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This paper introduces a Multi-Level Cascade Inverter (MLI) based on Enhanced Quasi-Z Source Inverter (MQZSI) to connect photovoltaic (PV) systems based on the proposed method. Usually the interface among PV power supply and load is completed with MQZS-CMLI. In this paper, the proposed control scheme is comprehensive implementation of Recalling Enhanced Recurrent Neural Network (RERNN) and Quasi-Opposite Chemical Reaction Optimization (QOCRO) named as RENCO. The main objective of proposed method is to decide the efficiency of the PV system by the maximal power extraction. Here, MQZS-CMLI's modeling design contains suitable number of components, other than their capacitors and semiconductors comply with low-voltage stress. It is improved for providing that maximum power of the PV power generation system. At first, the goal function is described according to the parameters and limitations of controller (like voltage, current, power, modulation index, so on). These parameters apply to recommend RENCO technology input. The proposed RENCO technology improves voltage distribution, power transmission, and minimizes power fluctuations while sharing power with load. The proposed MPPT-based technology ensures that the maximum power is provided to load. The proposed method adjust the duty cycle of MQZS-CMLI and reduces the modulation load. Finally, the proposed technology is executed on the MATLAB/Simulink platform, and its output efficiency is compared to existing systems under dissimilar load circumstances. [ABSTRACT FROM AUTHOR]