Khaled Abduesslam. M and Mohammed Ali and Basher H Alsdai and Muhammad Nizam and Inayati
Voltage Problem Location Classification Using Performance of Least Squares Support Vector Machine LSSVM and Learning Vector Quantization LVQ
1328 - 1332
2014
8
8
International Journal of Electrical and Computer Engineering
https://publications.waset.org/pdf/9999499
https://publications.waset.org/vol/92
World Academy of Science, Engineering and Technology
This paper presents the voltage problem location
classification using performance of Least Squares Support Vector
Machine (LSSVM) and Learning Vector Quantization (LVQ) in
electrical power system for proper voltage problem location
implemented by IEEE 39 bus New England. The data was collected
from the time domain simulation by using Power System Analysis
Toolbox (PSAT). Outputs from simulation data such as voltage, phase
angle, real power and reactive power were taken as input to estimate
voltage stability at particular buses based on Power Transfer Stability
Index (PTSI).The simulation data was carried out on the IEEE 39 bus
test system by considering load bus increased on the system. To verify
of the proposed LSSVM its performance was compared to Learning
Vector Quantization (LVQ). The results showed that LSSVM is faster
and better as compared to LVQ. The results also demonstrated that the
LSSVM was estimated by 0 misclassification whereas LVQ had
7.69 misclassification.
Open Science Index 92, 2014