ANFIS MPPT Assisted PV Fed DC-DC Switched Z Source Converter For Microgrid Applications

Photovoltaic (PV) modules are crucial components of contemporary distribution networks, but they have historically been employed primarily to provide profitable, clean, and green energy. An Adaptive Neuro Fuzzy Inference System (ANFIS) is described in this study as a technique for MPP prediction using information on solar interaction and ambient temperature. The proposed technique has the benefits of a quick reaction, overall harmonic distortion discount, more effective utilization of PV units, and straightforward ANFIS algorithm training. An innovative type of large step up DC to DC converter is produced by combining the switched-capacitor cells by a conventional Z-source impedance network. The recommended converter delivers a great voltage gain lacking the limited accountability sequence and does not necessitate an enormous quantity of modules while decreasing a voltage heaviness on the diodes and the control switch to fewer than partial the productivity power. The performance and application of the recommended converter are established by the simulation and experimental findings. The comparison of the controllers shows the superior MPPT effectiveness of ANFIS as 92.3%.