Distributed Multi-Area State Estimation for Power Systems With Switching Communication Graphs

We consider distributed multi-area state estimation algorithms for power systems with switching communication graphs. The power system is partitioned into multiple geographically non-overlapping areas and each area is assigned with an estimator to give a local estimate of the entire power system...

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Bibliographic Details
Published inIEEE transactions on smart grid Vol. 12; no. 1; pp. 787 - 797
Main Authors Wang, Jiexiang, Li, Tao
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.01.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Area measurement
Communication
Communication networks
Communications systems
Convergence
convergence analysis
distributed state estimation
Graph theory
Graphs
Power system
Power systems
State estimation
Switches
Switching
switching communication graph
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Summary:We consider distributed multi-area state estimation algorithms for power systems with switching communication graphs. The power system is partitioned into multiple geographically non-overlapping areas and each area is assigned with an estimator to give a local estimate of the entire power system's state. The inter-area communication networks are assumed to switch among a finite set of digraphs. Each area runs a distributed estimation algorithm based on consensus+innovations strategies. By the binomial expansion of matrix products, time-varying system and algebraic graph theories, we prove that all area's local estimates converge to the global least square estimate with probability 1 if the measurement system is jointly observable and the communication graphs are balanced and jointly strongly connected. Finally, we demonstrate the theoretical results by an IEEE 118-bus system.
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2020.3018486