SHARMILA SUMSUROOAH Sharmila.Sumsurooah@nottingham.ac.uk
Assistant Professor
A modeling methodology for robust stability analysis of nonlinear electrical power systems under parameter uncertainties
Sumsurooah, Sharmila; Odavic, Milijana; Bozhko, Serhiy
Authors
Milijana Odavic
Professor SERHIY BOZHKO serhiy.bozhko@nottingham.ac.uk
Professor of Aircraft Electric Power Systems
Abstract
This paper develops a modelling method for robust stability analysis of non-linear electrical power systems over a range of operating points and under parameter uncertainties. Standard methods can guarantee stability under nominal condi¬tions but do not take into account any uncertainties of the model. In this work, stability is assessed by using structured singular value (SSV) analysis also known as analysis. This method provides a measure of stability robustness of linear systems against all considered sources of structured uncertainties. The aim of this work is to apply the SSV method for robust small-signal analysis of non-linear systems over a range of operating points and parameter variations. To that end, a modelling methodology is developed to represent any such system with an equivalent linear model that contains all system variabil¬ity, in addition to being suitable for analysis. The method employs symbolic linearisation around an arbitrary operating point. Furthermore, in order to reduce conservativeness in the stability assessment of the non-linear system, the approach takes into account dependencies of operating points on parameter variations. The methodology is verified through analysis of the equivalent linear model of a 4 kW permanent magnet machine drive, which successfully predicts the destabilising torque over a range of different operating points and under parameter variations. Further, the predictions from analysis are validated against experimental results.
Citation
Sumsurooah, S., Odavic, M., & Bozhko, S. (2016). A modeling methodology for robust stability analysis of nonlinear electrical power systems under parameter uncertainties. IEEE Transactions on Industry Applications, 52(5), 4416-4425. https://doi.org/10.1109/TIA.2016.2581151
Journal Article Type | Article |
---|---|
Acceptance Date | May 28, 2016 |
Online Publication Date | Jun 15, 2016 |
Publication Date | Sep 1, 2016 |
Deposit Date | Oct 20, 2016 |
Publicly Available Date | Oct 20, 2016 |
Journal | IEEE Transactions on Industry Applications |
Print ISSN | 0093-9994 |
Electronic ISSN | 1939-9367 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 52 |
Issue | 5 |
Pages | 4416-4425 |
DOI | https://doi.org/10.1109/TIA.2016.2581151 |
Keywords | Robust stability analysis, Linear fractional transformation, Structured singular value, analysis |
Public URL | https://nottingham-repository.worktribe.com/output/975284 |
Publisher URL | http://ieeexplore.ieee.org/document/7492245/ |
Additional Information | 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works |
Contract Date | Oct 20, 2016 |
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