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Application of Artificial Bee Colony Optimization: Power System Voltage Stability Problems

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8947))

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Abstract

This paper highlights the effective usage of Artificial Bee Colony (ABC) to predict the stability of the system based on the Fast Voltage Stability Index (FVSI). The content of the paper is to compare the effectiveness of optimization techniques with the conventional method. The system stability, the point collapse and the weakest busses are identified based on the line reactive power loading in the power system network. Based on the weak bus identified either Thyristor Controlled Series Compensator (TCSC) or Unified Power Flow Controller (UPFC) will be connected to enhance the stability of the power system network. These techniques are coded with the newton raphson load flow analysis, implemented and tested with IEEE 30 bus system.

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Author information

Authors and Affiliations

  1. Department of EEE, SRM University, Kattankulathur, 603203, India

    Kiran S. Harish, Sekhar Dash Subhransu, C. Subramani & ChandraBabu Paduchuri

Authors
  1. Kiran S. Harish
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  2. Sekhar Dash Subhransu
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  3. C. Subramani
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  4. ChandraBabu Paduchuri
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Corresponding author

Correspondence to Kiran S. Harish .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, IIT, New Delhi, India

    Bijaya Ketan Panigrahi

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

    Ponnuthurai Nagaratnam Suganthan

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

    Swagatam Das

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Harish, K.S., Subhransu, S.D., Subramani, C., Paduchuri, C. (2015). Application of Artificial Bee Colony Optimization: Power System Voltage Stability Problems. In: Panigrahi, B., Suganthan, P., Das, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science(), vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_68

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  • DOI: https://doi.org/10.1007/978-3-319-20294-5_68

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20293-8

  • Online ISBN: 978-3-319-20294-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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