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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Castillo, M.R.M. London, J.B.A. Bretas, N.G. |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Electrical Engineering, E.E.S.C.-University of São Paulo, 13560-480, Brazil (Castillo, M.R.M.; London, J.B.A.; Bretas, N.G.) |
| Abstract | A practical and efficient off-line approach to detect, identify and correct series and shunt branch parameter errors is proposed. The branches suspected to be with parameters errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements incident to that branch, whose normalized residuals are larger than one specified threshold value, and the total number of measurement incident to that branch. Using several measurements snapshots, the suspicious branches parameters are estimated, in a sequential form, via an augmented state and parameter estimator which increases the V-θ state vector for the inclusion of suspicious branch parameters. Several simulation results (with the IEEE 14, 30 and 57 bus systems) have demonstrated the high accuracy and reliability of the proposed approach to lead with single and multiple parameter errors in adjacent and non-adjacent branches. |
| Starting Page | 1 |
| Ending Page | 7 |
| File Size | 427369 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424465491 |
| ISSN | 19449925 |
| e-ISBN | 9781424465514 |
| e-ISBN | 9781424483570 |
| DOI | 10.1109/PES.2010.5589552 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-07-25 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Transmission line measurements Parameter estimation Power measurement Mathematical model State estimation Fluid flow measurement Measurement uncertainty Parameter Estimation Power Systems State Estimation Parameter Error Detection |
| Content Type | Text |
| Resource Type | Article |
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