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工业化、城镇化进程中电力需求分析及预测 被引量:13

Analysis and Forecasting of Power Demand in Industrialization,Urbanization Process
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摘要 随着工业化、城镇化进程的不断加快,我国电力需求量将持续上升。电力的充足供应是我国经济稳步发展的重要保证,故合理准确的对电力需求进行分析及预测具有重要的现实意义。基于此,分析我国电力需求现状,利用通径分析筛选电力消费需求的核心驱动因素。在模型选择的基础上,基于单变量(ETS、ARIMA模型)和多变量(情景分析)两个维度进行电力需求量分析及预测。结果表明:GDP每提高1%使得电力需求量提高0.5249%;工业化水平每提高1%使得电力需求量提高2.2146%,城镇化水平每提高1%使电力需求量相应提高1.0076%。"十二五"末中国电力消费需求量将近61425.96KW/h,2020年中国电力消费需求将近81410.10KW/h。 With the development of the industrialization ,the urbanization process is accelerating .China’ s power demand will continue to rise .The power supply is an important guarantee for the steady development of our econ-omy.Therefore, a reasonable and accurate analysis of electricity demand and forecast is of important practical significance .This paper uses path analysis for screening the core of the electric power consumption demand based on this analysis of the current situation of China ’ s power demand .We analyze and forecast power demand based on single variables(ETS, ARIMA)and multivariate(scenario analysis)two dimensions based on model selection . The results show that GDP for every 1%increase in the electricity demand in 0 .5249%;the level of industriali-zation for every 1% increase in power demand has increased by 2.2146%, the level of urbanization for every 1%increase in power demand has increased by 1 .0076%.At the end of “Twelfth Five-Year Plan”, the con-sumption capacity of Chinese electric power reaches nearly 61425.96KW/h.By 2020,China electric power con-sumption will reach nearly 81410.10KW/h.
出处 《运筹与管理》 CSSCI CSCD 北大核心 2015年第1期164-172,共9页 Operations Research and Management Science
基金 国家自然科学基金资助项目(71103115) 中国博士后科学基金面上资助项目(2012M510580) 陕西省软科学研究计划项目(2012KRM95) 大学生创新创业训练计划项目(201210781026)
关键词 预测科学 ETS ARIMA 通径分析 电力需求 scientific forecasting ETS ARIMA path analysis power demand
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  • 1Kraft J, Kraft A. Relationship between energy and GNP[J]. Journal of Energy and Development, 1978, (3) : 401-403.
  • 2Julian Silk I, Frederick Joutz L. Short and long-run elasticities in US residential elect ricity demand: a cointegration approach [J]. Energy Economics, 1997, 19(4) : 493-513.
  • 3Thoma M. Electrical energy usage over the business cycle[ J]. Energy Economics, 2004, 26(3) : 463-485.
  • 4Steenhof P A, Fulton W. Factors affecting electricity generation in China: current situation and prospects [ J ]. Technological Forecasting and Social Change, 2007, 74(5) : 663-681.
  • 5林伯强.电力消费与中国经济增长:基于生产函数的研究[J].管理世界,2003,19(11):18-27. 被引量:428
  • 6王海鹏,田澎,靳萍.中国能源消费、经济增长间协整关系和因果关系的实证研究——以电力行业为例[J].生产力研究,2005(3):159-160. 被引量:67
  • 7朱忠烈,杨宗麟,程浩忠,顾洁,秦康平,林佳,陈银峰.节能减排背景下电力需求分析预测研究[J].华东电力,2009,37(5):703-707. 被引量:10
  • 8Yukun Bao, Tao Xiong, Zhongyi Hu. Multi-step-ahead [J]. Neurocomputing, 2013, (17) : 1-12.
  • 9Badfi MA, A1-Mutawa A, Davis D, Davis D. EDSSF: [J]. Energy, 1997, 22(6): 579-589.
  • 10time series prediction using multiple-output support vector regression a decision support system(DSS) for electricity peak-load forecasting Zachariadis T, Pashourtidou N. An empirical analysis of electricity consumption in Cyprus[ J]. Energy Economics, 2007, 29 (2) : 183-198.

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