Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus

Darus, Zamzuhairi (2003) Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus. Degree thesis, Universiti Teknologi MARA (UiTM).

Abstract

Voltage stability problems have been one of the major concerns for electric utilities as a result of a system heavy loading. This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). Analysis and evaluation of the voltage stability, it is necessary to accurately identify the stability margin at each load point under specific system configuration or power balance condition. In the analysis and evaluation of voltage stability, it is necessary to accurately identify the stability margin at each load point under specified system configuration or power balance condition. Voltage stability margin (VSM) can be basically identified by the multi-solution load flow calculation method. A systematic method for selecting the ANN's input variables was developed using Matlab Programming language.

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email / ID Num.
Darus, Zamzuhairi
2003328095
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Abdul Rahman, Titik Khawa
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Evolutionary programming (Computer science). Genetic algorithms
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Programme: Bachelor of Electrical Engineering (Hons)
Keywords: Voltage stability, evolution programming, heavy loading
Date: 2003
URI: https://ir.uitm.edu.my/id/eprint/78498
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