Classifications of voltage stability margin (VSM) and load power margin (LPM) using probabilistic neural network (PNN)
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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Asian Research Publishing Network (ARPN)
2017
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/2461/1/AJ%202019%20%2825%29.pdf http://eprints.uthm.edu.my/2461/ http://www.arpnjournals.com/jeas/volume_19_2017.htm |
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| Institution: | Universiti Tun Hussein Onn Malaysia |
| Language: | English |
| Summary: | 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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