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Securing the Smart Grid: A Machine Learning Approach

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Smart Grids

Part of the book series: Green Energy and Technology ((GREEN))

Abstract

The demand of electricity is increasing in parallel with the growth of the world population. The existing power grid, which is over 100 years old, is facing many challenges to facilitate the continuous flow of electricity from large power plants to the consumers. To overcome these challenges, the power industry has warmly accepted the new concept smart grid which has been initiated by the engineers. This movement will be more beneficial and sustainable to the extent if we can offer a secure smart grid. Machine learning, representing a comparatively new era of Information Technology, can make smart grid really secure. This chapter provides an overview of the smart grid and a practical demonstration of maintaining the security of smart grid by incorporating machine learning.

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Author information

Authors and Affiliations

  1. Central Queensland University, Rockhampton, QLD, 4702, Australia

    A. B. M. Shawkat Ali, Salahuddin Azad & Tanzim Khorshed

Authors
  1. A. B. M. Shawkat Ali
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  2. Salahuddin Azad
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  3. Tanzim Khorshed
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Corresponding author

Correspondence to A. B. M. Shawkat Ali .

Editor information

Editors and Affiliations

  1. , School of Information and Communication, CQ University, Bruce Highway, North Rockhampton, 4702, Queensland, Australia

    A B M Shawkat Ali

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© 2013 Springer-Verlag London

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Ali, A.B.M.S., Azad, S., Khorshed, T. (2013). Securing the Smart Grid: A Machine Learning Approach. In: Ali, A. (eds) Smart Grids. Green Energy and Technology. Springer, London. https://doi.org/10.1007/978-1-4471-5210-1_8

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  • DOI: https://doi.org/10.1007/978-1-4471-5210-1_8

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5209-5

  • Online ISBN: 978-1-4471-5210-1

  • eBook Packages: EnergyEnergy (R0)

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