摘要
基于我国化石能源消费的原始数据,应用灰色新陈代谢模型分别预测了2007-2020年煤、石油、天然气消费量,建立了化石能源消费量与CO2排放量的线性回归模型,实现了对化石能源燃烧产生的CO2排放量的预测,并分析了未来10 a化石能源消费与CO2排放趋势。结果表明,该方法计算简便、易操作、拟合度和预测精度较高、结果可靠,可为能源发展和CO2减排提供科学依据。
The energy consumptions of coal, petroleum and natural gas from 2007 to 2020 are forecasted, by mean of applying information renewal grey model to the history dataset of fossil energy consumption in China. Linear regression analysis is utilized to delineate the relationship between the fossil energy consumption and carbon dioxide emission. The carbon dioxide emission arising from fossil energy consumption are also predicted. The trends of fossil energy consumption and carbon dioxide emission till 2020 are also analyzed. The proposed method is simple to use, without any sacrifice on prediction accuracy. The results provide a quantitative scientific basis for energy development and carbon dioxide emission reduction in China.
出处
《水电能源科学》
北大核心
2009年第5期224-227,共4页
Water Resources and Power
基金
中国科学院知识创新工程基金资助项目(KSCX2-YW-G-028)
山东省科技攻关基金资助项目(2008GG20006002)
关键词
能源消费
CO2排放
灰色预测
新陈代谢模型
线性回归模型
energy consumption
carbon dioxide emission
grey forecast
information renewal model
linear regression model
