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

Mohamad Nor, Ahmad Fateh and Sulaiman, Marizan and Abdul Kadir, Aida Fazliana and Omar, Rosli (2017) Classifications of voltage stability margin (VSM) and load power margin (LPM) using probabilistic neural network (PNN). ARPN Journal of Engineering and Applied Sciences, 12 (19). pp. 5591-5596. ISSN 18196608

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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.

Item Type: Article
Uncontrolled Keywords: Voltage stability analysis; voltage stability margin; load power margin; artificial neural network; probabilistic neural network
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001-1841 Production of electric energy or power. Powerplants. Central stations
Divisions: Faculty of Electrical and Electronic Engineering > Department of Electrical Power Engineering
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 30 Sep 2019 02:58
Last Modified: 30 Sep 2019 02:58
URI: http://eprints.uthm.edu.my/id/eprint/11534
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