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This paper proposes an effective AI control technique‐based improved QZS‐CMI topology for interfacing PV system. Generally, the interface between the PV dc source and the load is accomplished by a QZSI. In the paper, the proposed control scheme is a consolidated execution of both the RF and CSA named as RFCSA. The principle goal of the proposed approach is to determine the efficiency of the PV system by the maximum power extraction. Here, the modeling design of QZS‐CMI is enhanced to deliver the maximum power from a PV power generating system. Initially, the objective function is defined based on their controller parameters and constraints such as voltages, current, power, and modulation index etc. These parameters are applied to the inputs of the proposed RFCSA technique. The proposed RFCSA technique is improved the voltage profile, power delivery, and minimizing the power oscillations while sharing the power to the load. The maximum power delivery to the load is ensured by an AI technique based on MPPT. The proposed AI‐based improved QZS‐CMI regulated the shoot‐through duty ratio and reduced the modulation burden. Moreover, the proposed RFCSA control technique reduced the injected power and regulates the dc link voltage, current, and frequency conditions. The proposed technique is implemented in MATLAB/Simulink platform, and their output performance is compared with the existing methods for different loading conditions.

This paper proposes a circuit topology of a single-stage three-phase current-source photovoltaic (PV) gridconnected inverter with high voltage transmission ratio (VTR). Also, an improved zone sinusoidal pulse width modulation (SPWM) control strategy and an activeclamped sub circuit that can suppress the energy storage switch's turn-off voltage spike are introduced. The circuit topology, control strategy, steady principle characteristics, and high-frequency switching process are analyzed profoundly, as well as the VTR's expression and design criterion of the centertapped energy storage inductor. The improved zone SPWM control strategy consists of two control loops, namely, the outer loop of input dc voltage of PV cells with the maximum power point tracking and the inner loop of the energy storage inductor current. The experimental results of a 3-kW 96VDC/380V50Hz3φAC prototype have shown that this kind of a three-phase inverter has the excellent performances such as singlestage power conversion, high VTR and power density, and high conversion efficiency. Nonetheless, it has small energy storage inductor and output CLfilter, low output current total harmonic distortion, and flexible voltage configuration of the PV cells. This study provides an effective design method for single-stage three-phase inverting with high VTR. Index Terms-Current source, high voltage transmission ratio (VTR), photovoltaic (PV) grid-connected inverter, three-phase,zone Sinusoidal Pulse width modulation (SPWM) control strategy.

This paper is aimed at the implementation of a Neuro-Fuzzy Based MPPT in Transformer less grid using CUK Converter in Step-Up Mode. A single diode model is preferred for photovoltaic array and simulation study is done by using MATLAB SIMULINK. Voltage and current are the inputs of ANFIS logic controller and the effective value of maximum power is the output. Thus in addition to supplying voltage by the inverter without Transformer for compensate the reactive power not exceeding its power rating. This results in utilization of PV system at night and at periods of low irradiation. Rules relating the input and output of ANFIS Logic Controller are written and simulation is performed. A DC-DC CUK is used for maintaining constant DC input to the inverter at various conditions of irradiation and temperature. Gating pulses to the inverter are generated by PI (Proportional integral) controller. Simulation model of a 1000W solar panel is developed and results are obtained with ANFIS logic controller for different irradiation and temperature conditions.