电信运营企业节能定量指标分解模型研究

发布时间：2018-06-28 01:59

本文选题：电信运营企业 + 节能定量指标　；参考：《北京邮电大学》2013年硕士论文

【摘要】：伴随着经济发展和国际能源价格提高,能源问题已成为世界各国的主要议题。我国是世界上最大的发展中国家,同时是继美国之后的第二大能源消耗国。为此,国家将节能减排作为转变发展方式、推动科学发展的重要抓手,提出“十一五”单位GDP能耗降低20%左右的目标。同时,国资委将三家电信运营企业的类别由“一般类”调整为“关注类”,定量考核企业能耗指标。针对电信运营企业,能源效率的影响因素有哪些?如何度量各因素的贡献度?如何根据这些影响因素将全集团的节能定量指标分解到各个分公司?本文以指数分解分析理论为基本框架,进行节能减排指标的三个层次的分解,定量研究影响电信运营企业能源消耗的相关因素,并以这些影响因素为依据,将节能定量指标分解到各分公司。指数分解分析理论是重要的系统分析工具,在过去二十余年中广泛应用于区域、国家及产业的能源和环境研究,主要从产业结构、部门能源强度、能源价格、能源消耗结构等角度分析过去一段时间内宏观层面的能源效率变化。但目前国内外在电信运营企业层面的研究涉及较少。本文将模型构建和实证研究相结合,主要研究以下内容： 1、在查阅相关文献的基础上,从管理和技术节能两个角度,归纳了电信运营企业节能减排的研究现状。 2、对指数分解分析理论体系进行归纳总结,将该理论的发展分为引入阶段和完善阶段,对比体系中各模型的合理性、可逆性、残差、零值和负值鲁棒性等特性,选择采用拉斯贝尔指数模型和对数平均迪氏指数模型考察部门产品份额、能源效率、不同能耗场景能耗等因素对总体的影响。 3、将两种指数模型结合,构建能源效率的预测模型,同时利用季节指数模型、回归分析等方法预测产出量,在此基础上将节能定量指标分解到各个部门。 4、结合实证分析结果,分析了各影响因素对电信运营企业总体指标的作用,并对进一步发展提出了建议。
[Abstract]:With the development of economy and the increase of international energy price, energy problem has become the main issue in the world. China is the world's largest developing country and the second largest energy consumer after the United States. Therefore, the state regards energy saving and emission reduction as an important hand in transforming development mode and promoting scientific development, and puts forward the target of reducing energy consumption per unit GDP of the 11th Five-Year Plan by about 20%. At the same time, SASAC adjusted the category of three telecom operators from "general category" to "concern class", and quantitatively assessed the energy consumption index of enterprises. For telecom operators, what are the factors affecting energy efficiency? How to measure the contribution of each factor? How to decompose the energy saving quantitative index of the whole group into each branch according to these influencing factors? In this paper, based on the theory of exponential decomposition analysis, three levels of energy saving and emission reduction targets are decomposed, and the related factors that affect the energy consumption of telecom operators are quantitatively studied, and based on these influencing factors. The energy saving quantitative index will be decomposed to each branch company. The theory of exponential decomposition analysis is an important tool for systematic analysis. It has been widely used in regional, national and industrial energy and environmental studies in the past two decades, mainly in terms of industrial structure, sector energy intensity, and energy prices. The change of energy efficiency at the macro level in the past period of time is analyzed from the perspective of energy consumption structure. But at present the domestic and foreign research in the telecommunication operation enterprise level involves less. This paper combines the model construction and empirical research, mainly studies the following contents: 1, based on the related literature, from the two angles of management and technology energy saving, The research status of energy saving and emission reduction in telecom operation enterprises is summarized. 2, the theoretical system of exponential decomposition analysis is summarized, and the development of the theory is divided into the stage of introduction and the stage of perfection, and the rationality of each model in the system is compared. Reversibility, residuals, zero and negative robustness, etc., are selected to study sector product share, energy efficiency, and logarithmic average Dee exponent model. The influence of energy consumption on the whole in different energy consumption scenarios. 3. Combining the two exponential models, the prediction model of energy efficiency is constructed, and the output is predicted by using seasonal exponential model and regression analysis, etc. On this basis, the quantitative index of energy saving is decomposed into various departments. 4 combined with the results of empirical analysis, this paper analyzes the effect of various factors on the overall index of telecom operation enterprises, and puts forward some suggestions for further development.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F626.1;F224

【参考文献】