Neural Network Based Fault Detection Location and Classification in Microgrid in MATLAB | Fault
Understanding Fault Detection in Microgrids
Overview of DC Load and Power Sources
The discussion begins with the scope of providing information about DC load, including power sources such as grid solar PV, battery, diesel power, and AC load power.
Fault Detection Process
A fault is created at 0.1 seconds into the process; it is detected as an A-B-G fault (double line to ground fault).
The fault location value is approximately 9.2 km from the grid side microgrid, indicating proximity to where the fault occurred.
Classification and Location Finding
The speaker changes a parameter to 5 km to check if the system can accurately detect the fault location.
After waiting for some time post-fault creation, classification occurs; initial detection shows values around 4.4 km to 4.6 km but confirms that the actual fault was at 5 km.
Neural Network Application
Video description
Neural Network Based Fault Detection Location and Classification in Microgrid in MATLAB | Fault
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