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Electrical Data Recovery with Weather Information via Collective Matrix Factorization

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International Conference on Applications and Techniques in Cyber Security and Intelligence ATCI 2018 (ATCI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 842))

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Abstract

It is an important application in power systems to monitor load and calculate the electricity cost using data collected from smart meters. As the development of smart grid and energy internet, this leads to a significant increase in the amount of data transmitted in real time. Due to the mismatch with communication networks that were not designed to carry high-speed and real time data, data losses and data quality degradation may happen constantly. The electrical data is incomplete. Therefore, the electrical data recovery is an important issue. The electrical data is produced by the action and feelings of the human being which has strong season feature and depends on the weather. We take the weather information as aid to recover electrical data via collective matrix factorization. We perform extensive simulations based on the real power system and weather data sets and the simulation results validate the efficiency and efficacy of the proposed scheme compared without weather information.

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Author information

Authors and Affiliations

  1. State Grid Gansu Electric Power Corporation, Lanzhou, 730000, China

    Xushan Han, Huafeng Zhang & Yanwen He

  2. Information Communication Corporation, State Grid Gansu Electric Power Corporation, Lanzhou, 730050, China

    Qian Dang

  3. Jinchang Power Company, State Grid Gansu Electric Power Corporation, Lanzhou, 737100, China

    Lin Gao

Authors
  1. Xushan Han
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  2. Qian Dang
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  3. Huafeng Zhang
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  4. Yanwen He
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  5. Lin Gao
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Corresponding author

Correspondence to Qian Dang .

Editor information

Editors and Affiliations

  1. Faculty of Science, Engineering and Built Environment, Deakin University Geelong, Geelong, VIC, Australia

    Jemal Abawajy

  2. Department of Information Systems and Cyber Security, The University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  3. School of Computing and Mathematics, Charles Sturt University, Albury, NSW, Australia

    Rafiqul Islam

  4. Tsinghua University, Beijing Shi, China

    Zheng Xu

  5. School of Computer Science, University of Oklahoma, Norman, OK, USA

    Mohammed Atiquzzaman

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Han, X., Dang, Q., Zhang, H., He, Y., Gao, L. (2019). Electrical Data Recovery with Weather Information via Collective Matrix Factorization. In: Abawajy, J., Choo, KK., Islam, R., Xu, Z., Atiquzzaman, M. (eds) International Conference on Applications and Techniques in Cyber Security and Intelligence ATCI 2018. ATCI 2018. Advances in Intelligent Systems and Computing, vol 842. Springer, Cham. https://doi.org/10.1007/978-3-319-98776-7_40

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