Abstract
Voltage stability is the ability of a power system to maintain acceptable voltage at all buses in the system under normal conditions and after being subjected to a disturbance. Itis important to keep the power system stable to avoid network failure or collapse. Recently years, it is reported that many major network failure occurs due to voltage instability. In case of that, voltage stability has become one of the major concerns in planning and operating of electrical power system. This problem has inspired researchers to seek for the solutions. One of effective way is by applying early prediction or on-line prediction of system's stability. This thesis has come up with new technique to predict the voltage stability condition of a power system. The proposed technique is using Genetic Algorithms-Based Machine Learning (GBML) to predict the voltage stability index. However researchers keep searching for most effective technique to predict the stability index.
Metadata
Item Type: | Thesis (Degree) |
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Creators: | Creators Email / ID Num. Mohd Ghazali, Zainab UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Abdul Rahman, Titik Khawa UNSPECIFIED |
Subjects: | Z Bibliography. Library Science. Information Resources > Information in specific formats or media > Electronic information resources > Computer network resources |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering |
Programme: | Bachelor of Electrical Engineering (Hons.) |
Keywords: | Voltage stability, power system, network failure |
Date: | 2007 |
URI: | https://ir.uitm.edu.my/id/eprint/84572 |
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