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Design and development of intelligent computational techniques for power quality data monitoring and management

Paracha, Zahir Javed (2011) Design and development of intelligent computational techniques for power quality data monitoring and management. PhD thesis, Victoria University.

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Abstract

The most important requirement of power system operations is sustained availability and quality supply of electric power. In Electrical Power Distribution System (EPDS), non-linear loads are the main cause of power quality (PQ) degradation. The PQ problems generated by these non-linear loads are complex and diversified in nature. The power system which is not capable to handle non-linear loads faces the problem of voltage unbalance, sag, swell, momentary or temporary interruption and ultimately complete outage of EPDS. The PQ problems have motivated power system engineers to design and develop new methodologies and techniques to enhance EPDS performance. To do so, they are required to analyse the PQ data of the system under consideration. Since, the density of the monitoring nodes in EPDS is quite high, the aggregate analysis is computationally involved. In addition, the cost involved with the PQ shortcomings is significantly high (for domestic consumers and rises exponentially for industrial consumers), hence it also becomes mandatory to project /predict the undesired PQ disturbance in EPDS. This will provides power system engineers to formulate intelligent strategy for efficient power system operations. This objective of the research is to identify and exploit the hidden correlation in PQ data with minimal computational cost and further use this knowledge to classify any PQ disturbance that may occur. ... Further this research also investigates the power distribution system behaviour considering the relationship of main PQ disturbance harmonics in conjunction with the other major PQ parameters i.e. voltage unbalance, sag, swell and frequency.

Item Type: Thesis (PhD thesis)
Uncontrolled Keywords: power quality disturbance, electrical power, electricity, power system, power distribution, power grid, electrical energy, energy management, energy efficiency, principal component analysis technique model, PCAT, mathematical computer models, fuzzy algorithm, clustering, artificial neural network, ANN, United Energy Distribution, Jemena Ltd. Australia, Victoria, Victorian
Subjects: FOR Classification > 0103 Numerical and Computational Mathematics
FOR Classification > 0906 Electrical and Electronic Engineering
Faculty/School/Research Centre/Department > School of Engineering and Science
Depositing User: VU Library
Date Deposited: 09 Feb 2012 05:03
Last Modified: 23 May 2013 16:56
URI: http://vuir.vu.edu.au/id/eprint/19381
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