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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Main Authors: Md Masud Rana, Amir Shahirinia
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8886497/
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spelling 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
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