基于改进的超效率SBM中国工业能源效率评价
发布时间：2018-09-11 19:22
【摘要】：中国经济的快速增长导致大量能源消耗和CO_2排放。如今在CO_2排放和能源消耗方面,中国已经超过美国,成为世界上最大的国家。为实现可持续发展、提高能源效率和控制温室气体排放,中国政府提出了建设环境友好型和资源节约型社会的战略目标。工业占据我国最大的终端能源消耗,占全国能源终端消费比例的70%,工业的能源利用情况对我国总体的能源利用情况有着重要的影响。本文对基于松弛变量视角的超效率SBM模型进行了改进,引入了非期望产出使得该模型更贴近生产实际,得出的结果更加合理。在本文改进的模型基础上结合逆DEA方法,计算出SBM有效地决策单元的能源最小节省量,用于构建对SBM有效的决策单元进行评价的能源效率指标。本文主要结论如下:中国各地区的工业能源效率情况差别明显,其中天津、北京、上海和广东每年的效率值均高于1,远远领先于其他省份,我国各个省的效率值分布差异很明显;东部能源效率值以明显的优势高于中部和西部,中部区域排第二,西部区域能源效率值排最后;Tobit回归分析结果表明地区GDP、地区人均GDP、经济结构、外商直接投资、工业新增固定投资和地理位置位于东部对地区工业能源效率有积极影响,地区产业结构和人口密度对地区工业能源效率有消极的影响,地理位置位于中部对工业能源效率没有显著影响;节能潜力较高的地区为河北、河南、山东等地区,山东、河南、河北等是减排潜力最大的地区;区域节能潜力为中部和西部交替居首位和第二位,东部地区位居第三,区域减排潜力为中部区域CO_2减排潜力最大,西部区域第二,东部区域最后。基于以上的结论和文中的分析,对于提升工业能源效率给出如下建议:提升效率水平较低地区的经济活动总量;根据地区能源产出的特点来调整地区工业结构;加快我国能源结构调整和工业企业电能替代;定量化企业的碳排放额度,开放碳排放的交易市场。
[Abstract]:China's rapid economic growth has led to massive energy consumption and CO_2 emissions. China has now overtaken the United States as the world's largest country in terms of CO_2 emissions and energy consumption. In order to achieve sustainable development, improve energy efficiency and control greenhouse gas emissions, the Chinese government has put forward the strategic goal of building an environmentally friendly and resource-efficient society. Industry occupies the largest terminal energy consumption in China, accounting for 70% of the national energy terminal consumption. The energy utilization of industry has an important impact on the overall energy utilization in China. In this paper, the super-efficiency SBM model based on relaxation variable is improved, and the non-expected output is introduced to make the model more close to the production practice, and the result is more reasonable. Based on the improved model and inverse DEA method, the minimum energy saving of SBM efficient decision making unit is calculated, which is used to construct the energy efficiency index for evaluating the effective decision making unit of SBM. The main conclusions of this paper are as follows: there are significant differences in the industrial energy efficiency among different regions in China. Among them, Tianjin, Beijing, Shanghai and Guangdong all have efficiency values higher than 1 per year, far ahead of other provinces. The distribution of efficiency values in various provinces in China is very obvious; the energy efficiency values in the east are significantly higher than those in the central and western regions, and the central regions rank second. The results of Tobit regression analysis show that the per capita GDP, economic structure, foreign direct investment (FDI), new fixed investment in industry and location in the east have a positive effect on the industrial energy efficiency in the GDP, region. The regional industrial structure and population density have a negative impact on the regional industrial energy efficiency, the geographical location in the central region has no significant impact on the industrial energy efficiency, and the regions with high energy saving potential are Hebei, Henan, Shandong, Shandong, and Henan. Hebei and so on are the regions with the greatest emission reduction potential, the regional energy saving potential is the first and second in the central and western regions, the eastern region is the third, the regional emission reduction potential is the largest in the central region and the second in the western region. Last in the eastern region. Based on the above conclusions and the analysis in this paper, the following suggestions are given to improve the industrial energy efficiency: to promote the total economic activity in areas with low efficiency level, to adjust the regional industrial structure according to the characteristics of regional energy output; Speed up the adjustment of energy structure and electric power substitution of industrial enterprises, quantify the carbon emission quota of enterprises, and open up the trading market of carbon emissions.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F224;F424
本文编号：2237642
[Abstract]:China's rapid economic growth has led to massive energy consumption and CO_2 emissions. China has now overtaken the United States as the world's largest country in terms of CO_2 emissions and energy consumption. In order to achieve sustainable development, improve energy efficiency and control greenhouse gas emissions, the Chinese government has put forward the strategic goal of building an environmentally friendly and resource-efficient society. Industry occupies the largest terminal energy consumption in China, accounting for 70% of the national energy terminal consumption. The energy utilization of industry has an important impact on the overall energy utilization in China. In this paper, the super-efficiency SBM model based on relaxation variable is improved, and the non-expected output is introduced to make the model more close to the production practice, and the result is more reasonable. Based on the improved model and inverse DEA method, the minimum energy saving of SBM efficient decision making unit is calculated, which is used to construct the energy efficiency index for evaluating the effective decision making unit of SBM. The main conclusions of this paper are as follows: there are significant differences in the industrial energy efficiency among different regions in China. Among them, Tianjin, Beijing, Shanghai and Guangdong all have efficiency values higher than 1 per year, far ahead of other provinces. The distribution of efficiency values in various provinces in China is very obvious; the energy efficiency values in the east are significantly higher than those in the central and western regions, and the central regions rank second. The results of Tobit regression analysis show that the per capita GDP, economic structure, foreign direct investment (FDI), new fixed investment in industry and location in the east have a positive effect on the industrial energy efficiency in the GDP, region. The regional industrial structure and population density have a negative impact on the regional industrial energy efficiency, the geographical location in the central region has no significant impact on the industrial energy efficiency, and the regions with high energy saving potential are Hebei, Henan, Shandong, Shandong, and Henan. Hebei and so on are the regions with the greatest emission reduction potential, the regional energy saving potential is the first and second in the central and western regions, the eastern region is the third, the regional emission reduction potential is the largest in the central region and the second in the western region. Last in the eastern region. Based on the above conclusions and the analysis in this paper, the following suggestions are given to improve the industrial energy efficiency: to promote the total economic activity in areas with low efficiency level, to adjust the regional industrial structure according to the characteristics of regional energy output; Speed up the adjustment of energy structure and electric power substitution of industrial enterprises, quantify the carbon emission quota of enterprises, and open up the trading market of carbon emissions.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F224;F424
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，本文编号：2237642
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