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Artificial Bee Colony Optimization Algorithm for Fault Section Estimation

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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 517))

Abstract

This paper introduces an optimization technique that uses an artificial bee colony (ABC) algorithm to solve the fault section estimation (FSE) problem. FSE is introduced as an optimization problem, where the objective function includes the status of protective relays and circuit breakers. The ABC algorithm is a new population-based optimization technique inspired by behavior of the bee colony to search honey. In order to test the effectiveness of the proposed technique, two sample systems are tested under various test cases. Also the results obtained by the proposed ABC algorithm is compared with those obtained using two other methods. The results show the accuracy and high computation efficiency of the ABC algorithm. The ABC algorithm has a main advantage that it has only two parameters to be controlled. Therefore, the tuning of the proposed algorithm is easier and has a higher probability to reach the optimum solution than other competing methods.

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Author information

Authors and Affiliations

  1. Department of Electrical Power & Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt

    M. A. Sobhy, A. Y. Abdelaziz, M. Ezzat & W. Elkhattam

  2. Department of Electrical Engineering, National Institute of Technology, Raipur, C.G, India

    Anamika Yadav & Bhupendra Kumar

Authors
  1. M. A. Sobhy
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  2. A. Y. Abdelaziz
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  3. M. Ezzat
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  4. W. Elkhattam
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  5. Anamika Yadav
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  6. Bhupendra Kumar
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Corresponding author

Correspondence to Anamika Yadav .

Editor information

Editors and Affiliations

  1. Department of Electrical and Electronics Engineering, SRM University, Chennai, Tamil Nadu, India

    Subhransu Sekhar Dash

  2. Department of Electrical and Electronics Engineering, SRM University, Chennai, Tamil Nadu, India

    K. Vijayakumar

  3. Department of Electrical and Electronics Engineering, Indian Institute of Technology Delhi, New Delhi, India

    Bijaya Ketan Panigrahi

  4. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

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Sobhy, M.A., Abdelaziz, A.Y., Ezzat, M., Elkhattam, W., Yadav, A., Kumar, B. (2017). Artificial Bee Colony Optimization Algorithm for Fault Section Estimation. In: Dash, S., Vijayakumar, K., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-10-3174-8_12

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  • DOI: https://doi.org/10.1007/978-981-10-3174-8_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3173-1

  • Online ISBN: 978-981-10-3174-8

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