Open AccessIslanding detection of synchronous distributed generators using data mining complex correlations
Author(s) -
Gomes Eduardo A.P.,
Vieira José C.M.,
Coury Denis V.,
Delbem Alexandre C.B.
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.1722
Subject(s) - islanding , computer science , data mining , generator (circuit theory) , fault (geology) , fault detection and isolation , distributed generation , real time computing , artificial intelligence , engineering , power (physics) , renewable energy , electrical engineering , physics , quantum mechanics , seismology , geology , actuator
This study proposes a novel method based on data mining for islanding detection of synchronous distributed generators. The method uses a new technique called data mining of code repositories (DAMICORE), which is a powerful data mining tool for detecting patterns and similarities in various kinds of datasets. In addition, a trip logic was developed in this proposal in order to detect islanding and disconnect the distributed generator. One of the most relevant features of the proposed method is its capability to generalise, which reduces the need of big datasets for training purposes. This approach has been tested with islanding, load switching and fault simulations, presenting promising results concerning performance, as well as detection time. General results showed a better performance of the method if compared to traditional anti‐islanding protection schemes, such as frequency‐based relays.