@inproceedings{1aa2eda665754391a8d9805f5b7bfcaf,
title = "Islanding detection for multi DG system using inverter based DGs",
abstract = "in this paper a multiple distributed-generation (DG) system was used to test the proposed islanding detection technique for grid-mode distributed-generation (DG). Twenty one features are extracted from measurement of the voltage and frequency at the point of common coupling (PCC) in order to identify islanding occurrence with high accuracy. An IEEE 34-bus system was used in this paper to generate islanding and non-islanding cases. Multiple locations for the DGs were used and also multiple DGs were also connected. Na{\"i}ve Bayes Classifier then was used to discriminate between islanding and non-islanding. In order to test the accuracy of the Na{\"i}ve Bayesian Classifier, Cross-Validation was used to evaluate the performance of the proposed islanding detection technique. Also, the algorithm was tested against Support Vector Machine (SVM). The results show the superiority of the Na{\"i}ve Bayes Classifier over the SVM.",
keywords = "Cross Validation, inverter-based distributed generator, islanding detection, Na{\"i}ve Bayes, power systems, Support Vector Machine, WEKA",
author = "Faqhruldin, \{Omar N.\} and El-Saadany, \{E. F.\} and Zeineldin, \{H. H.\}",
year = "2013",
doi = "10.1109/PESMG.2013.6672262",
language = "British English",
isbn = "9781479913039",
series = "IEEE Power and Energy Society General Meeting",
booktitle = "2013 IEEE Power and Energy Society General Meeting, PES 2013",
note = "2013 IEEE Power and Energy Society General Meeting, PES 2013 ; Conference date: 21-07-2013 Through 25-07-2013",
}