Efficient State Estimation for Gas Pipeline Networks via Low-Rank Approximations

In this paper we investigate the performance of projection-based low-rank approximations in Kalman filtering. For large-scale gas pipeline networks structure-preserving model order reduction has turned out to be an advantageous way to compute accurate solutions with much less computational effort. F...

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Bibliographic Details
Published in:arXiv.org 2021-05
Main Authors: Stahl, Nadine, Marheineke, Nicole
Format: Article
Language:English
Subjects:
Approximation
Gas pipelines
Kalman filters
Model reduction
Natural gas
State estimation
Online Access:Get full text
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Summary:In this paper we investigate the performance of projection-based low-rank approximations in Kalman filtering. For large-scale gas pipeline networks structure-preserving model order reduction has turned out to be an advantageous way to compute accurate solutions with much less computational effort. For state estimation we propose to combine these low-rank models with Kalman filtering and show the advantages of this procedure to established low-rank Kalman filters in terms of efficiency and quality of the estimate.
ISSN:2331-8422