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Mining-Based Device Control for Home Automation

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Artificial Intelligence and Evolutionary Computations in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 394))

Abstract

Dynamic demand response (DR) and demand side management (DSM) are the important functions that allow the customer to reduce the peak load demand. This results in the reduced energy consumption cost and better user experience. In DSM, the customers can make informed decisions regarding their energy consumption, and it helps to reshape their load profile. In this chapter, we proposed an integrated solution to predict the electricity demand and made a load shift in a locality at a given day. The system presented in this chapter expands the DR to residential loads by scheduling and controlling the appliance. The electricity demand in the home is forecasted by a decision support system, which helps the user to save energy by recommending optimal run time schedule for appliances, given user constraints and TOU pricing from the utility. The schedule is communicated to the appliance and executed by the appliance control interface.

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Authors and Affiliations

  1. Department of ECE, Mohamed Sathak A.J College of Engineering, Chennai, 603103, India

    C Ganesh Kumar & S Januja Josephine

  2. Department of ECE, SSN College of Engineering, Chennai, 603110, India

    Premanand V. Chandramani

Authors
  1. C Ganesh Kumar
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  2. S Januja Josephine
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  3. Premanand V. Chandramani
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Corresponding author

Correspondence to C Ganesh Kumar .

Editor information

Editors and Affiliations

  1. Electrical and Electronics Engineer, SRM Engineering College, Kattankulathur, Tamil Nadu, India

    Subhransu Sekhar Dash

  2. Electrical & Electronics Engineering, Velammal Engineering College, Chennai, Tamil Nadu, India

    M. Arun Bhaskar

  3. Dept Electrical & Electronics Engg, IIT Delhi, New Delhi, India

    Bijaya Ketan Panigrahi

  4. Indian Statistical Institute, Kolkata, India

    Swagatam Das

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© 2016 Springer India

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Ganesh Kumar, C., Januja Josephine, S., Chandramani, P.V. (2016). Mining-Based Device Control for Home Automation. In: Dash, S., Bhaskar, M., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 394. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2656-7_97

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  • DOI: https://doi.org/10.1007/978-81-322-2656-7_97

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2654-3

  • Online ISBN: 978-81-322-2656-7

  • eBook Packages: EngineeringEngineering (R0)

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