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中国城市天然气需求趋势预测

Forecast of Urban Natural Gas Demand Trend in China
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摘要 随着城镇化建设的快速推进,城市天然气供不应求时有发生,准确掌握城市天然气需求量变化趋势,是科学制定城市供气计划的前提。为精准预测城市天然气需求量,运用灰色关联分析法,诊断城市基础建设、城市燃气普及率、产业结构、人口密度、天然气用气人口、消费水平、人口发展、城镇化水平等8个影响因素之间的多重共线性问题,深度挖掘出5个有效影响因素构建GM(1,N)模型,对中国城市天然气需求量进行预测分析。研究结果表明:城市基础建设、人口密度、天然气用气人口、消费水平、人口发展等5个有效影响因素中,对中国城市天然气需求影响最大的3个因素依次是城市基础建设、天然气用气人口、消费水平;基于5个有效影响因素构建的GM(1,6)模型能很好地拟合城市天然气需求量历史数据,并预测出2022—2030年中国城市天然气需求量将呈现先增后降的发展趋势。 With the rapid promotion of urbanization,the shortage of natural gas in cities has occurred from time to time.Accurately grasping the change trend in urban natural gas demand is the prerequisite for scientifically formulating urban gas supply plans.To accurately predict urban natural gas demand,the paper uses the grey relational analysis method to diagnose such multiple collinearity problems between 8 influencing factors as urban infrastructure,gas penetration rate,industrial structure,population density,number of gas users,consumption level,population growth,and urbanization level and analyzes the demand for natural gas in Chinese cities by deeply digging 5 effective influencing factors and constructing the GM(1,N)model.The research results show that the 3 factors that have the greatest impact on natural gas demand in Chinese cities in order are urban infrastructure,number of gas users,and consumption level respectively among the 5 effective influencing factors.The GM(1,6)model constructed based on the 5 effective influencing factors can fit the historical data of urban natural gas demand well and predict that the demand for natural gas in Chinese cities will show a trend of increasing first and then decreasing from 2022 t o 2030.
作者 李洪兵 韩咪 刘可 吴小东 LI Hongbing;HAN Mi;LIU Ke;WU Xiaodong(College of Engineering,Sichuan Normal University,Chengdu 610101,China;School of Economics and Management,Southwest Petroleum University,Chengdu 610500,China;School of Economics and Management,Chinese and Law,Shandong Institute of Petroleum and Chemical Technology,Dongying 257061,China;Guangdong University of Petrochemical Technology,Maoming 525000,China)
出处 《油气与新能源》 2024年第3期6-13,共8页 Petroleum and new energy
基金 四川省科技计划项目“四川天然气供需安全演化机理研究”(2023NSFSC1038) 国家民委“一带一路”国别和区域研究中心“日本应急管理研究中心”项目“基于双层规划的灾后应急物资调度模型研究”(2023RBYJGL-4) 四川省哲学社会科学重点实验室“智慧应急管理重点实验室”项目“城市基层社区洪涝灾害应急能力提升路径研究”(2023ZHYJGL-6)。
关键词 城市天然气 影响因素 需求预测 灰色关联度 GM(1 N)模型 Urban natural gas Influence factors Demand forecast Degree o f grey incidence GM(1,N)model
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