A Method of NTL Detection in Smart Electricity Consumption

Jie Liu; Nian Liu

doi:10.4028/www.scientific.net/AMM.521.471

Paper Titles

Study on Control Strategy of Microgrid in Islanded Operation Mode
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Reliability Evaluation of Main Electrical Connection for the Smart Substation with DCB
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Smart Devices with Plug and Play Technique for Smart Grid Dispatch and Control System
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A Study of Optimal Capacity Configuration with Multi-Objective for Islanded Micro-Grid
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A Method of NTL Detection in Smart Electricity Consumption
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Impacts of Emission Trading on Optimal Bidding Strategies of Generation Companies in Day-Ahead Electricity Markets
p.476

Reliability Management of the Power System in China: Present Status and Future Challenges
p.480

The Temporal-Spatial Evolution of the Southern Corridor of West-to-East Power Transmission Project in China
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The Plant-Level Optimal Load Distribution Based on Economy and Environmental Protection
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 521A Method of NTL Detection in Smart Electricity...

A Method of NTL Detection in Smart Electricity Consumption

Abstract:

Nontechnical loss has been a significant factor to influence the profits of electric power companies. In the smart electricity consumption environment, the population of smart metering is helpful to collect the load data directly and promptly. A method of nontechnical loss detection, including offline parameter optimization and online detection, is proposed in this paper. With the updating of history data, the detection accuracy gets higher till the optimal point. Extreme learning machine is adopted to detect the nontechnical loss and genetic algorithm is used to find out the optimal parameters for each user. Finally, in the case study the real-time detection system assesses the classification accuracy and fault detection accuracy, verifying the stability of this method and advantages in reducing the cost.

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Periodical:

Applied Mechanics and Materials (Volume 521)

Pages:

471-475

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.521.471

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Online since:

February 2014

Authors:

Jie Liu*, Nian Liu

Keywords:

Nontechnical Loss, Online Detection, Parameter Optimization

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* - Corresponding Author

References

[1] Information on http: /news. xinhuanet. com/fortune/2006-10/28/content_5261038. htm. In Chinese.

Google Scholar

[2] J. Nagi, K. Yap, S. Tiong, S. Ahmed, and A. Mohammad. IEEE TENCON Region 10 Conf in Proc. 2008, p.1–6.

Google Scholar

[3] C. C. O. Ramos, A. N. Souza, J. P. Papa, and A. X. Falcão. A new approach for nontechnical losses detection based on optimum-path forest, IEEE Trans. Power Syst. 2011, vol. 26, no. 1, p.181–189.

DOI: 10.1109/tpwrs.2010.2051823

Google Scholar

[4] Qingxin Zhang, Kaituo Shi, Nian Liu, et al. 2012 China International Conference on Electricity Distribution (CICED). IEEE, 2012: 1-4.

DOI: 10.1109/ciced.2012.6508590

Google Scholar

[5] Huang G B, Zhu Q Y, Siew C K. Neuron computing, 2006, 70(1): 489-501.

Google Scholar

[6] Nizar A H, Dong Z Y, Wang Y. IEEE Transactions on Power Systems, 2008, 23(3): 946-955.

Google Scholar