Distributed Dynamic State Estimation Considering Packet Losses in Interconnected Smart Grid Subsystems: Linear Matrix Inequality Approach
This paper proposes a distributed dynamic state estimation algorithm considering packet losses in interconnected smart grid subsystems. Particularly, the distributed filter structure is developed in an interconnected way where the packet dropouts occur in communication links between them. The system...
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doaj-15ff8a8dd13e4f5b963549abdf23eccf2021-03-30T01:11:14ZengIEEEIEEE Access2169-35362020-01-0182687269310.1109/ACCESS.2019.29499958886497Distributed Dynamic State Estimation Considering Packet Losses in Interconnected Smart Grid Subsystems: Linear Matrix Inequality ApproachMd Masud Rana0https://orcid.org/0000-0002-5687-3789Amir Shahirinia1Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, USADepartment of Electrical EngineeringThis paper proposes a distributed dynamic state estimation algorithm considering packet losses in interconnected smart grid subsystems. Particularly, the distributed filter structure is developed in an interconnected way where the packet dropouts occur in communication links between them. The system error dynamic between true and estimate state is written in a compact form after combining all estimation errors. It can be transformed into the linear matrix inequality framework after introducing semidefinite programming variables. Finally, the local and neighboring gains for the distributed estimator are computed after solving the convex optimization problem. The explore method is applied to the IEEE 14-bus system. In doing this, the state-space model of IEEE 14-bus is obtained using the Holt-Winters method. Simulation results are demonstrated considering packet losses and cyber attacks.https://ieeexplore.ieee.org/document/8886497/Communication networksdistributed dynamic state estimationHolt-Winters methodinterconnected subsystemslinear matrix inequalitypacket dropouts |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Md Masud Rana Amir Shahirinia |
spellingShingle |
Md Masud Rana Amir Shahirinia Distributed Dynamic State Estimation Considering Packet Losses in Interconnected Smart Grid Subsystems: Linear Matrix Inequality Approach IEEE Access Communication networks distributed dynamic state estimation Holt-Winters method interconnected subsystems linear matrix inequality packet dropouts |
author_facet |
Md Masud Rana Amir Shahirinia |
author_sort |
Md Masud Rana |
title |
Distributed Dynamic State Estimation Considering Packet Losses in Interconnected Smart Grid Subsystems: Linear Matrix Inequality Approach |
title_short |
Distributed Dynamic State Estimation Considering Packet Losses in Interconnected Smart Grid Subsystems: Linear Matrix Inequality Approach |
title_full |
Distributed Dynamic State Estimation Considering Packet Losses in Interconnected Smart Grid Subsystems: Linear Matrix Inequality Approach |
title_fullStr |
Distributed Dynamic State Estimation Considering Packet Losses in Interconnected Smart Grid Subsystems: Linear Matrix Inequality Approach |
title_full_unstemmed |
Distributed Dynamic State Estimation Considering Packet Losses in Interconnected Smart Grid Subsystems: Linear Matrix Inequality Approach |
title_sort |
distributed dynamic state estimation considering packet losses in interconnected smart grid subsystems: linear matrix inequality approach |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
This paper proposes a distributed dynamic state estimation algorithm considering packet losses in interconnected smart grid subsystems. Particularly, the distributed filter structure is developed in an interconnected way where the packet dropouts occur in communication links between them. The system error dynamic between true and estimate state is written in a compact form after combining all estimation errors. It can be transformed into the linear matrix inequality framework after introducing semidefinite programming variables. Finally, the local and neighboring gains for the distributed estimator are computed after solving the convex optimization problem. The explore method is applied to the IEEE 14-bus system. In doing this, the state-space model of IEEE 14-bus is obtained using the Holt-Winters method. Simulation results are demonstrated considering packet losses and cyber attacks. |
topic |
Communication networks distributed dynamic state estimation Holt-Winters method interconnected subsystems linear matrix inequality packet dropouts |
url |
https://ieeexplore.ieee.org/document/8886497/ |
work_keys_str_mv |
AT mdmasudrana distributeddynamicstateestimationconsideringpacketlossesininterconnectedsmartgridsubsystemslinearmatrixinequalityapproach AT amirshahirinia distributeddynamicstateestimationconsideringpacketlossesininterconnectedsmartgridsubsystemslinearmatrixinequalityapproach |
_version_ |
1724187450120601600 |