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    This study introduces a dynamic event-triggered protocol for load frequency control in interconnected power systems, improving stability and communication efficiency using semi-Markov processes. The new asynchronous control strategy ensures finite-time performance despite system uncertainties.

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    Area of Science:

    • Control Systems Engineering
    • Power Systems Analysis
    • Stochastic Processes

    Background:

    • Interconnected multiarea power systems (IMAPSs) face challenges in maintaining stable load frequency control (LFC) due to stochastic parameter variations.
    • Traditional control protocols can be inefficient, leading to communication resource waste and suboptimal performance in dynamic grid environments.

    Purpose of the Study:

    • To develop a dynamic event-triggered protocol (DETP) for robust LFC in IMAPSs with stochastic semi-Markov parameters.
    • To address the asynchronization between system and controller modes using a hidden semi-Markov model (HSMM).
    • To ensure finite-time boundedness and predefined system performance under dynamic conditions.

    Main Methods:

    • Characterization of IMAPSs random behavior using semi-Markov processes (SMP).
    • Development of a dynamic event-triggered protocol (DETP) with adjustable thresholds for efficient communication.
    • Application of a hidden semi-Markov model (HSMM) to manage mode asynchronization.
    • Construction of a modular dependent random Lyapunov function for theoretical analysis.

    Main Results:

    • Sufficient conditions derived to guarantee finite-time boundedness of the system with performance guarantees.
    • The proposed DETP effectively modulates transmission frequency while optimizing communication resource usage.
    • Demonstrated efficiency of the asynchronous control strategy in a three-area power system simulation.

    Conclusions:

    • The novel asynchronous control strategy effectively solves the mode mismatch problem in IMAPSs.
    • The DETP offers a significant improvement over static protocols by enhancing dynamic performance and reducing communication overhead.
    • The study provides a robust framework for finite-time LFC in complex, stochastic power systems.