Trust-based distributed state estimation for microgrids with encoding-decoding mechanisms

In this article, a trust-based estimation algorithm in a distributed paradigm is developed for microgrids whose information transmission obeys the predetermined encoding and decoding rule. Because of weak communication protection, and harsh electromagnetic or geographical environments, the output of...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Information sciences Ročník 639; s. 118946
Hlavní autoři: Zhao, Peifeng, Liu, Hongjian, Huang, Tingwen, Tan, Hailong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.08.2023
Témata:
ISSN:0020-0255, 1872-6291
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this article, a trust-based estimation algorithm in a distributed paradigm is developed for microgrids whose information transmission obeys the predetermined encoding and decoding rule. Because of weak communication protection, and harsh electromagnetic or geographical environments, the output of sensors in microgrids could be subject to outliers or cyberattacks, which will lead to anomalous estimates. According to such a challenge, a simple clustering method is employed to distinguish between trusted and untrusted data. In light of distinguished data, a novel distributed estimator under an encoding and decoding scheme is then proposed where the correction of untrusted data is executed by the cluster information. Furthermore, a performable algorithm is developed by optimizing the upper bound of error covariance and a novel decomposition of system matrices, and a condition is derived to check the boundedness of the developed iterative algorithm. In the end, a simulation example is given to verify the effectiveness. •A simple clustering method is employed to distinguish trusted and untrusted data.•A novel distributed estimator is proposed where the correction of untrusted data is executed by the cluster information.•A performable algorithm is developed by optimizing the upper bound of error covariance.•A condition is derived to check the boundedness of the developed iterative algorithm.
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2023.118946