Enhancing the performance of the power system state estimate

Hatim Ghadhban Abood

doi:10.4225/23/5ae29ebc66b62

Enhancing the performance of the power system state estimate

Hatim Ghadhban Abood

School of Engineering

Research output: Thesis › Doctoral Thesis

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Abstract

This thesis addresses the problems that affect the accuracy and the numerical stability of the power system state estimation (PSSE). The enhancement of the PSSE is implemented in this thesis using four methodologies. The first solution method
Improves the conventional WLS state estimator using a regularisation technique. The other three methodologies aim to enrich
the measurement set using accurate meters which are the phasor measurement units (PMUs). The PMUs are allocated using
a meta-heuristic technique (the river formation dynamics (RFD)), a statistical analysis to the variance Inflation factors (VIF), and
the Cuckoo search optimisation with identifying the leverage measurements.

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	The University of Western Australia
Supervisors/Advisors	Sreeram, Victor, Supervisor Mishra, Yateendra, Supervisor
Award date	6 Apr 2018
DOIs	https://doi.org/10.4225/23/5ae29ebc66b62
Publication status	Unpublished - 2018

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THESIS - DOCTOR OF PHILOSOPHY - ABOOD Hatim Ghadhban - 2018
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Cite this

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title = "Enhancing the performance of the power system state estimate",

abstract = "This thesis addresses the problems that affect the accuracy and the numerical stability of the power system state estimation (PSSE). The enhancement of the PSSE is implemented in this thesis using four methodologies. The first solution methodImproves the conventional WLS state estimator using a regularisation technique. The other three methodologies aim to enrichthe measurement set using accurate meters which are the phasor measurement units (PMUs). The PMUs are allocated usinga meta-heuristic technique (the river formation dynamics (RFD)), a statistical analysis to the variance Inflation factors (VIF), andthe Cuckoo search optimisation with identifying the leverage measurements.",

keywords = "Power system state estimation, Phasor measurements (PMU), Power system monitoring, Power transmission systems, Power distribution systems, Weighted least squares, Non-linear regression",

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language = "English",

school = "The University of Western Australia",

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N2 - This thesis addresses the problems that affect the accuracy and the numerical stability of the power system state estimation (PSSE). The enhancement of the PSSE is implemented in this thesis using four methodologies. The first solution methodImproves the conventional WLS state estimator using a regularisation technique. The other three methodologies aim to enrichthe measurement set using accurate meters which are the phasor measurement units (PMUs). The PMUs are allocated usinga meta-heuristic technique (the river formation dynamics (RFD)), a statistical analysis to the variance Inflation factors (VIF), andthe Cuckoo search optimisation with identifying the leverage measurements.

AB - This thesis addresses the problems that affect the accuracy and the numerical stability of the power system state estimation (PSSE). The enhancement of the PSSE is implemented in this thesis using four methodologies. The first solution methodImproves the conventional WLS state estimator using a regularisation technique. The other three methodologies aim to enrichthe measurement set using accurate meters which are the phasor measurement units (PMUs). The PMUs are allocated usinga meta-heuristic technique (the river formation dynamics (RFD)), a statistical analysis to the variance Inflation factors (VIF), andthe Cuckoo search optimisation with identifying the leverage measurements.

KW - Power system state estimation

KW - Phasor measurements (PMU)

KW - Power system monitoring

KW - Power transmission systems

KW - Power distribution systems

KW - Weighted least squares

KW - Non-linear regression

U2 - 10.4225/23/5ae29ebc66b62

DO - 10.4225/23/5ae29ebc66b62

M3 - Doctoral Thesis

ER -

Enhancing the performance of the power system state estimate

Abstract

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