Abstract
The main of this study is to analyze recent detection methodologies of unintentional islanding in distributed generation of electric energy. This research focuses the use of supervised Learning Techniques and demonstrates that the use of these methodologies can achieve a performance superior to the conventional passive methods of islanding detection due to nondetection relays zones. A theoretical approach is taken on the international and national standards that prohibit the islanding occurrence, and the risk and damages due to this. Next, techniques for islanding detection are discussed, and comments about advantages and disadvantages of them are presented. A Simulation of Islanding and Non-Islanding operating states in a distribution system with Distributed Generation using the Simulink software is performed. The data obtained with this simulation is used to train an Artificial Neural Network (ANN or RNA) and make this grid able to identify the real system operating state.
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