Application of Kalman filtering in computer relaying of power systems Girgis, Adly
dc.contributor.department Electrical and Computer Engineering 2018-08-17T12:50:18.000 2020-07-02T05:58:49Z 2020-07-02T05:58:49Z Thu Jan 01 00:00:00 UTC 1981 1981
dc.description.abstract <p>Kalman-filter models for the optimal estimation of the post-fault currents and voltages for computer relaying purposes of power systems are presented. As a prerequisite for the Kalman-filtering implementation, the random description of the fault-induced noise signals was quantitatively studied. Empirical formulas that describe the random nature of the noise based on the probability of fault location and the frequency of occurrence of the different types of faults are given. These empirical formulas offer the possibility of developing other new techniques in computer relaying of power systems;Sensitivity of the Kalman filters to incorrect model parameters was studied through extensive simulation. A Kalman-filtering-based digital distance relay was designed to detect, classify, and locate faults in a high voltage transmission line in the shortest period of time;Comparison of the developed technique with four other algorithms demonstrated that the Kalman-filtering-based algorithm is superior to other techniques in the rate of convergence to the exact values, accuracy, and computer burden. Thus the Kalman-filtering approach appears to be especially well-suited to the power system protection problem.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 8167
dc.identifier.contextkey 6305007
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/7168
dc.language.iso en
dc.source.bitstream archive/|||Sat Jan 15 01:43:23 UTC 2022
dc.subject.disciplines Electrical and Electronics
dc.subject.disciplines Oil, Gas, and Energy
dc.subject.keywords Veterinary physiology
dc.subject.keywords Electrical engineering
dc.title Application of Kalman filtering in computer relaying of power systems
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication a75a044c-d11e-44cd-af4f-dab1d83339ff dissertation Doctor of Philosophy
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