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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 11
3348-3352,3357

Fuzzy multi-granularity-based abnormal power consumption detection method

Li Qilin1
Yan Ping1
Chen Baiyang2
Yuan Zhong2
Peng Dezhong2
Liu Yizhi2
1. Metering Center of State Grid Sichuan Electric Power Corporation, Chengdu 610045, China
2. College of Computer Science, Sichuan University, Chengdu 610065, China
DOI: 10.19734/j.issn.1001-3695.2023.05.0192

Abstract

Abnormal power consumption detection aims to identify and locate customers in the power system that deviate significantly from regular power consumption behavior. Existing supervised detection methods based on machine learning or deep learning generally require a large amount of manually labeled data, and require transformation for discrete data, thus leading to the loss of important information. FRS theory provides an effective tool for tackling discrete data. Therefore, FRS can be directly applied to the knowledge classification of heterogeneous information that includes continuous and discrete data. This paper proposed an unsupervised anomaly detection method with multi-granularity fuzzy relative differences based on FRS theory, and applied it to detect anomalous power consumption users in smart grid. Specifically, it first used information entropy of fuzzy approximation space to measure the importance of attributes for knowledge classification, then constructed a fuzzy granule sequence based on the attribute set's importance, and defined the fuzzy relative difference of the samples on top of this sequence. Finally, it constructed the anomaly detection method based on multi-granularity fuzzy relative differences and conducted evaluation on public datasets. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm. The code and data for the experiments are publicly available online.

Foundation Support

国网四川省电力公司科技项目(521997230015)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.05.0192
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 11
Section: System Development & Application
Pages: 3348-3352,3357
Serial Number: 1001-3695(2023)11-022-3348-05

Publish History

[2023-07-12] Accepted Paper
[2023-11-05] Printed Article

Cite This Article

李琪林, 严平, 陈白杨, 等. 一种模糊多粒度用电行为异常检测方法 [J]. 计算机应用研究, 2023, 40 (11): 3348-3352,3357. (Li Qilin, Yan Ping, Chen Baiyang, et al. Fuzzy multi-granularity-based abnormal power consumption detection method [J]. Application Research of Computers, 2023, 40 (11): 3348-3352,3357. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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