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Journal ArticleDOI

State Estimation in Power Systems: Detecting Bad Data through the Sparse Inverse Matrix Method

TLDR
In the real time control of power system, the state estimation function plays a leading role and must detect and eliminate the grossly erroneous measurements.
Abstract
In the real time control of power system, the state estimation function plays a leading role. To perform its task, the estimator must detect and eliminate the grossly erroneous measurements.

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Citations
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Journal ArticleDOI

Fast Decoupled State Estimation and Bad Data Processing

TL;DR: This paper presents fast-decoupled state estimators, using also decoupled detection and identification of bad data, using the sparse inverse matrix method.

Fast decoupledstate estimationand bad data processing

A. Garcia
TL;DR: In this paper, fast decoupled state estimators are used for detection and identification of bad data using pseudo-measurement generation, which avoids gain-matrix retriangulations or the use of modifica- tiontechniques like Woodbury formula.
Journal ArticleDOI

A Distributed Multiarea State Estimation

TL;DR: In this article, a distributed state estimation method for multi-area power systems is presented, where each area performs its own state estimation, using local measurements, and exchanges border information (estimated boundary states and measurements) at a coordination state estimator, which computes the system-wide state.
Journal ArticleDOI

Reliable Bad Data Processing for Real-Time State Estimation

TL;DR: In this paper, the authors describe a very simple alternative method, with considerably improved bad data detection properties, based on evaluating the coherency between the measurement with the largest normalized residual and the remainder of the measurement system.
Journal ArticleDOI

LAV Based Robust State Estimation for Systems Measured by PMUs

TL;DR: It is argued that the LAV estimator will be a statistically robust and computationally competitive estimator for those power systems that will be measured entirely by PMUs.
References
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Journal ArticleDOI

Static state estimation in electric power systems

TL;DR: A static state estimator is a collection of digital computer programs which convert telemetered data into a reliable estimate of the transmission network structure and state by accounting for small random metering-communication errors and the need for real-time solutions using limited computer time and storage.
Journal ArticleDOI

Bad Data Suppression in Power System Static State Estimation

TL;DR: In this paper, the authors proposed a bad data suppression (BDS) estimator which is based on a non-quadratic cost function but which reduces to the weighted least squares estimator in the absence of bad data.
Journal ArticleDOI

State Estimation in Power Systems Part I: Theory and Feasibility

TL;DR: State estimation is a digital processing scheme which provides a real-time data base for many of the central control and dispatch functions in a power system as discussed by the authors, where the estimator processes the imperfect information available and produces the best possible estimate of the true state of the system.
Journal ArticleDOI

Fast Method for Bad Data Identification in Power System State Estimation

TL;DR: The residual method principle used for bad data detection after a least squares state estimation is stated and how to find very rapidly a new state for the power system and new residuals after suppressing one of these doubtful measurements.
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