Abstract
Summary This paper presents a novel approach for intelligent islanding detection in a multi-machine distribution network using the Adaptive Boosting (AdaBoost) algorithm. The AdaBoost algorithm is an iterative procedure that improves the accuracy of classification models by combining multiple base classifiers. In this paper, two different case studies are specified so as to assess the performance of the AdaBoost in islanding detection. In order to train the AdaBoost algorithm, various scenarios are implemented in the case studies. A number of electrical parameters including frequency and voltage are utilized as a feature vector to describe the designed scenarios. In order to determine the accuracy of AdaBoost in detecting the islanding phenomenon, the proposed method is subsequently tested in further scenarios. Response time and non-detection zone of the suggested method are also evaluated in the case studies as the two other main criteria. The results indicate that this method can successfully detect islanding operation in a variety of operating states in the networks under study. All the simulations presented here are produced in the Simulink toolbox of MATLAB. Copyright © 2015 John Wiley & Sons, Ltd.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Transactions on Electrical Energy Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
