Decentralized state estimation for hybrid AC/DC microgrids

This paper presents a decentralized state estimation (SE) for the newly emerging hybrid ac/dc microgrid. The microgrid consists of an ac and a dc network which are connected via the interlinking ac/dc converter. The proposed SE is able to estimate the state variables of both networks in a decentrali...

Full description

Saved in:
Bibliographic Details
Main Authors: Xia, Nan, Gooi, Hoay Beng, Chen, Shuaixun, Hu, Wuhua
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/140227
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-140227
record_format dspace
spelling sg-ntu-dr.10356-1402272020-05-27T07:45:09Z Decentralized state estimation for hybrid AC/DC microgrids Xia, Nan Gooi, Hoay Beng Chen, Shuaixun Hu, Wuhua School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Decentralized State Estimation Dual Decomposition This paper presents a decentralized state estimation (SE) for the newly emerging hybrid ac/dc microgrid. The microgrid consists of an ac and a dc network which are connected via the interlinking ac/dc converter. The proposed SE is able to estimate the state variables of both networks in a decentralized way that the estimation is separately conducted while only limited information is exchanged during the process. The dual decomposition approach is adopted as the decentralized technique in this paper. Simulation results suggest that the proposed decentralized SE performs comparably to the centralized SE for the hybrid ac/dc microgrids in terms of accuracy, convergence, and robustness. 2020-05-27T07:45:09Z 2020-05-27T07:45:09Z 2016 Journal Article Xia, N., Gooi, H. B., Chen, S., & Hu, W. (2018). Decentralized state estimation for hybrid AC/DC microgrid. IEEE Systems Journal, 12(1), 434-443. doi:10.1109/JSYST.2016.2615428 1932-8184 https://hdl.handle.net/10356/140227 10.1109/JSYST.2016.2615428 2-s2.0-84992166162 1 12 434 443 en IEEE Systems Journal © 2016 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Decentralized State Estimation
Dual Decomposition
spellingShingle Engineering::Electrical and electronic engineering
Decentralized State Estimation
Dual Decomposition
Xia, Nan
Gooi, Hoay Beng
Chen, Shuaixun
Hu, Wuhua
Decentralized state estimation for hybrid AC/DC microgrids
description This paper presents a decentralized state estimation (SE) for the newly emerging hybrid ac/dc microgrid. The microgrid consists of an ac and a dc network which are connected via the interlinking ac/dc converter. The proposed SE is able to estimate the state variables of both networks in a decentralized way that the estimation is separately conducted while only limited information is exchanged during the process. The dual decomposition approach is adopted as the decentralized technique in this paper. Simulation results suggest that the proposed decentralized SE performs comparably to the centralized SE for the hybrid ac/dc microgrids in terms of accuracy, convergence, and robustness.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Xia, Nan
Gooi, Hoay Beng
Chen, Shuaixun
Hu, Wuhua
format Article
author Xia, Nan
Gooi, Hoay Beng
Chen, Shuaixun
Hu, Wuhua
author_sort Xia, Nan
title Decentralized state estimation for hybrid AC/DC microgrids
title_short Decentralized state estimation for hybrid AC/DC microgrids
title_full Decentralized state estimation for hybrid AC/DC microgrids
title_fullStr Decentralized state estimation for hybrid AC/DC microgrids
title_full_unstemmed Decentralized state estimation for hybrid AC/DC microgrids
title_sort decentralized state estimation for hybrid ac/dc microgrids
publishDate 2020
url https://hdl.handle.net/10356/140227
_version_ 1681058913722564608