@inproceedings{17cc27e74a4e4715b9bfad674b059a2f,
title = "Online voltage stability monitoring of distribution system using optimized Support Vector Machine",
abstract = "Voltage stability monitoring plays a significant role in secure and reliable operation of modern power systems. In this paper, two methods, (i) Particle Swarm Optimization (PSO) based Support Vector Machine (PSO-SVM) and (ii) Genetic Algorithm (GA) based Support Vector Machine (GA-SVM) is proposed for online voltage stability monitoring of distribution system. The optimal values of SVM parameters are obtained using PSO and GA algorithms. Comparison between proposed PSO-SVM and GA-SVM model are investigated on IEEE 33-bus radial distribution system. The results show that the PSO-SVM model for online voltage stability monitoring is more precise than GA-SVM.",
keywords = "Distribution system, Genetic algorithm, Machine learning, Particle swarm optimization, Support vector machine, Voltage stability",
author = "Akanksha Shukla and Kusum Verma and Rajesh Kumar",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 6th IEEE International Conference on Power Systems, ICPS 2016 ; Conference date: 04-03-2016 Through 06-03-2016",
year = "2016",
month = oct,
day = "5",
doi = "10.1109/ICPES.2016.7584132",
language = "English",
series = "2016 IEEE 6th International Conference on Power Systems, ICPS 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 IEEE 6th International Conference on Power Systems, ICPS 2016",
address = "United States",
}