14 / 2020-09-23 19:06:54
Identification of Potential Power Users Who Can Transfer Load to Valley Period Based on Association Rules Analysis
association rules analysis; load transfer; DSM; power load pattern; power user identification
Draft Rejected
Shengke Han / Xi'an Jiaotong University,School of electrical engineering
Xuan Feng / Xi'an Jiaotong University
Yanpeng Wang / Xi'an Jiaotong University
with the continuous improvement of smart grid informatization and digitization, power operators have accumulated a large number of power user data in actual operation. Through data mining on power user data, the power users' power load pattern can be analyzed and reasonable power usage suggestions can be given. In this paper, the Kmeans++ clustering algorithm is used to classify the power users into the users who have realized and unrealized load shifts to valley period. At the same time, using the power data such as power consumption, energy consumption category and the business information disclosed by enterprises on the Internet, Apriori algorithm is used to mine the association rules of users who have realized the load valley period transfer, and through the analysis of these rules, the potential power users who can realize the transfer of electricity consumption to valley period are identified. The practical application shows that this method realizes the above-mentioned user identification. 
Important Date
  • Conference Date

    Nov 02

    2020

    to

    Nov 04

    2020

  • Oct 27 2020

    Draft paper submission deadline

  • Nov 03 2020

    Contribution Submission Deadline

  • Nov 04 2020

    Registration deadline

  • Nov 17 2020

    Final Paper Deadline

Sponsored By
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
Organized By
Huazhong University of Science and Technology
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