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Static and Dynamic Networking of Smart Meters Based on the Characteristics of the Electricity Usage Information

Author

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  • Yaxin Huang

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China)

  • Yunlian Sun

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China)

  • Shimin Yi

    (Guangdong Power Grid Co., Ltd., Guangzhou 510620, China)

Abstract

The normal communication between smart meter and concentrator is a key factor influencing the normal function of users’ power consumption systems. To solve the communication failure of the smart meter caused by the signal conflict as well as the collected consecutive information abnormality from the same smart meter, according to the chain optimization index, the networking method of static and dynamic combination proposed in this paper is first used to picked out the optimal relay for a smart meter belonging to multiple relay communication ranges. Meanwhile, the communication with other secondary relays is closed to avoid signal conflict. Then the paper forms different combinations of collected data and these combinations are trained in the extreme learning machine (ELM) to find the characteristics value of power consumption information. Finally, in MATLAB simulation, if ELM detects the abnormal information, new communication path could be promptly found through dynamic adjustment of chain optimization weighted coefficient and the weighted coefficient of the number of the relayed smart meters. It solves the problem of consecutive information abnormality from the same smart meter and raises the reliability of smart meter’s communication, having a significantly meaning to guarantee the normal function of users’ power consumption system.

Suggested Citation

  • Yaxin Huang & Yunlian Sun & Shimin Yi, 2018. "Static and Dynamic Networking of Smart Meters Based on the Characteristics of the Electricity Usage Information," Energies, MDPI, vol. 11(6), pages 1-18, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1532-:d:152137
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    References listed on IDEAS

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    Cited by:

    1. Xavier Serrano-Guerrero & Guillermo Escrivá-Escrivá & Santiago Luna-Romero & Jean-Michel Clairand, 2020. "A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles," Energies, MDPI, vol. 13(5), pages 1-23, February.

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