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) |
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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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