Robust Decentralized State Estimation and Tracking for Power Systems via Network Gossiping

This paper proposes a fully decentralized adaptive re-weighted state estimation (DARSE) scheme for power systems via network gossiping. The enabling technique is the proposed Gossip-based Gauss-Newton (GGN) algorithm, which allows to harness the computation capability of each area (i.e. a database s...

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Veröffentlicht in:	IEEE journal on selected areas in communications Jg. 31; H. 7; S. 1184 - 1194
Hauptverfasser:	Xiao Li, Scaglione, A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2013 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms convergence Decentralized Failure gossiping Hybrid state estimation Mathematical models Maximum likelihood estimation Networks On-line systems Online Operations research Phasor measurement units Power measurement Power systems State estimation Studies Transmission line measurements Voltage measurement
ISSN:	0733-8716, 1558-0008
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Abstract	This paper proposes a fully decentralized adaptive re-weighted state estimation (DARSE) scheme for power systems via network gossiping. The enabling technique is the proposed Gossip-based Gauss-Newton (GGN) algorithm, which allows to harness the computation capability of each area (i.e. a database server that accrues data from local sensors) to collaboratively solve for an accurate global state. The DARSE scheme mitigates the influence of bad data by updating their error variances online and re-weighting their contributions adaptively for state estimation. Thus, the global state can be estimated and tracked robustly using near-neighbor communications in each area. Compared to other distributed state estimation techniques, our communication model is flexible with respect to reconfigurations and resilient to random failures as long as the communication network is connected. Furthermore, we prove that the Jacobian of the power flow equations satisfies the Lipschitz condition that is essential for the GGN algorithm to converge to the desired solution. Simulations of the IEEE-118 system show that the DARSE scheme can estimate and track online the global power system state accurately, and degrades gracefully when there are random failures and bad data.
AbstractList	This paper proposes a fully decentralized adaptive re-weighted state estimation (DARSE) scheme for power systems via network gossiping. The enabling technique is the proposed Gossip-based Gauss-Newton (GGN) algorithm, which allows to harness the computation capability of each area (i.e. a database server that accrues data from local sensors) to collaboratively solve for an accurate global state. The DARSE scheme mitigates the influence of bad data by updating their error variances online and re-weighting their contributions adaptively for state estimation. Thus, the global state can be estimated and tracked robustly using near-neighbor communications in each area. Compared to other distributed state estimation techniques, our communication model is flexible with respect to reconfigurations and resilient to random failures as long as the communication network is connected. Furthermore, we prove that the Jacobian of the power flow equations satisfies the Lipschitz condition that is essential for the GGN algorithm to converge to the desired solution. Simulations of the IEEE-118 system show that the DARSE scheme can estimate and track online the global power system state accurately, and degrades gracefully when there are random failures and bad data.
Author	Xiao Li Scaglione, A.
Author_xml	– sequence: 1 surname: Xiao Li fullname: Xiao Li email: eceli@ucdavis.edu organization: Dept. of Electr. & Comput. Eng., Univ. of California, Davis, Davis, CA, USA – sequence: 2 givenname: A. surname: Scaglione fullname: Scaglione, A. email: ascaglione@ucdavis.edu organization: Dept. of Electr. & Comput. Eng., Univ. of California, Davis, Davis, CA, USA
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SubjectTerms	Algorithms convergence Decentralized Failure gossiping Hybrid state estimation Mathematical models Maximum likelihood estimation Networks On-line systems Online Operations research Phasor measurement units Power measurement Power systems State estimation Studies Transmission line measurements Voltage measurement
Title	Robust Decentralized State Estimation and Tracking for Power Systems via Network Gossiping
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