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Modeling of Consumption Data for Forecasting in Automated Metering Infrastructure (AMI) Systems

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Automation Control Theory Perspectives in Intelligent Systems (CSOC 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 466))

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Abstract

The Smart Grid is a new paradigm that aims at improving the efficiency, reliability and economy of the power grid by integrating ICT infrastructure into the legacy grid networks at the generation, transmission and distribution levels. Automatic Metering Infrastructure (AMI) systems comprise the entire gamut of resources from smart meters to heterogeneous communication networks that facilitate two-way dissemination of energy consumption information and commands between the utilities and consumers. AMI is integral to the implementation of smart grid distribution services such as Demand Response (DR) and Distribution Automation (DA). The reliability of these services is heavily dependent on the integrity of the AMI data. This paper investigates the modeling of AMI data using machine learning approaches with the objective of load forecasting of individual consumers. The model can also be extended for detection of anomalies in consumption patterns introduced by false data injection attacks, electrical events and unauthorized load additions or usage modes.

The CER Electricity Dataset used in this work was provided by Irish Social Science Data Archive (ISSDA).

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Authors and Affiliations

  1. Computing, Hardware Systems and Architectures Group, Department of Electronics and Communication Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham University, Coimbatore, India

    A. Jayanth Balaji, D. S. Harish Ram & Binoy B. Nair

Authors
  1. A. Jayanth Balaji
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  2. D. S. Harish Ram
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  3. Binoy B. Nair
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Corresponding author

Correspondence to A. Jayanth Balaji .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Roman Senkerik

  3. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zuzana Kominkova Oplatkova

  4. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Petr Silhavy

  5. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zdenka Prokopova

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© 2016 Springer International Publishing Switzerland

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Jayanth Balaji, A., Harish Ram, D.S., Nair, B.B. (2016). Modeling of Consumption Data for Forecasting in Automated Metering Infrastructure (AMI) Systems. In: Silhavy, R., Senkerik, R., Oplatkova, Z.K., Silhavy, P., Prokopova, Z. (eds) Automation Control Theory Perspectives in Intelligent Systems. CSOC 2016. Advances in Intelligent Systems and Computing, vol 466. Springer, Cham. https://doi.org/10.1007/978-3-319-33389-2_16

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  • DOI: https://doi.org/10.1007/978-3-319-33389-2_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33387-8

  • Online ISBN: 978-3-319-33389-2

  • eBook Packages: EngineeringEngineering (R0)

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