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A method of electricity consumption behaviour clustering and pricing packages based on data mining

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DOI: 10.23977/isspj.2020.51004 | Downloads: 15 | Views: 930

Author(s)

Baoyi Wang 1, Yang Fan 1, Shaomin Zhang 1

Affiliation(s)

1 School of Control and Computer Engineering, North China Electric Power University, China

Corresponding Author

Baoyi Wang

ABSTRACT

In this paper, under the background of the reform of electricity sales side, a method of electricity consumption behaviour clustering and pricing packages based on data mining is proposed. Firstly, a distributed clustering framework combining DTW k-medoids algorithm and CFSFDP algorithm is proposed. Secondly, typical load curves of local data are extracted under the framework to construct local model. Then, quadratic clustering analysis is carried out for the local model results, and the global typical load curve is obtained to construct the global model. Finally, recommend the most suitable electricity sales plan to the target users. The experimental result shows that the subdivision of electricity consumption behavior can realize the effective personalized electricity package recommendation service for users and improve the power supply service quality for power companies and provide technical support for improving the operation efficiency.

KEYWORDS

smart grid, distributed clustering ,pricing packages recommendation

CITE THIS PAPER

Baoyi Wang, Yang Fan and Shaomin Zhang. A method of electricity consumption behaviour clustering and pricing packages based on data mining. Information Systems and Signal Processing Journal (2020) 5: 18-23. DOI: http://dx.doi.org/10.23977/isspj.2020.51004.

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