Visualization and Animation of State Estimation Performance

Meliopoulos, A. P. Sakis; Cokkinides, G.J.; Ingram, Michael; Bell, Sally; Mathews, Sunish

doi:10.1109/hicss.2005.678

Cited by 11 publications

(3 citation statements)

References 13 publications

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“…This can be applicable due to PMU technology that can provide GPS synchronized measurements that are time stamped and as a result globally valid, thus eliminating problems from the geographic separation of the power systems. This is the basic idea of the hybrid state estimator [11]- [12] and the SuperCalibrator concept [13]- [16]. Specifically, the SuperCalibrator is a distributed three-phase state estimator that operates at the substation level and requires at least one PMU at the substation of interest.…”

Section: Introductionmentioning

confidence: 99%

Object-oriented 3-Phase distributed dynamic state estimator

Huang

Farantatos

Cokkinides

et al. 2011

2011 IEEE Power and Energy Society General Meeting

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This paper presents a suite of two distributed dynamic state estimators (QSE and DSE) that are performed at the substation level. The algorithm uses local GPS-synchronized and conventional non-synchronized measurements in the substation of interest for estimating the states of the substation as well as the states at the other ends of the transmission lines at the adjacent substations. The estimation algorithm provides the true dynamic (transient) states of the system. As such it provides the basic infrastructure for highly accurate real time dynamic monitoring and control at speeds that are not presently available. Numerical experiments on the NYPA Gilboa-Blenheim substation are presented in this paper for the purpose of evaluating the performance of the proposed algorithms. It is shown that the proposed algorithm is reliable and feasible for practical implementation.

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Section: Introductionmentioning

confidence: 99%

Object-oriented 3-Phase distributed dynamic state estimator

Huang

Farantatos

Cokkinides

et al. 2011

2011 IEEE Power and Energy Society General Meeting

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“…The results from each subsystem then can be combined to synthesize the state of the entire system. The distributed state estimation idea has been realized by the SuperCalibrator concept proposed by the author [9], [10], [11]. The SuperCalibrator is conceptually very simple and applies to each substation of a large system.…”

Section: Introductionmentioning

confidence: 99%

Legacy SE to distributed dynamic state estimators: Evolution and experience

Meliopoulos

2015

2015 IEEE Power &Amp; Energy Society General Meeting

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This paper describes the evolution of state estimators from the legacy static state estimators to the distributed dynamic state estimators. Dynamic state estimators are computational demanding and only distributed approaches are practical. We present two specific distributed dynamic state estimators: (a) the quasi-dynamic state estimator which uses GPS-synchronized and non-synchronized measurements of phasors and a quasi-dynamic model (electrical transients are neglected but electromechanical transients are modeled), and (b) a distributed dynamic state estimator using sampled value measurements and the full dynamical model of the system. For each one of the distributed state estimators three solution approaches are used: (a) unconstraint optimization problem, (b) constraint optimization problem and (c) extended Kalman filter approach. The quasidynamic state estimator has been installed in pilot projects and field experience has been gained. The distributed dynamic state estimator forms the core technology for the setting-less protection and it has been extensively tested in the laboratory. Field demonstration are planned in the near future. Dynamic state estimator provide so much more and useful information that will drastically increase the operational reliability of the system. Recent developments have made dynamic state estimators feasible with practically no additional costs. By necessity, dynamic state estimators must be distributed operating on local data since we believe that it is impractical to construct massive and fast communication network for transferring the data that will be required by a centralized dynamic state estimator.

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“…In [6], programs to visualize line flow and bus data are presented. In [7], bad measurements used in state estimation are displayed in an easily identifiable way. This paper will describe a flexible software tool which takes advantage of different visualization techniques such as animation, color contouring and 3D visualization in order to extract and highlight certain user specified information from the data acquired by the supervisory data acquisition (SCADA) system.…”

Section: Introductionmentioning

confidence: 99%

3D Visualization of Power System State Estimation

Yuksel

Abur

et al.

MELECON 2006 - 2006 IEEE Mediterranean Electrotechnical Conference

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This paper presents the results of a project which is undertaken in order to develop a flexible visualization tool to be used mainly by power system operators. The project concentrated on two application functions, namely the power flow and the state estimation. One of the essential goals of the envisioned tool is to aid system operators by providing images of the system with easily identifiable characteristics related to violations of various operating limits. In addition, the tool is expected to illustrate deficiencies associated with the existing metering system both from the point of view of metering design as well as accuracy. The result is a user-friendly 3D graphic interface for the stated two power system applications. In power flow analysis mode, animation and bus contouring technique is used for visualizing power flows and bus voltages. In state estimation mode, color contour is used to visualize different observable islands and bad measurements which are identified through the largest normalized residuals test. Effectiveness of the tool is illustrated via different scenarios which are created using the IEEE 118 bus system as an example.

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Visualization and Animation of State Estimation Performance

Abstract: Abstract

Cited by 11 publications

References 13 publications

Object-oriented 3-Phase distributed dynamic state estimator

Object-oriented 3-Phase distributed dynamic state estimator

Legacy SE to distributed dynamic state estimators: Evolution and experience

3D Visualization of Power System State Estimation

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