Voltage Instability Analysis Based On Adaptive Neuro-Fuzzy Inference System And Probabilistic Neural Network

Mohamad Nor, Ahmad Fateh and Sulaiman, Marizan and Abdul Kadir, Aida Fazliana and Omar, Rosli (2018) Voltage Instability Analysis Based On Adaptive Neuro-Fuzzy Inference System And Probabilistic Neural Network. Journal of Engineering and Technology, 9 (2). pp. 1-13. ISSN 2180-3811

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Abstract

This paper presents the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Probabilistic Neural Network (PNN) for voltage instability analysis in electric power system. The voltage instability analysis is executed in this research by calculating the values of voltage instability indices. The voltage instability indices used are voltage stability margin (VSM) and load power margin (LPM). Both VSM and LPM are obtained from the real power-voltage (PV) curve and reactive power-voltage (QV) curve. ANFIS is used for predicting the values of voltage instability indices. Meanwhile, PNN is used for classifying the voltage instability indices. The IEEE 14-bus test system has been chosen as the reference electrical power system. Both ANFIS and PNN used in this research are deployed by using MATLAB software.

Item Type:	Article
Uncontrolled Keywords:	Voltage instability analysis, Voltage and load power margin, Probabilistic neural network, ANFIS, Voltage Instability, Adaptive Neuro-Fuzzy Inference System
Divisions:	Faculty of Electrical Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	08 Dec 2020 11:40
Last Modified:	08 Dec 2020 11:40
URI:	http://eprints.utem.edu.my/id/eprint/24548
Statistic Details:	View Download Statistic

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