Discrete Teager-Huang based Fault Diagnosis in multiple PV Based DC microgrid

Recently., photovoltaic (PV) based DC microgrids have gained popularity because of their availability in nature. Despite its numerous advantages, they are facing protection issues, particularly during fault. In order to protect the microgrid, this paper offers an innovative approach for identifying faults in the proposed DC microgrid. It is accomplished by integrating two well-known algorithms, such as discrete Teager energy (DTEO) and Hilbert-Huang transform (HHT) and it is is named as DT-H. Here, HHT is used to estimate the instantinous frequency and amplitude by utilizing the decomposition process. Further, these two parameters are utilized to estimate the energy using TEO. Generally, TEO exhibits large amplitude at the fault instant, that is why it is used for fault detection. Especially, it shows more accurate results whenever it is subjected to discretization. As a result, it is easier to diaognosis the fault within a very few samples using first peak of the DTEO. Therfore, the proposed method is used to attain quick and accurate fault diagnosis during PV and load uncertainties. The proposed algorithm is compared to state-of-the-art techniques to demonstrate its superiority. Here, DT-H is evidenced its superioty in terms of detection time. The entire process have been performed in the MATLAB/Simulink platform.