A deep CNN approach for islanding detection of integrated DG with time series data and scalogram

The ever increasing demand for electricity leads to the advancement of distributed generation (DG). Almost all DG sources are renewable nature. One major complications with high penetration is islanding. islanding may damage clients and their equipment. As per IEEE 1547 interconnection standards, will be identified in two seconds must turned off. In this paper, an advanced detection process stands on a deep learning technique continuous wavelet transforms convolution neural networks implemented. This approach time series information into scalogram images, later, images used train test non-islanding events. outcomes correlated artificial fuzzy logic methods. comparison shows that proposed efficiently detects