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Chaotic Quasi-Oppositional Moth Flame Optimization for Radial Distribution Network Reconfiguration with DG Allocation

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Soft Computing Applications in Modern Power and Energy Systems (EPREC 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1107))

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Abstract

This research aimed to reconfigure radial distribution networks in the presence of distributed generators (DGs) using the Chaotic Quasi-Oppositional Moth Flame Optimization (CQOMFO) method so as to minimize power losses in the power system network and keep the voltage profile consistent throughout the power system network, which will aid in increasing system efficiency. The primary goal is to demonstrate the proper placement of Distributed Generators (DGs) in the radial distribution network, as well as the reconfiguration and installation of DGs in the radial distribution network. The main advantage of this algorithm is continuous guiding search with changing goals, which can be used for real-time applications with only minor adjustments because the power from distributed generation is constantly changing. This algorithm’s efficiency and suitability for real-time applications have been determined by testing for loss minimization on typical 33- and 69-bus radial distribution systems.

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Author information

Authors and Affiliations

  1. Dr. B. C. Roy Engineering College, Durgapur, India

    Sneha Sultana, Sourav Paul, Poulami Acharya, Devjeet Sengupta & Nirmalya Dey

  2. Kalyani Government Engineering College, Kalyani, India

    Provas Kumar Roy

Authors
  1. Sneha Sultana
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  2. Sourav Paul
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  3. Poulami Acharya
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  4. Provas Kumar Roy
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  5. Devjeet Sengupta
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  6. Nirmalya Dey
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Corresponding author

Correspondence to Sneha Sultana .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, National Institute of Technology Jamshedpur, Jamshedpur, India

    Om Hari Gupta

  2. Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Narayana Prasad Padhy

  3. Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, NC, USA

    Sukumar Kamalasadan

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sultana, S., Paul, S., Acharya, P., Roy, P.K., Sengupta, D., Dey, N. (2024). Chaotic Quasi-Oppositional Moth Flame Optimization for Radial Distribution Network Reconfiguration with DG Allocation. In: Gupta, O.H., Padhy, N.P., Kamalasadan, S. (eds) Soft Computing Applications in Modern Power and Energy Systems. EPREC 2023. Lecture Notes in Electrical Engineering, vol 1107. Springer, Singapore. https://doi.org/10.1007/978-981-99-8007-9_15

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  • DOI: https://doi.org/10.1007/978-981-99-8007-9_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8006-2

  • Online ISBN: 978-981-99-8007-9

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