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<p>This paper presents a fully distributed adaptive dynamic event-triggered control (FDOAD-ETC) strategy for islanded AC microgrids (MGs). The proposed approach restores frequency and voltage to nominal values while achieving precise real power sharing. The fully distributed nature of the method eliminates the need for global information, such as the Laplacian matrix, relying only on local measurements from each distributed generator (DG). This enhances scalability and simplifies implementation, particularly for large-scale MGs. To demonstrate the core features of the approach, we introduce communication challenges such as delays and packet dropouts. These challenges highlight the strength of our adaptive dynamic event-triggered control (ADETC) system, which adjusts triggering thresholds in real time to ensure system stability and reduce communication overhead. Unlike static event-triggered methods, our dynamic approach is resilient to disruptions, prevents Zeno behavior, and adapts to varying network conditions. Simulations in MATLAB/SimPowerSystems validate the effectiveness of the FDOAD-ETC method, showing that it maintains stability and performance even under communication delays and data loss. The results confirm that our fully distributed and adaptive control framework provides a scalable, robust, and efficient solution for managing complex MGs.</p>

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Fully distributed adaptive event-triggered control with delay-aware dynamic thresholds for islanded AC microgrids

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月31日

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  • Zahrasadat Sajjadinezhad,
  • Nima Mahdian Dehkordi

摘要

This paper presents a fully distributed adaptive dynamic event-triggered control (FDOAD-ETC) strategy for islanded AC microgrids (MGs). The proposed approach restores frequency and voltage to nominal values while achieving precise real power sharing. The fully distributed nature of the method eliminates the need for global information, such as the Laplacian matrix, relying only on local measurements from each distributed generator (DG). This enhances scalability and simplifies implementation, particularly for large-scale MGs. To demonstrate the core features of the approach, we introduce communication challenges such as delays and packet dropouts. These challenges highlight the strength of our adaptive dynamic event-triggered control (ADETC) system, which adjusts triggering thresholds in real time to ensure system stability and reduce communication overhead. Unlike static event-triggered methods, our dynamic approach is resilient to disruptions, prevents Zeno behavior, and adapts to varying network conditions. Simulations in MATLAB/SimPowerSystems validate the effectiveness of the FDOAD-ETC method, showing that it maintains stability and performance even under communication delays and data loss. The results confirm that our fully distributed and adaptive control framework provides a scalable, robust, and efficient solution for managing complex MGs.