Voltage stability prediction in power system using artificial neural network / Irfan Hanafi Jamaluddin

Jamaluddin, Irfan Hanafi (2014) Voltage stability prediction in power system using artificial neural network / Irfan Hanafi Jamaluddin. Degree thesis, Universiti Teknologi MARA (UiTM).


Voltage instability has become one of the sudden interest in modem power system industry since it can initiate a critical event called voltage collapse or blackout in a system. Therefore, voltage stability management is vital in order to avoid loss of power and operating cost. This paper presents an application of Fast Voltage Stability Index (FVSI) and Artificial Neural Network (ANN) in determining the voltage stability for IEEE 30-Bus System. In this project, different load variations will be implemented which based on reactive power for voltage stability analysis. FVSI for each line will be calculated and the weakest line which has high value of FVSI and bus which has the lowest voltage will be identified. Next, the overall data from FVSI analysis will be collected and undergo training and testing in a multi-layer Feed Forward ANN for voltage stability determination. The simulation of FVSI and ANN is executed using MATLAB R2011 a software.


Item Type: Thesis (Degree)
Email / ID Num.
Jamaluddin, Irfan Hanafi
Email / ID Num.
Thesis advisor
Zakaria, Zuhaina
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electric power distribution. Electric power transmission
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Programme: Bachelor of Electrical Engineering (Hons)
Keywords: Fast voltage stability index, voltage stability, artificial neural network
Date: 2014
URI: https://ir.uitm.edu.my/id/eprint/78123
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