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Natural gas consumption forecasting model based on coal-to-gas project in China 被引量:4
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作者 Zhiqiang Wang Yichen Li +1 位作者 Zhanjun Feng Kai Wen 《Global Energy Interconnection》 2019年第5期430-436,共7页
Natural gas is widely used because it is environmentally friendly,particularly in reducing carbon emission and improving the Air Quality Index(AQI)around densely populated cities.China has initiated a coal-to-gas proj... Natural gas is widely used because it is environmentally friendly,particularly in reducing carbon emission and improving the Air Quality Index(AQI)around densely populated cities.China has initiated a coal-to-gas project(CGP)to improve the air quality in northern China.As a subcompany of China National Petroleum Corporation,PetroChina Natural Gas Marketing North Company has been focusing on natural gas resource allocation while considering numerous issues such as ensuring the bottom line of livelihood requirements in winter and the performance of economic indicators for an entire calendar year in the northern part of China.Therefore,the accurate prediction of natural gas consumption is important to PetroChina Natural Gas Marketing North Company.It has become a challenge to forecast natural gas consumption because the natural gas market has changed considerably because of the CGP.Natural gas consumption cannot be forecasted using conventional models.This study analyzes the characteristics of the CGP based on the data obtained from rural individual users and company users.Based on the analysis,the gas consumption in winter is predicted using two different forecasting approaches.The methods presented in this paper provide a basis for formulating effective measures for natural gas scheduling in the northern part of China. 展开更多
关键词 Natural gas Coal to gas project CGP gas consumption forecasting End user consumption characteristics
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Quantitative Analysis and Prediction of China's Natural Gas Consumption in Different Sectors Based on Bayesian Network
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作者 Jian CHAI Yabo WANG +3 位作者 Zhaohao WEI Huiting SHI Xiaokong ZHANG Xuejun ZHANG 《Journal of Systems Science and Information》 CSCD 2022年第4期338-353,共16页
In view of the heterogeneity of natural gas consumption in different sectors in China,this paper utilizes Bayesian network(BN)to study the driving factors of natural gas consumption in power generation,chemical and in... In view of the heterogeneity of natural gas consumption in different sectors in China,this paper utilizes Bayesian network(BN)to study the driving factors of natural gas consumption in power generation,chemical and industrial fuel sectors.Combined with Bayesian model averaging(BMA)and scenario analysis,the gas consumption of the three sectors is predicted.The results show that the expansion of urbanization will promote the gas consumption of power generation.The optimization of industrial structure and the increase of industrial gas consumption will enhance the gas consumption of chemical sector.The decrease of energy intensity and the increase of gas consumption for power generation will promote the gas consumption of industrial fuel.Moreover,the direct influencing factors of gas price are urbanization,energy structure and energy intensity.The direct influencing factors of environmental governance intensity are gas price,urbanization,industrial structure,energy intensity and energy structure.In 2025,under the high development scenario,China’s gas consumption for power generation,chemical and industrial fuel sectors will be 66.034,36.552 and 109.414 billion cubic meters respectively.From 2021 to 2025,the average annual growth rates of gas consumption of the three sectors will be 4.82%,2.18%and 4.43%respectively. 展开更多
关键词 Bayesian network influence factors Bayesian model average forecast natural gas consumption in different sectors
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