Efficient identification of critical parameters affecting the small-disturbance stability of power systems with variable uncertainty

Hasan, K, Preece, R and Milanovic, J 2016, 'Efficient identification of critical parameters affecting the small-disturbance stability of power systems with variable uncertainty', in Proceedings of the 2016 IEEE Power and Energy Society General Meeting (PESGM 2016), Boston, United States, 17-21 July 2016, pp. 741-745.


Document type: Conference Paper
Collection: Conference Papers

Title Efficient identification of critical parameters affecting the small-disturbance stability of power systems with variable uncertainty
Author(s) Hasan, K
Preece, R
Milanovic, J
Year 2016
Conference name PESGM 2016
Conference location Boston, United States
Conference dates 17-21 July 2016
Proceedings title Proceedings of the 2016 IEEE Power and Energy Society General Meeting (PESGM 2016)
Publisher IEEE
Place of publication United States
Start page 741
End page 745
Total pages 5
Abstract This paper implements an efficient sensitivity analysis (SA) technique to identify and rank critically important uncertain parameters that affect the small-disturbance stability of a power system. Identification and ranking of uncertain parameters are vital in modern power system operation due to the adoption of deregulated market structure and integration of intermittent energy resources and new types of loads. Ranking of critical uncertain parameters will facilitate better operation and control with less monitoring (targeted only on the parameters of interest) by system operators and stakeholders. The Morris screening method of sensitivity analysis has been described and implemented in this paper as the most suitable for this study based on comparison with various local and global techniques which highlighted the their comparative computational complexities and simulation time requirements. All methods have been illustrated using a modified version of the 68 bus NET-SNYPS test system. Illustrative results are provided considering varying levels of parameter uncertainties in order to establish not only the impact of system variability on parameter ranking, but also the robustness of the presented technique.
Subjects Renewable Power and Energy Systems Engineering (excl. Solar Cells)
Keyword(s) Computational efficiency
power system analysis computing
probability distribution
sensitivity analysis
small-signal stability
uncertainty
DOI - identifier 10.1109/PESGM.2016.7741291
Copyright notice © 2016 IEEE
ISBN 9781509041695
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