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Multi-Objective Artificial Bee Colony Algorithm with Minimum Manhattan Distance for Passive Power Filter Optimization Problems

Author

Listed:
  • Nien-Che Yang

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan)

  • Danish Mehmood

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan)

  • Kai-You Lai

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan)

Abstract

Passive power filters (PPFs) are most effective in mitigating harmonic pollution from power systems; however, the design of PPFs involves several objectives, which makes them a complex multiple-objective optimization problem. This study proposes a method to achieve an optimal design of PPFs. We have developed a new multi-objective optimization method based on an artificial bee colony (ABC) algorithm with a minimum Manhattan distance. Four different types of PPFs, namely, single-tuned, second-order damped, third-order damped, and C-type damped order filters, and their characteristics were considered in this study. A series of case studies have been presented to prove the efficiency and better performance of the proposed method over previous well-known algorithms.

Suggested Citation

  • Nien-Che Yang & Danish Mehmood & Kai-You Lai, 2021. "Multi-Objective Artificial Bee Colony Algorithm with Minimum Manhattan Distance for Passive Power Filter Optimization Problems," Mathematics, MDPI, vol. 9(24), pages 1-19, December.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:24:p:3187-:d:699589
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    References listed on IDEAS

    as
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