基于节能降耗的辽宁能源发展战略研究

发布时间：2018-12-27 13:18

【摘要】：能源是经济和社会发展的重要物质基础,生产和生活的方方面面都离不开能源。辽宁是能源消费大省,节能降耗任务十分艰巨。当前国外学者针对能源消费、能源强度等多个角度与经济发展之间关系的研究颇为丰富,国内学者针对各省能源消费以及经济发展水平之间存在的关系也进行了大量研究,但目前定量分析辽宁能源消费情况的不多,对未来进行预测的文献更少。论文首先对国内外大量相关文献进行综述,为本文的撰写提供理论依据。其次对相关概念进行界定,并对辽宁能源消费的现状进行分析,指出当前辽宁能源消费领域存在的诸多问题,因此实施能源发展战略十分必要。再次综合考虑人口、经济发展、能源结构、产业结构和汽车拥有量等诸多因素,兼顾考虑数据的可获得性,进行回归分析,得出辽宁能源消费影响因素的定量分析结果。回归过程采取偏最小二乘方法,该方法在自变量存在严重多重共线性和样本个数小于变量个数的条件下仍然适用,因此可更好的保证计算结果的准确性和可靠性。利用时间序列ARIMA和灰色预测组合预测模型对“十二五”期间辽宁能源消费总量进行预测,发现未来几年辽宁省能源消费仍以较高的速度增长,并保持在很高的消费水平。ARIMA模型是预测精度较高的短期预测模型,灰色模型通过寻找等待预测系统的变化规律,对系统内部数据的未来变化进行预测,对随时间变化递增或递减的序列预测效果较好。最后采用SWOT分析,对辽宁能源环境进行分析,制定出尽可能发挥优势、把握机遇、缩小劣势和规避威胁的战略。SWOT分析方法综合考虑内外部环境,考虑问题比较全面,能够客观而准确的分析问题。
[Abstract]:Energy is an important material basis for economic and social development. Liaoning is a big energy consumption province, energy conservation and consumption reduction task is very arduous. At present, foreign scholars have done a lot of research on the relationship between energy consumption, energy intensity and economic development. Domestic scholars have also done a lot of research on the relationship between energy consumption and the level of economic development in various provinces. However, there is not much quantitative analysis of Liaoning energy consumption, and there are fewer literatures to predict the future. Firstly, the paper summarizes a large number of related literature at home and abroad to provide theoretical basis for the writing of this paper. Secondly, it defines the related concepts, analyzes the current situation of Liaoning energy consumption, and points out many problems in Liaoning energy consumption field, so it is necessary to implement the energy development strategy. Considering the factors such as population, economic development, energy structure, industrial structure and car ownership, and taking into account the availability of data, the quantitative analysis results of the factors affecting energy consumption in Liaoning are obtained. The partial least square method is adopted in the regression process. This method is still applicable under the condition that the independent variables have serious multiple collinearity and the number of samples is smaller than the number of variables, so the accuracy and reliability of the calculation results can be better guaranteed. The total energy consumption in Liaoning Province during the 12th Five-Year Plan period is predicted by using time series ARIMA and grey forecast combined forecasting model, and it is found that the energy consumption in Liaoning Province will still increase at a relatively high speed in the next few years. ARIMA model is a short-term prediction model with high prediction accuracy. Grey model predicts the future change of system data by looking for the change law of waiting prediction system. It is better to predict the series with increasing or decreasing with time. Finally, the SWOT analysis is used to analyze the energy environment in Liaoning Province, and a strategy is worked out to give full play to the advantages, seize the opportunities, reduce the disadvantages and avoid the threat. The SWOT analysis method considers the internal and external environment comprehensively, and considers the problems more comprehensively. Able to analyze problems objectively and accurately.
【学位授予单位】：大连交通大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F426.2

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