Open AccessIslanding detection method for grid connected photovoltaic systems
Author(s) -
Wang Meng Hui,
Huang MeiLing,
Liou KangJian
Publication year - 2015
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2014.0264
Subject(s) - islanding , photovoltaic system , grid , computer science , power (physics) , electronic engineering , artificial neural network , electric power system , novelty , control theory (sociology) , real time computing , engineering , artificial intelligence , electrical engineering , mathematics , philosophy , physics , geometry , theology , control (management) , quantum mechanics
The detection of islanding effect is one of the important issues for photovoltaic (PV) power system since islanding is dangerous to utility equipment and workers, and result in severe injuries and death. The novelty of this study is combining extension neural networks and Chaos synchronisation (CS) on islanding detection of grid connected PV systems based on non‐autonomous Chua's circuit. Combining CS and extension neural network type‐2 (ENN‐2), this research is to propose a novel detection method at detecting and distinguishing the occurrence of islanding effect based on non‐autonomous Chua's circuit. Simulation and experimental designs through powersim (PSIM) were applied to mimic PV power system to demonstrate the effectiveness of the proposed method. Results show that the accuracy of ENN‐2 achieves 98.4% on detecting the islanding effect for PV power system.