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Event triggered state estimation based on multi-sensor data for distribution systems with quick dynamics
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AI
DOI：10.1016/j.epsr.2026.113205.png)
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Abstract
En 中文
• A tailored event-triggered mechanism is developed for DSSE based on measurement variations, using merely local real-time measurements and eliminating the need for state feedback at the edge. It is designed to operate within existing unidirectional communication infrastructures, enhancing its adaptability in real distribution systems. • A regularized robust state estimation model is built for the three-phase balanced and unbalanced distribution systems, leveraging prior state information to mitigate under-determined issues and to accurate track fast dynamics. • A linearized weighted least absolute-based method in the complex domain is developed to facilitate computational efficient SE execution and enable high estimation rates required to track fast dynamics. • Case studies on the three-phase balanced and unbalanced distribution systems are demonstrated superiorities of the proposed approach, particularly under conditions of asynchronous data, load jumps, severe fluctuations of distributed power generation and measurement outliers.
Keywords:
Event-triggered mechanism
State estimation
Distribution systems
Fast dynamics
Robust estimation
Journal
IF:
4.2
Papers:
1.1W
Citations:
2.2W
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