电力投资最优规模与绩效研究

发布时间：2018-04-02 08:19

本文选题：电力投资　切入点：最优规模　出处：《上海电力学院》2017年硕士论文

【摘要】：电力投资是一国能源工业发展必不可少的物质基础。改革开放以来,伴随着经济的高速发展与用电量的快速增长,电力投资总额也在不断地扩大。然而投资规模并非越大越好,由于边际产出递减效应的存在,电力投资存在一个最优规模的问题。鉴于此,分析我国电力投资是否达到最优规模,以及如何评估不同地区的投资绩效,以便做出合理的投资安排,对于电力投资的科学规划有着重要的理论意义和现实意义。首先,为分析电力消费与国民经济的长期趋势,采用HP滤波法将用电量和GDP时间序列分为趋势部分和波动部分,在此基础上借助脉冲响应函数考察两者关系,揭示了电力消费到经济增长的单向长期的因果关系,表明充分的电力供给是经济增长的重要保障。以此为依据,结合财政支出增长效应理论,构建了电力投资最优规模与边际产出的回归模型,并给出变量的处理方法。该模型函数表达式简洁,意义清晰,求解方便,具有可操作性。然后以我国1996-2013年的序列样本求解电力投资的最优规模,以及电源与电网投资的边际产出。实证结果显示:我国电力投资的最优规模为3.5%,高于实际规模。其中,电源投资的边际产出为1.23,电网投资的边际产出为1.35,因此我国电力投资规模与结构尚有进一步优化的空间。其次,根据电力投资绩效评价的意义、原则和要求,构建了包含4个一级指标、12个二级指标的电力投资绩效评价指标体系,该指标体系从社会、经济、环境3个方面对电力工业的发展水平进行了充分覆盖,因而可以较好地对电力投资的绩效进行评价。最后以电力投资绩效评价指标体系为标准,基于熵权TOPSIS绩效评价方法,对2013年我国7个按地理方位划分的区域和30个行政区域的电力投资绩效进行了综合评价。评价结果揭示了不同地区电力工业的优势环节和薄弱环节,反映了电力投资绩效的不平衡,从而为政府优化投资决策提供了参考。该方法概念通俗易懂,应用方便,计算过程清晰,各评价对象的赋权不依赖于主观判断,并且可以用简单的数学形式描述,因此具有很强的科学性与客观性。
[Abstract]:Electricity investment is an indispensable material foundation for the development of energy industry in a country. Since the reform and opening up, with the rapid development of economy and the rapid growth of electricity consumption, the total amount of electricity investment has been continuously expanding. However, the scale of investment is not the bigger the better. Because of the diminishing marginal output effect, there is a problem of optimal scale in power investment. In view of this, this paper analyzes whether the power investment in China has reached the optimal scale and how to evaluate the investment performance of different regions. In order to make reasonable investment arrangements, it is of great theoretical and practical significance for the scientific planning of power investment. First, in order to analyze the long-term trend of electricity consumption and national economy, The power consumption and GDP time series are divided into trend part and fluctuation part by HP filtering method. On the basis of this, the relationship between electricity consumption and economic growth is investigated with the help of impulse response function, and the one-way long-term causality between power consumption and economic growth is revealed. It shows that adequate power supply is an important guarantee for economic growth. Based on the theory of fiscal expenditure growth effect, the regression model of optimal scale of power investment and marginal output is established. The function expression of the model is simple, the meaning is clear, the solution is convenient and operable. Then, the optimal scale of power investment is solved with the series samples from 1996 to 2013. The empirical results show that the optimal scale of power investment in China is 3.5, which is higher than the actual scale. The marginal output of power investment is 1.23 and the marginal output of grid investment is 1.35. Therefore, there is still room for further optimization of the scale and structure of power investment in China. Secondly, according to the significance, principles and requirements of power investment performance evaluation, This paper constructs an index system of power investment performance evaluation, which includes 4 first class indexes and 12 second class indexes. The index system covers the development level of power industry from three aspects: society, economy and environment. Therefore, the performance of power investment can be evaluated better. Finally, based on entropy weight TOPSIS performance evaluation method, the performance evaluation index system of power investment is taken as the standard. The performance of power investment in 7 geographical regions and 30 administrative regions in China in 2013 is comprehensively evaluated. The evaluation results reveal the advantages and disadvantages of the power industry in different regions. It reflects the imbalance of power investment performance, which provides a reference for the government to optimize investment decision. This method is easy to understand, easy to use, clear calculation process, and the weight of each evaluation object does not depend on subjective judgment. And can be described in simple mathematical form, so it has a strong scientific and objective.
【学位授予单位】：上海电力学院
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F426.61

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