Fault detection and classification in DC microgrid clusters

Ground Fault Location of Cable Using Wavelet in DC Microgrid

Fault Detection and Location in DC Microgrids by Recurrent Neural Networks and Decision Tree Classifier

Microgrids have played an important role in distribution networks during recent years.  DC microgrids are very popular among researchers because of their benefits. Protection is one of the significant challenges in the way of microgrids progress. As a result, in this paper, a fault detection and location scheme for DC microgrids is proposed. Due to advances in Artificial Intelligence (AI) and s...

A local measurement-based protection scheme for DER integrated DC microgrid using Bagging Tree

In recent years, DC microgrid has attracted considerable attention of the research community because of the wide usage of DC power-based appliances. However, the acceptance of DC microgrid by power utilities is still limited due to the issues associated with the development of a reliable protection scheme. The high magnitude of DC fault current, its rapid rate of rising and absence of zero cros...

Fault Detection in Ring Based Smart LVDC Microgrid Using Ensemble of Decision Tree

In modern infrastructure, the demand for DC power-based appliances is rapidly increasing, and this phenomenon has created a positive impact on the acceptance of the DC microgrid. However, due to numerous issues such as the absence of zero crossing, bidirectional behaviour of sources, and different magnitudes of fault current during grid connected and islanded modes of operation, protecting DC m...

A Novel Fault Detection and Classification Approach in Transmission Lines Based on Statistical Patterns

Symmetrical nature of mean of electrical signals during normal operating conditions is used in the fault detection task for dependable, robust, and simple fault detector implementation is presented in this work. Every fourth cycle of the instantaneous current signal, the mean is computed and carried into the next cycle to discover nonlinearities in the signal. A fault detection task is complete...