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

• Main Authors: Mohamad Nor, Ahmad Fateh, Sulaiman, Marizan, Abdul Kadir, Aida Fazliana, Omar, Rosli
• Format: Article
• Language: English
• Published: Penerbit Universiti Teknikal Malaysia Melaka 2018
• Online Access: http://eprints.utem.edu.my/id/eprint/24548/2/MARIZAN_104.PDF; http://eprints.utem.edu.my/id/eprint/24548/; https://journal.utem.edu.my/index.php/jet/article/view/2243/VOLTAGE%20INSTABILITY%20ANALYSIS%20BASED%20ON%20ADAPTIVE%20NEURO-FUZZY%20INFERENCE%20SYSTEM
• Institution: Universiti Teknikal Malaysia Melaka

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.