陕西省终端能源消费中电力消费发展预测研究

发布时间：2018-01-06 19:29

本文关键词：陕西省终端能源消费中电力消费发展预测研究　出处：《华北电力大学》2015年硕士论文　论文类型：学位论文

【摘要】：终端能源消费是提升能源效率的重要一环。陕西省是我国能源资源富集区之一,但其电力消费水平还未达到全国平均水平。因此,有必要对陕西省终端能源消费中的电力消费情况进行深入分析研究,为能源结构的优化和可持续发展提供理论依据。本文首先对电力消费的影响因素进行了探讨,将其分为生产用电和生活用电两个方面进行分析。利用LMDI法将生产用电分解为经济效应、结构效应和强度效应,结果表明,经济效应是电力终端消费量增长的关键因素,强度效应是抑制其增长的重要因素,结构效应的增长作用不明显。利用灰色关联度模型对生活用电的影响因素与生活用电量进行关联度分析,得到与生活用电量的灰色关联度由大到小的影响因素依次为：农村居民家庭人均纯收入、城镇居民人均可支配收入、城镇人口比例、平均每户人数和人口。利用MIV-GRNN模型对所选取的所有因素进行敏感度分析,结果表明,对电力消费量和电力消费占比影响较大的因素有人口、平均每户人数、第二产业GDP占比、第三产业GDP占比。根据数据历史趋势和影响因素对未来五年的电力消费量和电力消费占比进行预测。在传统的变权重组合模型加入新的限制条件,并结合多项式回归模型、GM(1,1)模型、多元线性回归模型和GRNN模型,形成了改进变权重组合预测模型。经拟合验证,改进变权重组合模型减小了误差,具有参考意义。基于该模型的预测结果表明,虽然未来五年电力消费量和电力消费占比都呈现上升趋势,但仍未达到满意水平为提高电力在终端能源消费中的比重,对电力消费增长潜力从交通电气化、工农业生产和电器普及推广三个角度进行分析,对已实行的电能替代措施和面临的挑战进行分析介绍,并为开拓陕西省电力消费市场提出相关建议。
[Abstract]:End energy consumption is an important part of improving energy efficiency. Shaanxi Province is one of the rich areas of energy resources in China, but its power consumption level has not reached the national average level. It is necessary to analyze and study the electric power consumption in the terminal energy consumption of Shaanxi Province. For the optimization of energy structure and sustainable development to provide a theoretical basis. Firstly, this paper discusses the influence factors of electricity consumption. It can be divided into two aspects: production power and daily electricity. The LMDI method is used to decompose the production power into economic effect, structural effect and intensity effect. The results show that the power consumption can be divided into three parts: economic effect, structural effect and intensity effect. Economic effect is the key factor of power terminal consumption growth, and intensity effect is an important factor to restrain its growth. The growth effect of structural effect is not obvious. The grey correlation model is used to analyze the influence factors of household electricity consumption and the living electricity consumption. The grey correlation degree between the power consumption and the rural households per capita net income, urban residents per capita disposable income, the proportion of urban population is the order of influencing factors from large to small. 3. The main factors are: rural households per capita net income, urban residents per capita disposable income, urban population ratio. The MIV-GRNN model is used to analyze the sensitivity of all the selected factors. The results show that the population has a great influence on the power consumption and the proportion of electricity consumption. Average household size, secondary industry GDP ratio. According to the historical trend and influencing factors of the tertiary industry, the paper predicts the power consumption and the power consumption ratio in the next five years. The new restriction condition is added to the traditional variable weight combination model. Combined with polynomial regression model, multivariate linear regression model and GRNN model, an improved variable weight combination prediction model was formed. The improved variable-weight combination model reduces the error and has reference significance. The prediction results based on the model show that although the power consumption and power consumption ratio will increase in the next five years. However, in order to improve the proportion of electricity in the end energy consumption, the potential of power consumption growth is analyzed from three aspects: traffic electrification, industrial and agricultural production and popularization of electrical appliances. This paper analyzes and introduces the electric power substitution measures and the challenges faced by them, and puts forward some suggestions for developing the electric power consumption market in Shaanxi Province.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F426.61

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