Distributed Operation State Monitoring of PowerNetwork System Considering Load Disturbance

Introduction: This study aims to propose a distributed monitoring framework for multi- -node power networks, addressing system-wide status-observation challenges where individual nodes have limited sensors and communication capabilities. Methods: The framework adopts localized data processing and neighbor information exchange for collaborative state estimation, with innovations including customizable coefficient matrix design and a load disturbance rejection mechanism based on rigorous matrix analysis. Results: Experimental validation on a 5-node thermal power system shows that the framework achieves global monitoring with local resources, achieving enhanced state estimation accuracy via parameter optimization and maintaining computational efficiency. Discussion: The solution eliminates centralized data processing dependencies, offering practical value for power grid maintenance and fault detection, while its flexible design supports scalability, though it is tailored to multi-node thermal power systems Conclusion: The distributed framework effectively balances monitoring precision and resource constraints, providing a scalable, efficient solution for operational optimization of distributed energy systems.