Font Size: a A A

Coal Demand Forecast In The Future Under The Constraints Of Resources And Environment

Posted on:2021-05-08Degree:MasterType:Thesis
Country:ChinaCandidate:H SongFull Text:PDF
GTID:2370330602972291Subject:Geological Engineering
Abstract/Summary:PDF Full Text Request
Coal has been the main resource consumed in China for a long time,In 2018,China's total primary energy consumption was 4.646 billion Tce,accounting for about 59%of China's total primary energy consumption in 2018.The increase of China's carbon emissions accounted for 30%of the total global increase in 2017,which promoted the increase of global carbon dioxide emissions and increased the pressure to mitigate climate change.The large-scale use of coal has also brought serious environmental pollution problems such as haze.China has put forward requirements for strengthening the construction of ecological civilization and green development in the 13th five year plan outline and the report of the 18th National Congress and other documents.It can be seen that China attaches great importance to the construction of ecological environment protection and ecological civilization in the process of economic development.After analyzing and comparing the research methods of medium and long-term coal demand of many scholars,this paper uses neural network model,multiple regression,time series prediction,etc.,selects per capita GDP,the proportion of labor population as the prediction parameters of economic development,and chooses carbon emission,SO2,smoke?dust?and total energy demand as the causes of resource and environmental pressure.The Research and experimental development expenditure was selected as the prediction parameters of technical level.Meanwhile,the electric power production,urbanization rate and crude steel production are selected as the prediction parameters of three major coal consumption industries:thermal power industry,construction industry and steel industry.In this paper,MATLAB,SPSS,Python and other mathematical tools are used to build the prediction model.This paper selceted MSE value of the prediction results to evaluate the prediction results of each mode,used as the proportion value of each model to participate in the combined prediction and carried out the combined prediction result of coal demand.The final prediction results show that:from 2020 to 2050,China's coal consumption is in a state of phased decline.2025-2040 is the period with the largest decline rate of coal consumption.Based on GDP,air pollutant emissions,carbon emissions and other parameters.this paper analyzes China's future coal demand under the pressure of resources,environment and climate change.Compared with other mechanisms,the predicted results under the consideration of environmental pressure in this paper are reduced,In 2040,the predicted value of this paper is about 20 million tons of raw coal lower than that of the resource strategy research center of Geological Survey Bureau,about 30 million tons lower than that of BP,and about 80 million tons lower than that of EIA.It can be seen that considering the pressure of resources and environment,the demand for coal will be more restrained in the future.In order to achieve the economic and ecological environment development goals set out in the first and second 15-year goals and the second100-year goals,China should develop high-efficiency coal technology,improve the utilization efficiency of coal and reduce the emission of pollutants.On the other hand,China should vigorously develop photovoltaic energy,nuclear energy and other non fossil energy to increase the proportion of emerging energy in the total energy consumption of China.In addition,China should vigorously develop the direction of coal clean chemical industry,such as directional pyrolysis,hydrogenation pyrolysis,and improve the proportion of clean coal chemical industry in the coal consumption structure to slow down the pressure of coal supply side reduction.
Keywords/Search Tags:Coal demand, Resource and environment pressure, Climate change, Neural network
PDF Full Text Request
Related items