DocumentCode :
2668087
Title :
State estimation and learning of unknown branch current flows using decentralized Kalman filter with virtual disturbance model
Author :
Liu, Junqi ; Benigni, Andrea ; Obradovic, Dragan ; Hirche, Sandra ; Monti, Antonello
Author_Institution :
E.ON Energy Res. Center, RWTH Aachen Univ., Aachen, Germany
fYear :
2010
fDate :
22-24 Sept. 2010
Firstpage :
31
Lastpage :
36
Abstract :
This paper presents the design of a decentralized Kalman filter (DKF) without communication to be used for state estimation in distributed generation-based power systems. The idea is to reconstruct information about the system states in the power network, avoiding as much as possible the use of communication channels. The DKF is synthesized based on local models of the power network associated with a virtual disturbance model. The synthesized local Kalman filters of the DKF approach are used for local state estimation while the dynamics of the rest of the power network are lumped into the time-varying virtual disturbance model. The proposed solution is applied to an interconnected power network. By choosing appropriate models for the virtual disturbance the DKF can be suited for both DC and AC distribution systems. It is shown for both cases that the DKF can learn (infer) the local states of the network including the aggregated branch currents coming from the other buses. The herein presented approach is well suited for the agent-based distributed control of micro-grids.
Keywords :
Kalman filters; distributed power generation; power grids; power system state estimation; agent based distributed control; branch current flow learning; decentralized Kalman filter; distributed generation; interconnected power network; local state learning; microgrid; power systems; state estimation; time varying virtual disturbance model; Kalman filters; Load modeling; Mathematical model; Power system dynamics; State estimation; Voltage measurement; Decentralized Kalman Filter; Decentralized State Estimation; Power System State Estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Measurements For Power Systems (AMPS), 2010 IEEE International Workshop on
Conference_Location :
Aachen
Print_ISBN :
978-1-4244-7372-4
Type :
conf
DOI :
10.1109/AMPS.2010.5609327
Filename :
5609327
Link To Document :
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