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A Comprehensive Analysis Method for Optimal Configuration of Smart Meter Data Collector Based on PSO-BP Algorithm

Published: 13 April 2022 Publication History

Abstract

Aiming at the current electric power industry's problems related to the unreasonable configuration of smart meter data collectors and the smart meter measurement technology, this paper proposes a comprehensive analysis method for the optimal configuration of smart meter data collectors based on the PSO-BP neural network prediction model. Through the analysis of historical data in the station area, PSO is used to optimize the index. The database is established to import the BP neural network algorithm and training, and then the prediction of the station area to be configured with the data collector is completed. The experimental case proves that the above steps can reasonably configure the collector in the station area and optimize the data collection of the smart meter. While realizing convenient and effective data transmission, it also guarantees a certain degree of economy.

References

[1]
W. Luan, J. Peng, M. Maras, J. Lo and B. Harapnuk, "Smart Meter Data Analytics for Distribution Network Connectivity Verification," in IEEE Transactions on Smart Grid, vol. 6, no. 4, pp. 1964-1971, July 2015.
[2]
"IEEE Vision for Smart Grid Controls: 2030 and Beyond Reference Model," in IEEE Vision for Smart Grid Control: 2030 and Beyond Reference Model, vol., no., pp.1-10, 12 Sept. 2013.
[3]
W. Luan, D. Sharp and S. LaRoy, "Data traffic analysis of utility smart metering network," 2013 IEEE Power & Energy Society General Meeting, 2013, pp. 1-4.
[4]
N. Schaefer, T. Degner, T. Keil and J. Jaeger, "Coaction of protection and distribution management systems in case of islanded distribution networks," 2008 China International Conference on Electricity Distribution, 2008, pp. 1-4.
[5]
M. K. Deb Barma and S. Das, "Data gathering mechanism of mobile data collector in wireless sensor network," 2016 International Conference on Internet of Things and Applications (IOTA), 2016, pp. 401-405.
[6]
N. Rokbani, M. Slim and A. M. Alimi, "The Beta distributed PSO, β-PSO, with application to Inverse Kinematics," 2021 National Computing Colleges Conference (NCCC), 2021, pp. 1-6.
[7]
Z. Caihong, W. Zengyuan and L. Chang, "A Study on Quality Prediction for Smart Manufacturing Based on the Optimized BP-AdaBoost Model," 2019 IEEE International Conference on Smart Manufacturing, Industrial & Logistics Engineering (SMILE), 2019, pp. 1-3.
[8]
Li Yiquan, Jiao Shaolin, Zeng Genghui, Liu Wei, Tu Qingrui, Tan Qian, Cong Mingyi, Zhan Qingcai.A new method of complex fault deduction for power grid based on Bayesian network[J].Power System Protection and Control,2020,48( 04):57-63.
[9]
Zhang Enliang. Research on Road Traffic Safety Prediction Based on BP Neural Network[D]. Beijing Jiaotong University, 2007.
[10]
Shi Hongtao,Yang Jingling,Ding Maosheng,Wang Jinmei.Short-term wind power prediction method based on wavelet-BP neural network[J].Automation of Electric Power Systems,2011,35(16):44-48.
[11]
Wang Xingang,Wu Ying,Zhang Yin.On-line monitoring method of smart electric energy meter based on data mining[J].Electrical Measurement and Instrumentation,2016,53(13):65-69.
[12]
J Liu Xingyu. Research on non-technical loss detection method of distribution network based on deep learning[D].University of Electronic Science and Technology of China,2021.

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ICITEE '21: Proceedings of the 4th International Conference on Information Technologies and Electrical Engineering
October 2021
477 pages
ISBN:9781450386494
DOI:10.1145/3513142
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 April 2022

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Author Tags

  1. BP
  2. Smart meter
  3. data collection
  4. particle swarm optimization

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  • Research-article
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  • Refereed limited

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  • State Grid Hunan Electric Power Company Limited

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ICITEE2021

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