Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/835
Title: | Distributed Gauss-Newton Method for State Estimation Using Belief Propagation | Authors: | Cosovic M. Vukobratović, Dejan |
Issue Date: | 1-Jan-2019 | Journal: | IEEE Transactions on Power Systems | Abstract: | © 2018 IEEE. We present a novel distributed Gauss-Newton method for the non-linear state estimation (SE) model based on a probabilistic inference method called belief propagation (BP). The main novelty of our work comes from applying BP sequentially over a sequence of linear approximations of the SE model, akin to what is done by the Gauss-Newton method. The resulting iterative Gauss-Newton belief propagation (GN-BP) algorithm can be interpreted as a distributed Gauss-Newton method with the same accuracy as the centralized SE, however, introducing a number of advantages of the BP framework. The paper provides extensive numerical study of the GN-BP algorithm, provides details on its convergence behavior, and gives a number of useful insights for its implementation. | URI: | https://open.uns.ac.rs/handle/123456789/835 | ISSN: | 8858950 | DOI: | 10.1109/TPWRS.2018.2866583 |
Appears in Collections: | FTN Publikacije/Publications |
Show full item record
SCOPUSTM
Citations
29
checked on May 3, 2024
Page view(s)
25
Last Week
5
5
Last month
0
0
checked on May 10, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.