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Bibliographic Details
Main Authors: Kandivalasa, Akhila, Netto, Marcos
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2510.26701
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author Kandivalasa, Akhila
Netto, Marcos
author_facet Kandivalasa, Akhila
Netto, Marcos
contents The proposed approach yields a numerical method that provably executes in linear time with respect to the number of nodes and edges in a graph. The graph, constructed from the power system model, requires only knowledge of the dependencies between state-to-state and output-to-state variables within a state-space framework. While graph-based observability analysis methods exist for power system static-state estimation, the approach presented here is the first for dynamic-state estimation (DSE). We examine decentralized and centralized DSE scenarios and compare our findings with a well-established, albeit non-scalable, observability analysis method in the literature. When compared to the latter in a centralized DSE setting, our method reduced computation time by 1440x.
format Preprint
id arxiv_https___arxiv_org_abs_2510_26701
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Graph approach for observability analysis in power system dynamic state estimation
Kandivalasa, Akhila
Netto, Marcos
Systems and Control
The proposed approach yields a numerical method that provably executes in linear time with respect to the number of nodes and edges in a graph. The graph, constructed from the power system model, requires only knowledge of the dependencies between state-to-state and output-to-state variables within a state-space framework. While graph-based observability analysis methods exist for power system static-state estimation, the approach presented here is the first for dynamic-state estimation (DSE). We examine decentralized and centralized DSE scenarios and compare our findings with a well-established, albeit non-scalable, observability analysis method in the literature. When compared to the latter in a centralized DSE setting, our method reduced computation time by 1440x.
title Graph approach for observability analysis in power system dynamic state estimation
topic Systems and Control
url https://arxiv.org/abs/2510.26701