Time Series Cluster Analysis on Electricity Consumption of North Hebei Province in China

  • Luhua Zhang
  • Miner Liu
  • Jingwen Xia
  • Kun GuoEmail author
  • Jun Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10862)


In recent years, China has vigorously promoted the building of ecological civilization and regarded green low-carbon development as one of the important directions and tasks for industrial transformation and upgrading. It calls for accelerating industrial energy conservation and consumption reduction, accelerating the implementation of cleaner production, accelerating the use of renewable resources, promoting industrial savings and cleanliness, advancing changes in low-carbon and high-efficiency production, and promoting industrial restructuring and upgrading. A series of measures have had a negative impact on the scale of industrial production in the region, thereby affecting the electricity consumption here. Based on the electricity consumption data of 31 counties in northern Hebei, this paper uses the time series clustering method to cluster the electricity consumption of 31 counties in Hebei Province. The results show that the consumption of electricity in different counties is different. The macro-control policies have different impacts on different types of counties.


Electricity consumption Time series clustering Wavelet analysis 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Luhua Zhang
    • 1
  • Miner Liu
    • 2
  • Jingwen Xia
    • 2
  • Kun Guo
    • 3
    • 4
    • 5
    Email author
  • Jun Wang
    • 1
  1. 1.Jibei Electric Power Company Limited Metering CentreBeijingChina
  2. 2.China University of Political Science and LawBeijingChina
  3. 3.School of Economics and ManagementUniversity of Chinese Academy of SciencesBeijingChina
  4. 4.Research Centre on Fictitious Economy and Data ScienceUCASBeijingChina
  5. 5.CAS Key Laboratory of Big Data Mining and Knowledge ManagementBeijingChina

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