中国电力 ›› 2017, Vol. 50 ›› Issue (6): 172-176.DOI: 10.11930/j.issn.1004-9649.2017.06.172.05

• 技术经济 • 上一篇    下一篇

基于智慧能源视角影响北京市电力需求的灰色关联分析

迟远英1, 2, 刘蕾1, 齐霁1, 王新迎3   

  1. 1. 北京工业大学 经济与管理学院 北京现代制造业发展研究基地,北京 100124;
    2. 北京工业大学 北京未来网络科技高精尖创新中心,北京 100124;
    3. 中国电力科学研究院,北京 100192
  • 收稿日期:2016-12-26 出版日期:2017-06-20 发布日期:2017-07-12
  • 作者简介:迟远英(1968-),女,山东烟台人,教授,从事低碳经济及新能源、能源产业经济研究。E-mail: goodcyy@bjut.edu.cn
  • 基金资助:
    北京市教育委员会社科计划重点资助项目(SZ201510005002) 科技部重点研发计划子课题资助项目(2016YFB0901200) 国家自然科学基金重大研究计划重点项目(91646201) 国家基金重大研究计划培育项目(91546111)

Grey Correlation Analysis of Power Demand in Beijing Based on Smarter Energy

CHI Yuanying1, 2, LIU Lei1, Qi Ji1, WANG Xinying3   

  1. 1. Research Base of Beijing Modern Manufacturing Development, College of Economics and Management, Beijing University of Technology, Beijing 100124, China;
    2. Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing 100124 China;
    3. China Electric Power Research Institute, Beijing 100192, China
  • Received:2016-12-26 Online:2017-06-20 Published:2017-07-12
  • Supported by:
    ; This work is supported by Beijing Municipal Education Commission key program of social science program (No. JD011012201501).

摘要: 电力需求变化受各种因素的影响,对于智慧能源建设需要深入分析各种因素的未来趋势及对用电需求的影响。运用灰色关联方法对影响北京市用电需求量的宏观因素进行了分析,选取可以反映北京市经济、社会、科学、文化水平的指标,利用2002—2014年的年度数据计算影响因素与全社会用电量之间的绝对关联度、相对关联以及综合关联度,并进行排序分析。结果表明:相比经济、社会、文化因素,科技因素与社会用电需求的关系最为显著。

关键词: 智慧能源, 电力需求量, 灰色关联度, 北京市

Abstract: With increasingly prominent of energy and environmental problems, energy reform is gradually advancing. Electric demand analysis is an important part in energy reform. There are various factors has influence on power demand change. It is very important to analysis future trends and influence of those factors. Grey correlation analysis is used to analyze main factors related to power demand in Beijing. From collected data in years 2002-2014, several indexes based on economic, social, scientific and cultural levelare selected to calculate absolute, relative and comprehensive correlation degree among impact factors and power consumption in whole society. The results show that compared with economic, social and cultural factors, science and technology has the most significant impact on power consumption.

Key words: smarter energy, electricity demand, grey correlation analysis, Beijing

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