Behavior-Based Detection of Abnormal Power Consumption for Power Saving

Chiao Ching Huang; Yi Ting Tsao; Jane Yung Jen Hsu

doi:10.4028/www.scientific.net/AMM.291-294.674

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 291-294Behavior-Based Detection of Abnormal Power...

Behavior-Based Detection of Abnormal Power Consumption for Power Saving

Abstract:

Abnormalities are caused by incorrect or inappropriate behaviors or appliance malfunctions. They may lead to electricity waste and safety hazards. This paper describes a novel appliance management system for detecting abnormal power consumption in convenience stores based on power meters. Our system detects abnormal power consumption through historical behavior models. Generalized extreme studentized deviate (GESD) and regression methods are applied to build behavior models. The behavior based abnormal detection methods can assist in preventing these waste and safety problems and improve the appliance management to achieve power saving.

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Periodical:

Applied Mechanics and Materials (Volumes 291-294)

Pages:

674-678

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.291-294.674

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Online since:

February 2013

Authors:

Chiao Ching Huang, Yi Ting Tsao, Jane Yung Jen Hsu

Keywords:

Abnormal Detection, Appliance Management, Power Consumption, Power Saving, Regression

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References

[1] V. Barnett, T. Lewis, Outliers in Statistical Data, third ed., (1994).

Google Scholar

[2] M. Ito, R. Uda, S. Ichimura, K. Tago, T. Hoshi, and Y. Matsushita, A Method of Appliance Detection Based on Features of Power Waveform, Proceedings of the International Symposium on Applications and the Internet (2004).

DOI: 10.1109/saint.2004.1266131

Google Scholar

[3] S. Lee, G. Lin, W. Jih, and J. Y. Hsu, Appliance Recognition and Unattended Appliance Detection for Energy Saving, Proceedings of the AAAI Workshop on Plan, Activity, and Intent Recognition (2010).

Google Scholar

[4] X. Li, C. P. Bowers, and T. Schnier, Classification of Energy Consumption in Buildings With Outlier Detection, IEEE Transactions on Industrial Electronics (2010) 3639-3644.

DOI: 10.1109/tie.2009.2027926

Google Scholar

[5] D. Liu, Q. Chen, K. Mori, and Y. Kida, A Method for Detecting Abnormal Electricity Energy Consumption in Buildings, Journal Of Computational Information Systems (2010).

Google Scholar

[6] B. Rosner, Percentage Points for a Generalized ESD Many-Outlier Procedure, Technometrics (1983) 165-172.

DOI: 10.1080/00401706.1983.10487848

Google Scholar

[7] T. Saitoh, Y. Aota, T. Osaki, R. Konishi, and K. Sugahara, Current Sensor based Non-intrusive Appliance Recognition for Intelligent Outlet, Proceedings of the International Technical Conference on Circuits/Systems Computers and Communications (2008).

Google Scholar

[8] J. E. Seem, Using Intelligent Data Analysis to Detect Abnormal Energy Consumption in Buildings, Energy and Buildings (2007) 52-58.

DOI: 10.1016/j.enbuild.2006.03.033

Google Scholar