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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Zusammenfassung: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.
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ISSN:0733-8716
1558-0008
DOI:10.1109/JSAC.2013.130703