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<p>This paper presents an optimal passive filter framework to mitigate harmonic distortions generated by industrial loads at the point of common coupling (PCC) with the power grid. Real-time power quality measurements at the point of connection of an industrial steel plant load were employed as the base input for C-type filter parameters optimization. The filter tuning was cast as a multi-objective optimization problem and solved using an adaptive-weight Artificial Bee Colony (MOABC) algorithm, with objectives including minimization of filter cost, voltage total harmonic distortion (VTHD), impedance frequency response deviation and current total demand distortion (ITDD). The resulting Pareto front is analyzed via a Grey Relational Analysis-based Multi-Criteria Decision-Making (MCDM) approach to select a C-type filter configuration optimized for the seventh harmonic. Comparative studies against Particle Swarm Optimization, Crow Search and Crow Spiral algorithms confirm that the proposed MOABC–MCDM methodology delivers superior harmonic attenuation and power factor enhancement at the industrial point of connection.</p>

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Power Quality Assessment and Harmonic Mitigation at the Point of Common Coupling of Industrial Load

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月17日

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  • Emenike Ugwuagbo,
  • Biplob Ray,
  • Adeola Balogun,
  • Frank Okafor,
  • Jay Sul,
  • Nurun Nabi,
  • Ujjwal Datta

摘要

This paper presents an optimal passive filter framework to mitigate harmonic distortions generated by industrial loads at the point of common coupling (PCC) with the power grid. Real-time power quality measurements at the point of connection of an industrial steel plant load were employed as the base input for C-type filter parameters optimization. The filter tuning was cast as a multi-objective optimization problem and solved using an adaptive-weight Artificial Bee Colony (MOABC) algorithm, with objectives including minimization of filter cost, voltage total harmonic distortion (VTHD), impedance frequency response deviation and current total demand distortion (ITDD). The resulting Pareto front is analyzed via a Grey Relational Analysis-based Multi-Criteria Decision-Making (MCDM) approach to select a C-type filter configuration optimized for the seventh harmonic. Comparative studies against Particle Swarm Optimization, Crow Search and Crow Spiral algorithms confirm that the proposed MOABC–MCDM methodology delivers superior harmonic attenuation and power factor enhancement at the industrial point of connection.