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Classifications of voltage stability margin (VSM) and load power margin (LPM) using probabilistic neural network (PNN)

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Title: Classifications of voltage stability margin (VSM) and load power margin (LPM) using probabilistic neural network (PNN)

Authors: Ahmad Fateh Mohamad Nor, Marizan Sulaiman, Aida Fazliana Abdul Kadirand, Rosli Omar

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2017

Volume: 12

Issue: 19

Language: English

Categories
Electrical Engineering (5972) Neural Networks (134) Load Flow Analysis (4) Voltage Stability (8) Power Systems (548)

Abstract

Voltage stability margin (VSM) and load power margin (LPM) arethe indicators that show how close a load bus is to experiencing voltage instability. The smaller the values of VSM or LPM of a particular load bus, the closer the load bus towards voltage instability. This paper presents the application of probabilistic neural network (PNN) for classifying VSM and LPM values. A number of training data is generated for the PNN model to classify. The PNN model used in this paper should be able to classify which values are within VSM/LPM values and which values are not. The IEEE 14-bus system has been chosen as the reference electrical power system. MATLAB is used to deploy the PNN model for VSM and LPM classifications.

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