supply, and promoting the use of high-quality energy from straw. Full article

(This article belongs to the Special Issue New Insights into Energy Economics and Sustainable Development)

► Show Figures

Figure 1

Journal Menu

Journal Browser

New Insights into Energy Economics and Sustainable Development

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (8 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI