Economic and intensity effects of coal consumption in China

2022 ◽  
Vol 301 ◽  
pp. 113912
Author(s):  
Jiandong Chen ◽  
Zhiwen Li ◽  
Malin Song ◽  
Yuzhi Wang ◽  
Yinyin Wu ◽  
...  
Keyword(s):  
2020 ◽  
Vol 6 (2) ◽  
pp. 194-221 ◽  
Author(s):  
Paul K. Gellert ◽  
Paul S. Ciccantell

Predominant analyses of energy offer insufficient theoretical and political-economic insight into the persistence of coal and other fossil fuels. The dominant narrative of coal powering the Industrial Revolution, and Great Britain's world dominance in the nineteenth century giving way to a U.S.- and oil-dominated twentieth century, is marred by teleological assumptions. The key assumption that a complete energy “transition” will occur leads some to conceive of a renewable-energy-dominated twenty-first century led by China. After critiquing the teleological assumptions of modernization, ecological modernization, energetics, and even world-systems analysis of energy “transition,” this paper offers a world-systems perspective on the “raw” materialism of coal. Examining the material characteristics of coal and the unequal structure of the world-economy, the paper uses long-term data from governmental and private sources to reveal the lack of transition as new sources of energy are added. The increases in coal consumption in China and India as they have ascended in the capitalist world-economy have more than offset the leveling-off and decline in some core nations. A true global peak and decline (let alone full substitution) in energy generally and coal specifically has never happened. The future need not repeat the past, but technical, policy, and movement approaches will not get far without addressing the structural imperatives of capitalist growth and the uneven power structures and processes of long-term change of the world-system.


2021 ◽  
Vol 13 (14) ◽  
pp. 7612
Author(s):  
Mahdis sadat Jalaee ◽  
Alireza Shakibaei ◽  
Amin GhasemiNejad ◽  
Sayyed Abdolmajid Jalaee ◽  
Reza Derakhshani

Coal as a fossil and non-renewable fuel is one of the most valuable energy minerals in the world with the largest volume reserves. Artificial neural networks (ANN), despite being one of the highest breakthroughs in the field of computational intelligence, has some significant disadvantages, such as slow training, susceptibility to falling into a local optimal points, sensitivity of initial weights, and bias. To overcome these shortcomings, this study presents an improved ANN structure, that is optimized by a proposed hybrid method. The aim of this study is to propose a novel hybrid method for predicting coal consumption in Iran based on socio-economic variables using the bat and grey wolf optimization algorithm with an artificial neural network (BGWAN). For this purpose, data from 1981 to 2019 have been used for modelling and testing the method. The available data are partly used to find the optimal or near-optimal values of the weighting parameters (1980–2014) and partly to test the model (2015–2019). The performance of the BGWAN is evaluated by mean squared error (MSE), mean absolute error (MAE), root mean squared error (RMSE), standard deviation error (STD), and correlation coefficient (R^2) between the output of the method and the actual dataset. The result of this study showed that BGWAN performance was excellent and proved its efficiency as a useful and reliable tool for monitoring coal consumption or energy demand in Iran.


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3226
Author(s):  
Jakub Jasiński ◽  
Mariusz Kozakiewicz ◽  
Maciej Sołtysik

The European Green Deal aims to make Europe the world’s first climate-neutral continent by 2050 by shifting to a clean circular economy, combating biodiversity loss and reducing pollution levels. In Poland, whose economy invariably remains one of the most dependent on coal consumption in Europe, institutional responses to the above EU objectives have taken the shape of energy cooperatives aimed at filling the gaps in the development of the civic dimension of energy on a local scale and the use of potential renewable energy sources in rural areas, including in relation to the agricultural sector. This article is a continuation of the authors’ previous research work, which has so far focused on the analysis of the development of profitability of Polish institutions that fit into the European idea of a “local energy community”, which includes energy cooperatives. In this research paper, they present the results of subsequent research work and analyses performed on the basis of it which, on the one hand, complement the previously developed optimization model with variables concerning actual energy storage and, on the other hand, analyze the profitability of the operation of energy cooperatives in the conditions of the “capacity market”. The latter was actually introduced in Poland at the beginning of 2021. The research took account of the characteristics of energy producers and consumers in rural areas of Poland, the legally defined rules for the operation of the capacity market and the institutional conditions for the operation of energy cooperatives that can use the potential of energy storage. A dedicated mathematical model in mixed integer programming technology was used, enriched with respect to previous research, making it possible to optimize the operation of energy cooperative with the use of actual energy storage (batteries). Conclusions from the research and simulation show that the installation of energy storage only partially minimizes the volume of energy drawn from the grid in periods when fees related to the capacity market are in force (which should be avoided due to higher costs for consumers). The analysis also indicates that a key challenge is the proper parameterization of energy storage.


Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2950
Author(s):  
Vinod Kumar ◽  
Liqiang Duan

Coal consumption and CO2 emissions are the major concerns of the 21st century. Solar aided (coal-fired) power generation (SAPG) is paid more and more attention globally, due to the lesser coal rate and initial cost than the original coal-fired power plant and CSP technology respectively. In this paper, the off-design dynamic performance simulation model of a solar aided coal-fired power plant is established. A 330 MW subcritical coal-fired power plant is taken as a case study. On a typical day, three various collector area solar fields are integrated into the coal-fired power plant. By introducing the solar heat, the variations of system performances are analyzed at design load, 75% load, and 50% load. Analyzed parameters with the change of DNI include the thermal oil mass flow rate, the mass flow rate of feed water heated by the solar energy, steam extraction mass flow rate, coal consumption, and the plant thermal efficiency. The research results show that, as DNI increases over a day, the coal saving rate will also increase, the maximum coal saving rate reaches up to 5%, and plant thermal efficiency reaches 40%. It is analyzed that the SAPG system gives the best performance at a lower load and a large aperture area.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Jiansu Wei ◽  
Weijun Zhu ◽  
Duanyang Liu ◽  
Xiao Han

Based on the surface meteorological data of Jiangsu Province during 1980–2012, the climatic characteristics and the trends of haze were analyzed. The results indicated that during 1980–2012 haze days increased; in particular, severe and moderate haze days significantly increased. In the northern and coastal cities of Jiangsu Province China, haze days showed a significant increase. Haze often appeared in fall and winter and rarely in summer in the study area. It also occurred more often inland, and less along the coast. Haze occurred more often in June due to straw burning in the harvest time. The haze day increased during the 1990s over southern and southwestern Jiangsu Province; in central and northern Jiangsu, haze day increased after 2000. The continuous, regional, and regional continuous haze days all showed increasing trends. As the urban area expanded each year, industrial emissions, coal consumption, and car ownership increased accordingly, resulting in regional temperature increase and relative humidity decrease, which formed the urban heat island and dry island effects. Hence, haze formation and maintenance conditions became more favorable for more haze days, which led to the increase of haze days, and the significant increases of continuous, regional, and regional continuous haze days.


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