Power system fault detection and state estimation using Kalman filter with hypothesis testing

Chowdhury, Fahmida; Christensen, Jørgen Grønnegaard; Aravena, J.L.

doi:10.1109/61.85843

Cited by 53 publications

(25 citation statements)

References 9 publications

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“…However it has the limitation due to the difficulties in modeling the fault resistance. A Kalman filter-based approach [5]- [7] has been proposed in order to detect power system faults. Wavelet based approach [8] is used to detect the abrupt change in the signal.…”

Section: Introductionmentioning

confidence: 99%

Abrupt change detection of fault in power system using independent component analysis

Dubey

Mohanty

Kishore

2011

2011 International Conference on Signal Processing, Communication, Computing and Networking Technologies

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Abstract-This paper proposes a novel fault detector for digital relaying based on independent component analysis (leA). The index for effective detection is derived from independent components of fault current. The proposed fault detector reduces the computational burden for real time applications and is therefore more accurate and robust as compared to other approaches. Further, a comparative assessment is carried out to establish the effectiveness of the proposed method as compared to the existing methods. This approach can be applied for fault classification and localization of a distance relay reflecting its consistency in all system changing conditions and thus validates its efficacy in the real time applications. The method is tested under a variety of fault and other disturbance conditions of typical power system.

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Section: Introductionmentioning

confidence: 99%

Abrupt change detection of fault in power system using independent component analysis

Dubey

Mohanty

Kishore

2011

2011 International Conference on Signal Processing, Communication, Computing and Networking Technologies

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“…In software system computer relaying, sequential methods should be preferred primarily for the following reasons: The measurements are obtained sequentially sequential tests are usually substantially more efficient in terms of the use of information in the measurements than nonsequential tests, and thus lead to a quicker decision at the same level of decision errors, a sequential test does not need to determine the number of measurements for the test in advance, while a non-sequential test does. It is due to this last reason that some adhoc and questionable tricks to be adopted in the non-sequential hypothesis testing based technique to handle the case in which one sample is not enough to make a decision [6]. As a sequential method, SPRT has an additional advantage that its appropriate threshold for the test statistics can be determined easily without knowledge of the distribution of the measurements, while for a non-sequential test the threshold usually depends on the distribution.…”

Section: Wald's Sequential Test For a Poisson Processmentioning

confidence: 99%

An SPRT Procedure for an Ungrouped Data using MMLE Approach

Goutham¹,

Prasad²

2013

IOSR-JCE

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Sequential Analysis of statistical science could be adopted in order to decide up on the reliable/unreliable of the developed software very quickly. Sequential analysis is different from classical hypothesis testing. In classing hypothesis testing one can draw conclusion during the data collection and final conclusion can possible be reached at a later stage, whereas sequential analysis are easy to see as data collection can be terminated after fewer cases and decision taken earlier stage, thus saving in terms of reliability of software. In this paper we proposed the performance of sequential probability ratio test (SPRT) on time domain data using exponential model and analyzed the result by applying on 3 data sets. The parameters are estimated using Modified Maximum likelihood estimation.

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“…The algorithm has been implemented in several power system identification such as dynamic state estimation [56], frequency estimation [57], and fault detection [58]. Adaptive KF techniques that use modal analysis and parametric AR models have been applied to on-line estimation of electromechanical modes using PMUs.…”

Section: Kalman Filtering (Kf)mentioning

confidence: 99%

Survey on power system stabilizers control and their prospective applications for power system damping using Synchrophasor‐based wide‐area systems

Chompoobutrgool

Vanfretti

Ghandhari

2011

Int Trans Elec Energy Syst

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Power system oscillation damping remains as one of the major concerns for secure and reliable operation of large power systems, and is of great current interest to both industry and academia. The principal reason for this is that the inception of poorly-damped low-frequency inter-area oscillations (LFIOs) when power systems are operating under stringent conditions may lead to systemwide breakups or considerably reduce the power transfers over critical corridors. With the availability of high-sampling rate phasor measurement units (PMUs), there is an increasing interest for effectively exploiting conventional damping control devices, such as power system stabilizers (PSSs), by using these measurements as control input signals. In this paper, we provide a comprehensive overview of distinct elements (or "building blocks") necessary for wide-area power system damping using synchrophasors and PSSs. These building blocks together shape a tentative methodical framework, and are disposed as follows: (1) fundamental understanding of the main characteristics of inter-area oscillations, (2) wide-area measurement and control systems (WAMS and WACS) and wide-area damping control (WADC), (3) advanced signal processing techniques for mode property identification, (4) methods for model-based small-signal analysis, (5) control input signals selection, and (6) methods for PSS control design. We also describe the latest developments in the implementation of synchrophasor measurements in WAMS and WACS as well as their prospectives for WADC applications. This paper serves both to abridge the state-of-the-art in each of these elements, and to accentuate aspiring ideas in each building block.

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Power system fault detection and state estimation using Kalman filter with hypothesis testing

Cited by 53 publications

References 9 publications

Abrupt change detection of fault in power system using independent component analysis

Abrupt change detection of fault in power system using independent component analysis

An SPRT Procedure for an Ungrouped Data using MMLE Approach

Survey on power system stabilizers control and their prospective applications for power system damping using Synchrophasor‐based wide‐area systems

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