Passive Islanding Detection for Distributed Generation Using Decision Tree Algorithm, M.Sc. Thesis Sharif University of Technology ; Abbaspour Tehrani Fard, Ali (Supervisor) ; Ranjbar, Ali Mohammad (Supervisor)
Abstract
The integration of renewable energy sources introduces several issues including islanding operation. Therefore, Islanding phenomenon should be detected by a fast and reliable islanding detection method. In this thesis an intelligent-based approach is proposed to detect islanding state for Photovoltaic (PV) and Doubly Fed Induction Generator (DFIG) units. Decision tree classification algorithm is chosen as weak classifier and by Adaptive Boosting (AdaBoost), detection accuracy is improved. 16 features are employed to construct feature vectors. Because of intermittency of renewable electricity generation, different states for PV and DFIG generation are assumed. Probable events are simulated...
Cataloging briefPassive Islanding Detection for Distributed Generation Using Decision Tree Algorithm, M.Sc. Thesis Sharif University of Technology ; Abbaspour Tehrani Fard, Ali (Supervisor) ; Ranjbar, Ali Mohammad (Supervisor)
Abstract
The integration of renewable energy sources introduces several issues including islanding operation. Therefore, Islanding phenomenon should be detected by a fast and reliable islanding detection method. In this thesis an intelligent-based approach is proposed to detect islanding state for Photovoltaic (PV) and Doubly Fed Induction Generator (DFIG) units. Decision tree classification algorithm is chosen as weak classifier and by Adaptive Boosting (AdaBoost), detection accuracy is improved. 16 features are employed to construct feature vectors. Because of intermittency of renewable electricity generation, different states for PV and DFIG generation are assumed. Probable events are simulated...
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