Voltage Stability Analysis Of Load Buses In Electric Power System Using Adaptive Neuro-Fuzzy Inference System (Anfis) And Probabilistic Neural Network (Pnn)

Mohamad Nor, Ahmad Fateh and Sulaiman , Marizan and Abdul Kadir, Aida Fazliana and Omar, Rosli (2017) Voltage Stability Analysis Of Load Buses In Electric Power System Using Adaptive Neuro-Fuzzy Inference System (Anfis) And Probabilistic Neural Network (Pnn). ARPN Journal Of Engineering And Applied Sciences, 12 (5). pp. 1406-1412. ISSN 1819-6608

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Abstract

This paper presents the application of neural networks for analysing voltage stability of load buses in electric power system. Voltage stability margin (VSM) and load power margin (LPM) are used as the indicators for analyzing voltage stability. The neural networks used in this research are divided into two types. The first type is using the neural network to predict the values of VSM and LPM. Multilayer perceptron back propagation (MLPBP) neural network and adaptive neuro-fuzzy inference system (ANFIS) will be used. The second type is to classify the values of VSM and LPM using the probabilistic neural network (PNN). The IEEE 30-bus system has been chosen as the reference electrical power system. All of the neural network-based models used in this research is developed using MATLAB.

Item Type:	Article
Uncontrolled Keywords:	voltage stability analysis, voltage and load power margin, artificial neural network, probabilistic neural network, ANFIS.
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics
Divisions:	Faculty of Electrical Engineering
Depositing User:	Nor Aini Md. Jali
Date Deposited:	13 Jul 2017 07:44
Last Modified:	21 Jul 2021 23:36
URI:	http://eprints.utem.edu.my/id/eprint/18656
Statistic Details:	View Download Statistic

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