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Application of Neural Networks to Automatic Load Frequency Control

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8298))

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Abstract

This paper is intended to present the benefits of the application of artificial neural network to automatic load frequency control. The power system model has been simulated and the conventional PI controller has been replaced by the artificial neural network controller wherein, we have trained the neural controller to behave as a PI controller. The strategy has been successfully tested for both a single area as well as multi area systems using MATLAB/SIMULINK. With the help of a neural controller we have been able to achieve a smaller transient dip as well as faster stabilization of frequency.

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Author information

Authors and Affiliations

  1. Dept. of Electrical and Electronics Engineering, SRM University, Chennai, India

    Soumyadeep Nag & Namitha Philip

Authors
  1. Soumyadeep Nag
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  2. Namitha Philip
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Editor information

Editors and Affiliations

  1. Electrical Engineering Dept, IIT Delhi, Hauz Khas, 110016, New Delhi, India

    Bijaya Ketan Panigrahi

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, 700108, Kolkata, India

    Swagatam Das

  4. SRM Engineering College, Department of Electrical and Electronics Engineering, SRM University, Potheri, Kattankulathur, 603203, Kancheepuram, Tamil Nadu, India

    Shubhransu Sekhar Dash

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© 2013 Springer International Publishing Switzerland

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Nag, S., Philip, N. (2013). Application of Neural Networks to Automatic Load Frequency Control. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8298. Springer, Cham. https://doi.org/10.1007/978-3-319-03756-1_39

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  • DOI: https://doi.org/10.1007/978-3-319-03756-1_39

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03755-4

  • Online ISBN: 978-3-319-03756-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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