• Krati Sharma
• Ms. Apurva Vashishth
• Ms. Manju Mathur

In power systems, defensive devices can distinguish fault conditions and work circuit breakers and different devices to restrict the deficiency of administration because of a disappointment. In light of the counterfeit neural network , the fault discovery of microgrid was contemplated. A limited scale demonstrating of the microgrid including sunlight powered chargers , battery energy stockpiling system, burdens and AC framework is recreated in MATLAB. An unexpected change in the worth of auxiliary current ISec and the heap power PL is the reason for the calculation that identify the fault area. Here we notice the spikes in the diagram of ISec as the faults .These faults are created physically by turning on every one of the circuit breakers at different snapshots of a day . Likewise the faults were concentrated by keeping just as separating the battery regulator. Having created the information at different occasions of a day and preparing the dataset in ANN brought a respectable exactness of (70%~80 %). So having new information of power, ISec and time, we can anticipate in case there is a fault or not , and in case there is , the area of the fault not set in stone pretty precisely.

Fault Detection , Circuit Breakers , ANN

"Novel Concept of Fault Detection using ANN and 3 Circuit Breakers", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 11, page no.a291-a300, November-2021, Available :http://www.jetir.org/papers/JETIR2111041.pdf

"Novel Concept of Fault Detection using ANN and 3 Circuit Breakers", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 11, page no. ppa291-a300, November-2021, Available at : http://www.jetir.org/papers/JETIR2111041.pdf