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

Text
AJ 2019 (23).pdf
Restricted to Registered users only
Download (384kB) | Request a copy

Official URL: http://www.arpnjournals.com/jeas/volume_05_2017.ht...

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 analysing 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:	T Technology > T Technology (General)
Divisions:	Faculty of Electrical and Electronic Engineering > Department of Electrical Engineering
Depositing User:	Miss Afiqah Faiqah Mohd Hafiz
Date Deposited:	20 Oct 2021 03:19
Last Modified:	20 Oct 2021 03:19
URI:	http://eprints.uthm.edu.my/id/eprint/2456

Actions (login required)

View Item