Statistical method for identification of sources of electromechanical oscillations in power systems
dc.contributor.advisor
Bialek, Janusz
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dc.contributor.advisor
Djokic, Sasa
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dc.contributor.advisor
Harrison, Gareth
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dc.contributor.author
McNabb, Patrick James
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dc.contributor.sponsor
Engineering and Physical Sciences Research Council (EPSRC)
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dc.contributor.sponsor
Psymetrix
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dc.date.accessioned
2014-10-08T13:21:15Z
dc.date.available
2014-10-08T13:21:15Z
dc.date.issued
2011-06-28
dc.description.abstract
The use of real-time continuous dynamics monitoring often indicates dynamic behaviour
that was not anticipated by model-based studies. In such cases it can be
difficult to locate the sources of problems using conventional tools. This thesis details
the possibility of diagnosing the causes of problems related to oscillatory stability using
measurement-based data such as active power and mode decay time constant, derived
from system models. The aim of this work was to identify dynamics problems independently
of an analytical dynamic model, which should prove useful in diagnosing and
correcting dynamics problems.
New statistical techniques were applied to both dynamic models and real systems which
yielded information about the causes of the long decay time constants observed in these
systems. Wavelet transforms in conjunction with General Linear Models (GLMs) were
used to improve the statistical prediction of decay time constants derived from the
system. Logic regression was introduced as a method of establishing important interactions
of loadflow variables that contribute to poor damping.
The methodology was used in a number of case studies including the 0.62Hz Icelandic
model mode and a 0.48Hz mode from the real Australian system. The results presented
herein confirm the feasibility of this approach to the oscillation source location problem,
as combinations of loadflow variables can be identified and used to control mode
damping. These ranked combinations could be used by a system operator to provide
more comprehensive control of oscillations in comparison to current techniques.
en
dc.identifier.uri
http://hdl.handle.net/1842/9500
dc.language.iso
en
dc.publisher
The University of Edinburgh
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dc.relation.hasversion
McNabb. P, Wilson. D, Bialek. J, ”Dynamic Model Validation of the Icelandic Power System using WAMS based Measurements of Oscillatory Stability” PSCC, Glasgow, 2008
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dc.relation.hasversion
Wilson. D, Hay. K, McNabb. P, Trehern. J, ”Identifying Sources of Damping Issues in the Icelandic Power System”. IEEE.InProceedings, PSCC, Glasgow, 2008.
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dc.relation.hasversion
P. McNabb, N. Bochkina, D. Wilson, J. Bialek ”Oscillation Source Location using Discrete Wavelet Transforms”. IEEE.InProceedings, Transmission and Distribution Conference, New Orleans, 2010.
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dc.relation.hasversion
P. McNabb, N. Bochkina, D. Wilson, J. Bialek ”Oscillation Source Location using Logic Regression”. IEEE.InProceedings, IEEE Smart Grids Europe, Gothenburg, 2010.
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dc.subject
modes of oscillation
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dc.subject
waves
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dc.title
Statistical method for identification of sources of electromechanical oscillations in power systems
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Doctoral
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dc.type.qualificationname
PhD Doctor of Philosophy
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