Application of artificial neural network for voltage stability monitoring / Valerian Shem

Shem, Valerian (2003) Application of artificial neural network for voltage stability monitoring / Valerian Shem. Degree thesis, Universiti Teknologi MARA.

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Abstract

This project is about monitoring the voltage stability of a system bus. Voltage stability problem has been one of the major concerns for electric utilities as a result of system heavy loading and needs to be solved. A 6-system bus is used as input variables, which consists of real power value (PL) and reactive power (QL). This system analyzes the concerned variables and shows the stabilized value for load power (L) as the output. To solve this problem, this simulation implements the Artificial Neural Network approach using both standard back-propagation technique and hybrid technique (standard backpropagation and genetic algorithm (GA)). The latter technique requires GA to find the optimal value for each weight of the neural network. A comparative study is conducted to measure the performance of the neural network using different types of parameters. By completing this project, we should be able to have an idea on how to monitor voltage stability from any system bus and to make machine learns like human does.

Item Type: Thesis (Degree)
Uncontrolled Keywords: Artificial neural network, voltage stability, backpropagation
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic computers.Computer science > Neural networks (Computer science)
Q Science > QA Mathematics > Instruments and machines > Electronic computers.Computer science > Neural networks (Computer science)

T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electric power distribution. Electric power transmission
Divisions: Faculty of Information Technology and Quantitative Sciences
Depositing User: Staf Pendigitan 1
Date Deposited: 28 Dec 2010 06:50
Last Modified: 19 Apr 2017 04:13
URI: http://ir.uitm.edu.my/id/eprint/1003

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