Fault classification and mitigation in grid-connected solar PV system using hybrid whale optimization algorithm with ANFIS

Generally, fault mitigation and classification technique has become an important issue in grid-connected PV (GCPV) systems. This study intends a control topology for fault grouping and mitigation scheme in GCPV systems. Whale optimization algorithm (WOA)-ANFIS controllers are applied to uphold the DC-link voltage in UPQC as a perpetual limit. The ANFIS algorithm is employed to attain the apprising procedure of the WOA. The ANFIS controller is working based on the ANN (Artificial Neural Network) and FIS (Fuzzy Interference system). Additionally, the fault classification is proposed in this paper. The fault classification is attained through the use of DWT and ANFIS. Initially, the normal signals are analyzed; the fault is created and extracted in the consumption of DWT. Then the extracted characteristics are fed to the ANFIS for classification. The ANFIS classified faults in the consumption of fuzzy rules. The goals of the projected model are to classify and mitigate the faults in GCPV systems. The projected system is executed using MATLAB/Simulink. So as to investigate the efficacy of the projected technique, the several categories of concerns are examined and verified with the prevailing tactics for instance, UPQC with PSO-ANFIS, UPQC with WOA-ANN method.