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<p>This study introduces a Hybrid Intelligent Control (HIC) structure for improving Power Quality (PQ) within Renewable-Integrated Microgrids (MG). A traditional control technique is combined with an adaptive Artificial Intelligence (AI) based optimization layer for superior Voltage and Frequency Regulation; Harmonic Mitigation; and Unbalanced Compensation. The hierarchical control structure allows for real-time control parameter adjustments in response to changing Load Conditions; Generation; and Network conditions thus overcomes the deficiencies of both Fixed Parameter and Pure Heuristic Controllers. MATLAB/Simulink was used to perform comprehensive simulation studies of an Islanded MG containing PV, WT, FC, and Battery Storage Units. The results show that the proposed HIC provides faster Transient Recovery Time; Less Overshoot; and Improved Steady-State Performance than Conventional PI and Non-Intelligent Hybrid Control Schemes. Specifically, the total harmonic distortion (THD) at the point of common coupling (PCC) was reduced from 4.7% (PI) and 2.8% (hybrid) to 1.2% with the HIC, while the voltage unbalance factor (VUF) decreased from 2.9 to 0.7%. Additionally, the controller maintained frequency deviations within ±0.05&#xa0;Hz under islanded operation, demonstrating better dynamic stability. These improvements confirm that the proposed HIC enhances both the reliability and resilience of modern MGs, offering a scalable and computationally efficient solution for future intelligent power networks.</p>

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Hybrid Intelligent Control Framework for Power Quality Enhancement in Microgrid Systems

  • 期刊论文

  • 发表日期：

    2026年3月3日

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  • Pratibha V. Hurkadli,
  • T. C. Manjunath,
  • G. Arun Kumar

摘要

This study introduces a Hybrid Intelligent Control (HIC) structure for improving Power Quality (PQ) within Renewable-Integrated Microgrids (MG). A traditional control technique is combined with an adaptive Artificial Intelligence (AI) based optimization layer for superior Voltage and Frequency Regulation; Harmonic Mitigation; and Unbalanced Compensation. The hierarchical control structure allows for real-time control parameter adjustments in response to changing Load Conditions; Generation; and Network conditions thus overcomes the deficiencies of both Fixed Parameter and Pure Heuristic Controllers. MATLAB/Simulink was used to perform comprehensive simulation studies of an Islanded MG containing PV, WT, FC, and Battery Storage Units. The results show that the proposed HIC provides faster Transient Recovery Time; Less Overshoot; and Improved Steady-State Performance than Conventional PI and Non-Intelligent Hybrid Control Schemes. Specifically, the total harmonic distortion (THD) at the point of common coupling (PCC) was reduced from 4.7% (PI) and 2.8% (hybrid) to 1.2% with the HIC, while the voltage unbalance factor (VUF) decreased from 2.9 to 0.7%. Additionally, the controller maintained frequency deviations within ±0.05 Hz under islanded operation, demonstrating better dynamic stability. These improvements confirm that the proposed HIC enhances both the reliability and resilience of modern MGs, offering a scalable and computationally efficient solution for future intelligent power networks.