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

  • A. Jayanth BalajiEmail author
  • D. S. Harish Ram
  • Binoy B. Nair
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 466)


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.


Automated metering infrastructure Smart grid Load forecasting Distribution side management Soft computing Artificial intelligence 


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Authors and Affiliations

  • A. Jayanth Balaji
    • 1
    Email author
  • D. S. Harish Ram
    • 1
  • Binoy B. Nair
    • 1
  1. 1.Computing, Hardware Systems and Architectures Group, Department of Electronics and Communication Engineering, Amrita School of EngineeringAmrita Vishwa Vidyapeetham UniversityCoimbatoreIndia

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