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Communication Performance Assessment for Advanced Metering Infrastructure

Author

Listed:
  • Jen-Hao Teng

    (Departmental of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan)

  • Chia-Wei Chao

    (Departmental of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan)

  • Bin-Han Liu

    (Departmental of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan)

  • Wei-Hao Huang

    (Departmental of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan)

  • Jih-Ching Chiu

    (Departmental of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan)

Abstract

Advanced Metering Infrastructure (AMI), the foundation of smart grids, can be used to provide numerous intelligent power applications and services based on the data acquired from AMI. Effective and efficient communication performance between widely-spread smart meters and Data Concentrator Units (DCUs) is one of the most important issues for the successful deployment and operation of AMI and needs to be further investigated. This paper proposes an effective Communication Performance Index (CPI) to assess and supervise the communication performance of each smart meter. Some communication quality measurements that can be easily acquired from a smart meter such as reading success rate and response time are used to design the proposed CPI. Fuzzy logic is adopted to combine these measurements to calculate the proposed CPI. The CPIs for communication paths, DCUs and whole AMI can then be derived from meter CPIs. Simulation and experimental results for small-scale AMIs demonstrate the validity of the proposed CPI. Through the calculated CPIs, the communication performance and stability for AMI can be effectively assessed and supervised.

Suggested Citation

  • Jen-Hao Teng & Chia-Wei Chao & Bin-Han Liu & Wei-Hao Huang & Jih-Ching Chiu, 2018. "Communication Performance Assessment for Advanced Metering Infrastructure," Energies, MDPI, vol. 12(1), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:12:y:2018:i:1:p:88-:d:193711
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    References listed on IDEAS

    as
    1. Kai Ma & Xuemei Liu & Jie Yang & Zhixin Liu & Yazhou Yuan, 2017. "Optimal Power Allocation for a Relaying-Based Cognitive Radio Network in a Smart Grid," Energies, MDPI, vol. 10(7), pages 1-17, July.
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